Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed.
Response to Amendment
Applicant’s amendments dated 02/04/2026 have been received and filed.
Response to Arguments
Applicant's arguments filed 02/04/2026 have been fully considered. Some are found persuasive, and some are not.
Applicant’s arguments regarding the claims being directed towards altering the state of the ESS prior to an uphill portion of the trip in regards to the 101 and 103 rejection is found unpersuasive. While the claim limitations state that there is a fuel cell system that is arranged to perform this task, the task is not performed in a positively cited manner. No limitation cites that a battery is charged, only that a fuel cell is capable of performing the task. The end results of the claims are selecting of routes. Even if the routes were useful, the mere selection of routes is not understood to integrate the judicial exception into a practical application. A step indicating that the vehicle is controlled to travel the route via an autonomous system. Additionally, limitations that cite that the fuel cell specifically charges the ESS prior to an uphill section (in response to one being detected would be a stronger limitation) would be a stronger argument.
Additionally, the argument that the claims show a strategy for charge management in regards to the 101 rejection is not persuasive. While the examiner does believe that this is the intent of the invention, the examiner does not believe the claims capture this. There is no positively recited claim that controls the power train, only a possibility that a particular route may lead to potential power train profiles. Additionally, the claims do not suggest what any sort of strategy might be. There are uphill and downhill portions of the route, candidate routes are determined, the state of charge as well as regenerative braking is predicted, and then based off of that a route is selected. Whether the goal is to keep the SoC below a threshold, above a threshold, maximize regenerative braking, or maintain efficient use of power is not apparent from the claims themselves.
The following arguments regarding the rejection under U.S.C. 103 have been considered and found unpersuasive. The argument that Son and Lane do not teach identifying downhill portions of the routes is found unpersuasive. Son and Lane repeatedly refer to downhill portions of the route and utilize equations, functions, and algorithms to determine state of charge before and after these portions. They must identify these portions as uphill or downhill in order to do this. The examiner has provided more paragraphs that cite this.
The argument that Son can not read on the claims because Son is directed broadly towards energy efficiency and using a fuel cell to preemptively power an ESS may not be fuel efficient is found unpersuasive. If the battery power were necessary to get over the uphill portion of the route, then it would be necessary for Son to perform the task. To not do this would make the route impossible, which would reasonably be worse than being fuel inefficient.
The argument that Lane is not relevant to preemptive energy charging is found unpersuasive. While Lane does not specifically state using a fuel cell to power an ESS, Lane does preemptively charge an ESS when it is necessary to reach a destination. The argument that this would not apply because Lane’s charging is triggered by destination requirements and not tactical anticipation of identified topographical features like an uphill climb is found unpersuasive because Lane cites the topography as a considering on whether or not a destination can be reached, which would make topography features one of the considerations. “[0042] The dispatch controller 120 and/or the ECM 122 can also determine the route data 136, including a particular path for the route 110, at least in part by determining an expected energy consumption level 144 associated with travel along the route 110 from the current location of the machine 102 to the maintenance station 108. The expected energy consumption level 144 can be a combination of energy expected to be consumed by, and energy expected to be captured during, operations of the machine 102 while traveling along the route 110. The expected energy consumption level 144 can be based on a model of the machine 102 that indicates a size of the machine 102, a weight of the machine 102, a weight of a payload carried by the machine 102, and/or based on physics models indicating amounts of energy likely to be consumed and/or captured based on grades and/or distances of the segments 142, and/or other factors. In some examples, the expected energy consumption level 144 can be determined by a machine learning model that has been trained on historical data indicating energy consumption levels associated with traversal of terrain by the machine 102 or similar machines through segments 142 associated one or more grades and/or distances.”
The argument that there is no rationale to combine Son and Lane because one is directed towards fuel efficient pathing, and the other is directed towards charge management for operations is found unpersuasive. Both are directed towards monitoring battery usage, slope, and watching state of charge in order to ensure effective use of vehicles. The examiner believes that they are both related to the application of energy management, state of charge management, and considering slopes for pathing.
The argument that Son does not identify a “midpoint” onset of a downhill section is persuasive. Son does not teach alternative routes for a midpoint on a trip and only teaches the alternative routes for a larger path. Lane, however, does teach the use of alternative routes (loops, larger paths) in order to use excess energy before wanting a specific state of charge at a specific location. The examiner believes that the claims are obvious in light of these teachings Therefore, the examiner has updated the rejection below to include Lane’s teaching.
Please refer to the rejections below.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, and 3-20 are rejected under 35 U.S.C. 101 because they are directed towards a mental process without significantly more.
Claim 1 Cites
A computer system for a heavy-duty vehicle comprising a fuel-cell system and an electrical energy storage system, ESS, where the fuel-cell system is arranged to preemptively charge the ESS prior to an uphill portion of a trip to be traversed by the heavy-duty vehicle, wherein the computer system comprises processing circuitry configured to:
identify a downhill portion of a trip to be undertaken by the heavy-duty vehicle,
determine at least two candidate routes leading from a starting location along the trip to an onset of the downhill portion of the trip,
predict a state of energy, SoE, of the ESS at the onset of the downhill portion for each candidate route, and
select a proposed route out of the candidate routes at least in part based on the predicted SoE for each candidate route and on an estimated amount of energy regenerated by traversing the downhill portion of the trip.
Step 2A prong one evaluation: Judicial Exception – Yes – Mental Processes
The Office submits that the foregoing bolded limitation(s) constitutes judicial exceptions in terms of “mental processes” because under its broadest reasonable interpretation, the claim covers performance using mental.
The claims recite identifying a downhill portion of a trip. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider a trip, and identify downhill portions of the trip. Thus this step is directed to a mental process.
The claims recite determining at least two candidate routes from a starting location to an onset of a downhill portion of a trip. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider a trip, and determine 2 ways to get to a downhill portion of the trip. Thus this step is directed to a mental process.
The claims recite predicting a state of energy at the onset of the downhill portion for the candidate routes. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider a trip, and predict a state of charge at a portion of a downhill portion (I will be going downhill for a while and my charge will be full when I reach another downhill portion). Thus this step is directed to a mental process.
The claims recite selecting a proposed route based on the SoE at the downhill portion as well as predicted regenerated braking. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider a trip, and predict a state of charge at a portion of a downhill portion (I will be going downhill for a while and my charge will be full when I reach another downhill portion), consider the amount of charge they’d gain (I may fill 20% of my battery) and choose an optimal route based on this information. Thus this step is directed to a mental process.
Step 2A Prong Two evaluations
Claims are evaluated whether as a whole it integrates the recited judicial exception into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea or adding/performing insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”).
The claims recite identifying portions of routes, determining routes, predicting states of energy, and selecting routes using a device, a processor, a memory, a computer, processing circuitry, and a non-transitory computer readable storage medium. The above listed actions are recited at a high level of generality. The computer/circuitry that facilitate the steps are described by the specification at a high level of generality. The generically recited computer merely describes how to generally “apply” the otherwise mental/extra solution processes using a generic or general-purpose processor. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The dependent claims recite obtaining sensor data and sending sensor data. The previously listed action is described at a high level of generality. The sending, receiving and production of signals is considered well known, common, and conventional. Producing signals, sending and receiving data and performing functions known in the art is considered insignificant extra solution activity. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claim is not patent eligible.
2B Evaluation: Inventive Concept – No
Claims are evaluated as to whether the claims as a whole amount to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim.
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than possible uses for the output of the abstract idea. The same analysis applies here in 2B, i.e., possible uses for information or mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Thus the claims are not patent eligible.
Claim 18 cites:
A computer-implemented method performed by a computer system in a heavy-duty vehicle comprising a fuel-cell system and an electrical energy storage system, ESS, where the fuel-cell system is arranged to preemptively charge the ESS prior to an uphill portion of a trip to be traversed by the heavy-duty vehicle, the method comprising
identifying, by processing circuitry of the computer system, a downhill portion of a trip to be undertaken by the heavy-duty vehicle,
determining, by the processing circuitry, at least two candidate routes leading from a starting location along the trip to an onset of the downhill portion of the trip,
predicting, by the processing circuitry, a state of energy, SoE, of the ESS at the onset of the downhill portion for each candidate route, and
selecting, by the processing circuitry, a proposed route out of the candidate routes at least in part based on the predicted SoE for each candidate route and on an estimated amount of energy regenerated by traversing the downhill portion of the trip.
Step 2A prong one evaluation: Judicial Exception – Yes – Mental Processes
The Office submits that the foregoing bolded limitation(s) constitutes judicial exceptions in terms of “mental processes” because under its broadest reasonable interpretation, the claim covers performance using mental.
The claims recite identifying a downhill portion of a trip. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider a trip, and identify downhill portions of the trip. Thus this step is directed to a mental process.
The claims recite determining at least two candidate routes from a starting location to an onset of a downhill portion of a trip. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider a trip, and determine 2 ways to get to a downhill portion of the trip. Thus this step is directed to a mental process.
The claims recite predicting a state of energy at the onset of the downhill portion for the candidate routes. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider a trip, and predict a state of charge at a portion of a downhill portion (I will be going downhill for a while and my charge will be full when I reach another downhill portion). Thus this step is directed to a mental process.
The claims recite selecting a proposed route based on the SoE at the downhill portion as well as predicted regenerated braking. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider a trip, and predict a state of charge at a portion of a downhill portion (I will be going downhill for a while and my charge will be full when I reach another downhill portion), consider the amount of charge they’d gain (I may fill 20% of my battery) and choose an optimal route based on this information. Thus this step is directed to a mental process.
Step 2A Prong Two evaluations
Claims are evaluated whether as a whole it integrates the recited judicial exception into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea or adding/performing insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”).
The claims recite identifying portions of routes, determining routes, predicting states of energy, and selecting routes using a device, a processor, a memory, a computer, processing circuitry, and a non-transitory computer readable storage medium. The above listed actions are recited at a high level of generality. The computer/circuitry that facilitate the steps are described by the specification at a high level of generality. The generically recited computer merely describes how to generally “apply” the otherwise mental/extra solution processes using a generic or general-purpose processor. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The dependent claims recite obtaining sensor data and sending sensor data. The previously listed action is described at a high level of generality. The sending, receiving and production of signals is considered well known, common, and conventional. Producing signals, sending and receiving data and performing functions known in the art is considered insignificant extra solution activity. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claim is not patent eligible.
2B Evaluation: Inventive Concept – No
Claims are evaluated as to whether the claims as a whole amount to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim.
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than possible uses for the output of the abstract idea. The same analysis applies here in 2B, i.e., possible uses for information or mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Thus the claims are not patent eligible.
Claim 3 cites
The computer system according to claim 1, where the processing circuitry is configured to predict the SoE of the ESS at least in part by accounting for a predicted fuel cell charging operation along each candidate route.
Claim 4 cites
The computer system according to claim 1, where the processing circuitry is configured to predict the SoE of the ESS at the onset of the downhill portion for each candidate route at least in part by identifying uphill portions along the candidate routes.
Claim 5 cites
The computer system according to claim 1, where the processing circuitry is configured to implement a digital twin of the energy system of the heavy-duty vehicle, and to predict the SoE of the ESS at the onset of the downhill portion for each candidate route at least in part based on the digital twin.
Claim 6 cites
The computer system according to claim 1, where the processing circuitry is configured to receive prerecorded SoE profile data from on-board data storage and/or from a remote server for at least a part of the trip.
Claim 7 cites:
The computer system according to claim 6, where the processing circuitry is configured to predict the SoE of the ESS at the onset of the downhill portion for each candidate route based at least in part on the prerecorded SoE profile data.
Claim 8 cites
The computer system according to claim 1, where the processing circuitry is configured to select the proposed route out of the candidate routes at least in part based on an energy storage capacity of the ESS.
Claim 9 cites:
The computer system according to claim 8, where the processing circuitry is configured to determine a current energy storage capacity of the ESS based at least in part on ambient temperature.
Claim 10 cites:
The computer system according to claim 1, where the heavy-duty vehicle comprises an energy dissipation device, where the processing circuitry is configured to select the proposed route out of the candidate routes at least in part based on an energy dissipating capacity of the energy dissipation device.
Claim 11 cites:
The computer system according to claim 10, where the processing circuitry is configured to determine a current energy dissipating capacity of the energy dissipation device based at least in part on a current temperature of the energy dissipation device.
Claim 12 cites:
The computer system according to claim 1, where the processing circuitry is configured to select the proposed route out of the candidate routes at least in part based on endurance braking capacity and/or a cooling capacity of a service brake system of the heavy-duty vehicle.
Claim 13 cites:
The computer system according to claim 1, where the processing circuitry is configured to propose an ESS discharge stop along the route prior to the downhill portion in case none of the candidate routes satisfies an SoE acceptance criteria at the onset of the downhill portion.
Claim 14 cites:
The computer system according to claim 1, where the starting location is a current location of the heavy-duty vehicle.
Claim 15 cites:
The computer system according to claim 1, where the processing circuitry is configured to record an SoE profile along the trip as function of location of the heavy-duty vehicle.
Claim 16 cites:
The computer system according to claim 15, where the processing circuitry is configured to transmit the recorded SoE profile along the trip to on-board data storage and/or to a remote server.
Claim 17 cites:
A heavy-duty vehicle comprising a computer system according to claim 1.
Claim 19 cites:
A computer program product comprising program code for performing, when executed by the processing circuitry, the method of claim 18.
Claim 20 cites:
A non-transitory computer-readable storage medium comprising instructions, which when executed by the processing circuitry, cause the processing circuitry to perform the method of claim 18.
Step 2A prong one evaluation: Judicial Exception – Yes – Mental Processes
The Office submits that the foregoing bolded limitation(s) constitutes judicial exceptions in terms of “mental processes” because under its broadest reasonable interpretation, the claim covers performance using mental.
Claim 3 cites predicting the state of charge accounting for fuel cell charging operation along the candidate route. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider fuel cell charging from historic data along certain segments and estimate a change to the state of energy. Thus this step is directed to a mental process.
Claim 4 cites predicting the state of energy by identifying uphill routes. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider uphill portions of routes and estimate how they will affect the state of energy. Thus this step is directed to a mental process.
Claim 7 cites predicting the SoE based on prerecorded profile data. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider prerecorded data that may assist them with the estimations . Thus this step is directed to a mental process.
Claim 8 cites selecting the proposed route based on storage capacity of the ESS. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider expected energy gain and loss, and consider that the battery will likely be over capacity at points, and choose based off of that . Thus this step is directed to a mental process.
Claim 9 cites determining a current energy storage capacity of the ESS based on an ambient temperature. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider a simple equation that equates capacity to temperature. Thus this step is directed to a mental process.
Claim 10 cites selecting a proposed route based on energy dissipating capacity of the energy dissipation device. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider the energy dissipating capacity, consider the likely energy that will be created while braking on a downhill portion, and consider the trajectory safe, and select another route. Thus this step is directed to a mental process.
Claim 11 cites determining a current energy capacity based on a current temperature of the device. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider a simple equation of correlation between capacity and temperature. Thus this step is directed to a mental process.
Claim 12 cites selecting a proposed route based on endurance braking capacity or cooling capacity of a service brake. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the limitation that processing circuitry be programed to perform the task. That is, other than reciting “processor”, or “memory”, nothing in the claim precludes the element being done in the mind. A person could mentally consider a braking requirement, consider the brakes available, and choose routes that will not destroy their brakes. Thus this step is directed to a mental process.
Step 2A Prong Two evaluations
Claims are evaluated whether as a whole it integrates the recited judicial exception into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea or adding/performing insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”).
The claims recite identifying portions of routes, determining routes, predicting states of energy, and selecting routes using a device, a processor, a memory, a computer, processing circuitry, a digital twin, and a non-transitory computer readable storage medium. The above listed actions are recited at a high level of generality. The computer/circuitry that facilitate the steps are described by the specification at a high level of generality. The generically recited computer merely describes how to generally “apply” the otherwise mental/extra solution processes using a generic or general-purpose processor. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The dependent claims recite obtaining sensor data and sending sensor data. The previously listed action is described at a high level of generality. The sending, receiving and production of signals is considered well known, common, and conventional. Producing signals, sending and receiving data and performing functions known in the art is considered insignificant extra solution activity. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claim is not patent eligible.
2B Evaluation: Inventive Concept – No
Claims are evaluated as to whether the claims as a whole amount to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim.
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than possible uses for the output of the abstract idea. The same analysis applies here in 2B, i.e., possible uses for information or mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Thus the claims are not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3-4, 8, 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Son et al (US Pub 2019/0178662 A1), hereafter known as Son, in light of Lane et al (US Pub 2023/0168696 A1), hereafter known as Lane.
For Claim 1, Son teaches A computer system for a vehicle comprising a fuel-cell system and an electrical energy storage system, ESS, where the heavy-duty vehicle comprises a fuel-cell system arranged to provide power to a trip to be traversed by the heavy-duty vehicle wherein the computer system comprises processing circuitry configured to: ([0027] It is understood that the term “vehicle” or “vehicular” or other similar term as used herein is inclusive of motor vehicles in general such as passenger automobiles including sports utility vehicles (SUV), buses, trucks, various commercial vehicles, watercraft including a variety of boats and ships, aircraft, and the like, and includes hybrid vehicles, electric vehicles, plug-in hybrid electric vehicles, hydrogen-powered vehicles and other alternative fuel vehicles (e.g. fuels derived from resources other than petroleum). As referred to herein, a hybrid vehicle is a vehicle that has two or more sources of power, for example both gasoline-powered and electric-powered vehicles.)
identify a downhill portion of a trip to be undertaken by the vehicle, ([0047] The traffic information may include at least one cycle of traffic lights, an average speed in each section, acceleration/deceleration information in each section, or traffic jam degree/traffic volume information in each section. Further, the geographic information may include slope information of each section, section length information, etc. The weather information may include wind velocity, wind direction, rain, snow and humidity information, etc., which are required to calculate a driving load.
[0046] First, information input to the driving load calculation unit 241 may be driving environment information which may influence energy change based on driving of the vehicle along each of at least one path located between a point of departure and a destination. For example, the driving environment information may include at least one of traffic information, geographic information or weather information.
[0047] The traffic information may include at least one cycle of traffic lights, an average speed in each section, acceleration/deceleration information in each section, or traffic jam degree/traffic volume information in each section. Further, the geographic information may include slope information of each section, section length information, etc. The weather information may include wind velocity, wind direction, rain, snow and humidity information, etc., which are required to calculate a driving load.
[0052] Next, operations of the output/brake energy calculation unit 243 and the consumption/regeneration energy and SOC calculation unit 245 will be described with reference to FIG. 6 and FIGS. 7A-7B. FIG. 6 is a graph illustrating a method of calculating energy in accordance with one exemplary embodiment of the present invention, and FIGS. 7A-7B are graphs illustrating a method of calculating and correcting an SOC in accordance with one exemplary embodiment of the present invention. In FIG. 6 and FIGS. 7A-7B, it may be assumed that one path is divided into three sections according to slope. In particular, an initial section is a flat section, a middle section is an uphill section having a shorter distance than that of the initial section, and a final section is a downhill section having a relatively long distance.
[0051] In the determination of the driving load, the driving load calculation unit 241 may determine the driving load using slope information, as exemplarily shown in FIG. 5B. The driving load calculation unit 241 may be configured to calculate a driving load of the vehicle in each of a plurality of sections constituting each of at least one path from a point of departure to a destination using the driving environment information, as described above.
[0063] Information regarding the determined path may be output to the outside (e.g., the navigation system), and guidance of the path having the minimized energy consumption may be provided to a driver. Through the above-described path search method, an optimum path may be provided to a driver intending to minimize energy consumed to reach a destination regardless of time and distance, using characteristics (e.g., ISG, regenerative braking, efficiency characteristics, etc.) of hybrid electric vehicles using both an internal combustion engine and a motor and various information (e.g., precise traffic information, road slopes, weather, etc.).
[0006] FIG. 1 is a graph illustrating one example of a general method of calculating energy consumption in consideration of a driving path. With reference to FIG. 1, a path on which energy consumption is calculated includes a flatland section, an uphill section and a downhill section. Energy consumptions E.sub.output1, E.sub.output2 and E.sub.output3 in the respective sections may be calculated by multiplying a driving load by the distances of the respective sections, and the energy consumption E.sub.output3 in the downhill section may be zero (i.e., E.sub.output3=0) unless a driver separately accelerates the vehicle. Accordingly, total energy consumption E.sub.sum on the path may be calculated as “E.sub.output1+E.sub.output2+E.sub.output3”.
[0064] For example, a section, in which a vehicle stoppage situation caused by traffic lights, congested areas, etc. is continued but energy may be effectively used, may be selected to minimize energy consumption in this section even if the time required to pass through the section is longer. Further, since regeneration efficiency is considered, a path having a high downward slope may be searched and, thus, regeneration energy may be maximized. In particular, in a section having a high SOC, a path on which a downhill section comes after an uphill section rather than a path on which an uphill section comes after a downhill section may be searched in consideration of a limit in a quantity of regeneration and, in a section having a low SOC, a path on which an uphill section comes after a downhill section rather than a path on which a downhill section comes after an uphill section may be searched to secure the SOC.)
determine at least two candidate routes leading from a starting location along the trip to an end of the trip, including an onset of the downhill portion of the trip, ([0014] According to the purpose of the invention, as embodied and broadly described herein, a method of searching for a path of a hybrid electric vehicle may include acquiring driving environment information, determining a driving load of the vehicle in each of a plurality of sections of at least one path from a point of departure to a destination, determining output energy and brake energy in each of the sections based on the determined driving load, determining consumption energy and regeneration energy in each of the sections based on the output energy and the brake energy in each of the sections, determining energy consumption on each of the at least one path by summing the consumption energies and the regeneration energies in the sections, and determining an energy minimization path by comparing the determined energy consumptions on the at least one path.
[0059] When the consumption/regeneration energy and SOC calculation unit 245 determines consumption energy and regeneration energy in each section in consideration of the SOC, the path determination unit 247 may be configured to determine energy consumption on each of the respective paths by summing the consumption energies in the respective sections of each path, and determine a path having the lowest energy consumption by comparing the energy consumptions on the respective paths. Information regarding the determined path may be output to the outside (e.g., the navigation system may be configured to output the information to a driver within the vehicle).
There can be more than one path to consider.)
predict a state of energy, SoE, of the ESS at the onset of the downhill portion for each candidate route, and ([0061] A driving load F.sub.load of the vehicle in each of sections of each of a plurality of paths may be calculated through the driving environment information (e.g., F.sub.load=ma+F.sub.aero+F.sub.R.R+mg sin θ) (Operation S820), output/brake energies in each section may be calculated based on the driving load F.sub.load (Operation S830), and consumption/regeneration energies in each section may be calculated based on the output/brake energies (Operation S840). A SOC in each section may be calculated in consideration of the consumption/regeneration energies in each section, a fuel/battery consumption ratio according to the driving load, and maximum/minimum SOCs (Operation S850). Operations S820 to S850 were described above in detail with reference to FIGS. 5A-7B, and a redundant description thereof will thus be omitted because it is considered to be unnecessary.)
select a proposed route out of the candidate routes at least in part based on the predicted SoE for each candidate route and on an estimated amount of energy regenerated by traversing the downhill portion of the trip. ([0062] When the consumption energy and the regeneration energy in each section in consideration of the SOC may be determined, energy consumption on each path may be calculated by summing the consumption energies and the regeneration energies in the respective sections of each path (Operation S860), and a path having the lowest energy consumption may be determined by comparing the energy consumptions on the respective paths (Operation S870).
[0063] Information regarding the determined path may be output to the outside (e.g., the navigation system), and guidance of the path having the minimized energy consumption may be provided to a driver. Through the above-described path search method, an optimum path may be provided to a driver intending to minimize energy consumed to reach a destination regardless of time and distance, using characteristics (e.g., ISG, regenerative braking, efficiency characteristics, etc.) of hybrid electric vehicles using both an internal combustion engine and a motor and various information (e.g., precise traffic information, road slopes, weather, etc.).)
Son does not teach that the vehicle is heavy duty
That the fuel cell system is arranged to preemptively charge the ESS prior to an uphill portion of a trip,
Determining at least two candidate routes leading from a starting location along the trip to an onset of the downhill portion of the trip.
Lane, however, does teach that the vehicle is heavy duty. ([0016] The machine 102 can, in some examples, be a commercial or work machine, such as a mining machine, earth-moving machine, backhoe, scraper, dozer, loader (e.g., large wheel loader, track-type loader, etc.), shovel, truck (e.g., mining truck, haul truck, on-highway truck, off-highway truck, articulated truck, etc.), a crane, a pipe layer, farming equipment, or any other type of mobile machine or vehicle. As noted above, the machine 102 can operate at, and/or travel around, the worksite 100. The worksite 100 can be a mine site, a quarry, a construction site, or any other type of worksite or work environment. As an example, the machine 102 can be a haul truck that moves dirt, rocks, gravel, and/or other material around the worksite 100. In other examples, the machine 102 can be an electric automobile or other type of mobile machine used for personal transportation, commercial transportation, or other purposes, such as an electric vehicle configured to travel on public and/or private roads. In these examples, the worksite 100 can include navigable areas through which the machine 102 can travel.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Lane so that the vehicle is a heavy duty vehicle because heavy duty vehicles would also be expected to benefit from methods that optimize energy efficiency and maintaining the energy level of a battery within a range because it would prevent the vehicle from running out of energy, and it would prevent regenerative braking from being wasted when a battery is already fully charged during regenerative braking.
Son, however, does teach that in situations in which uphill portions are upcoming, a high SoC is preferred. ([0064] For example, a section, in which a vehicle stoppage situation caused by traffic lights, congested areas, etc. is continued but energy may be effectively used, may be selected to minimize energy consumption in this section even if the time required to pass through the section is longer. Further, since regeneration efficiency is considered, a path having a high downward slope may be searched and, thus, regeneration energy may be maximized. In particular, in a section having a high SOC, a path on which a downhill section comes after an uphill section rather than a path on which an uphill section comes after a downhill section may be searched in consideration of a limit in a quantity of regeneration and, in a section having a low SOC, a path on which an uphill section comes after a downhill section rather than a path on which a downhill section comes after an uphill section may be searched to secure the SOC.)
Lane, however, does teach ensuring that the vehicle has a sufficient state of charge prior to an uphill portion of a trip. ([0039] As a non-limiting example, the dispatch controller 120 and/or the ECM 122 may determine that travel through the route 110 would cause the SoC of the battery 104 to drop below the target SoC 112 of a service operation by the time the machine 102 reaches the maintenance station 108. The dispatch controller 120 and/or the ECM 122 can accordingly cause the machine 102 to visit the charging station 106 or another charging station 106 to increase the SoC of the battery 104 to a target starting SoC before beginning travel along the route 110, as discussed further below. In this example, the dispatch controller 120 and/or the ECM 122 can determine the target starting SoC as an SoC that, if decreased by an amount of energy predicted to be consumed during traversal of the route 110 by the machine 102, would cause the SoC of the battery 104 to satisfy the target SoC 112 associated with the service operation when the machine 102 reaches the maintenance station.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Lane such that the fuel cell system is arranged to preemptively charge the ESS prior to an uphill portion of a trip.
It would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in this way because it could allow the vehicle to utilize both sources of energy during the uphill climb, in case that becomes necessary to power the vehicle up the hill. Additionally, it is important to note that the limitation does not specifically cite that the fuel cell system charges the ESS, or that it does so in response to detecting an uphill portion of a trip, only that it is arranged to do so prior to an uphill portion of a trip. Any fuel cell system that is attached to an electric battery that could potentially charge an ESS before an uphill portion of the trip would meet this limitation. The examiner understands that it is common for fuel cell hybrid systems to be capable of this task.
Lane, however, does teach that if the state of charge of the vehicle is too high at the end of the trip, the trip can be adjusted to add more loops, work, or following a less direct path. [0048] As a non-limiting example, if the target SoC 112 is a specific SoC value or a specific range of SoC values, and the expected energy consumption level 144 for the route 110 would cause the SoC of the battery 104 to be above the target SoC 112 at the end of the route 110, the path of the route 110 can be changed to increase the expected energy consumption level 144 to a value equal to a difference between the current SoC 126 and the target SoC 112. For instance, the dispatch controller 120 or the ECM 122 can adjust the path of the route 110 to increase a total travel distance associated with the route 110 by following a less-direct path to the maintenance station 108 and/or by adding loops or repeated sections of the path, thereby increasing the expected energy consumption level 144 associated with the route 110. As another example, the dispatch controller 120 or the ECM 122 can adjust one or more portions of the route 110 to go up steeper hills or grades, and thereby increase the expected energy consumption level 144 associated with the route 110.
[0049] As still another example, the dispatch controller 120 or the ECM 122 can increase the expected energy consumption level 144 associated with the route 110 by adjusting the route 110 so that the machine 102 performs one or more work operations along the route 110. For instance, the dispatch controller 120 or the ECM 122 can have a list of work tasks to be performed by the machine 102 and/or any other machine, and can assign one or more of the work tasks to the machine 102. As an example, if the machine 102 is a haul truck, the dispatch controller 120 can assign the haul truck to pick up a payload at a first location on the route 110, carry the payload to a second location on the route 110, and drop off the payload at the second location before continuing to further locations along the route 110. The dispatch controller 120 or the ECM 122 can accordingly adjust the route 110 and/or corresponding dispatch data 134 to cause the machine 102 to travel to one or more work locations, perform one or more work operations, pick up and transport one or more payloads through one or more portions of the route 110, and/or otherwise consume additional energy by performing one or more work operations along the route 110.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Lane such that the method will be determining at least two candidate routes leading from a starting location along the trip to an onset of the downhill portion of the trip.
It would be obvious to one of ordinary skill in the art prior to the effective filing date to do this because in a situation in which there is expected to be too much charge at the end of the trip or segment such that damage could be caused to the vehicle, then it would be useful to ensure that there is less charge before that segment begins. Modifying the route or taking an alternative route would be one expected way to do this, as taught by Lane.
For Claim 4, Son teaches The computer system according to claim 1, where the processing circuitry is configured to predict the SoE of the ESS at the onset of the downhill portion for each candidate route at least in part by identifying uphill portions along the candidate routes. ([0004] For example, a driving load F.sub.load of a vehicle may be calculated by Equation “F.sub.load=ma+F.sub.aero+F.sub.R.R.+mg sin θ” wherein, m represents a weight of the vehicle, a represents an acceleration of the vehicle, F.sub.aero represents air resistance, F.sub.R.R. represents rolling resistance of the vehicle, and θ represents a slope of a current driving road. Particularly, the slope θ of the current driving road may be acquired using navigation information, and the rolling resistance F.sub.R.R. and weight m of the vehicle may be constants, and air resistance F.sub.aero may be calculated using weather information (e.g., temperature, wind direction, wind velocity, humidity, etc.) and a speed of the vehicle.
Slope is considered as a part of the SoE.)
For Claim 8, Son teaches The computer system according to claim 1, where the processing circuitry is configured to select the proposed route out of the candidate routes at least in part based on an energy storage capacity of the ESS. ([0057] However, such a calculation may not accord with management of an SOC in an actual hybrid electric vehicle. For example, when the SOC reaches the maximum set value SOC.sub.max, the SOC is not increased anymore and, when the SOC reaches the minimum set value SOC.sub.min, it may be difficult to drive the electric motor. Therefore, an SOC change may be calculated through consumption energy and regeneration energy in each section, the SOC change may be applied to an SOC start value of the corresponding section, and correction may be executed according to whether an acquired SOC deviates from a range between the maximum and minimum set values.
[0058] In other words, the consumption/regeneration energy and SOC calculation unit 245 may be configured to correct energy consumption as being performed by the engine alone (i.e., E.sub.consumption=E.sub.consumption,engine, E.sub.consumption,motor=0) if SOC<SOC.sub.min, and correct the regeneration energy to zero (E.sub.regeneration=0) if SOC>SOC.sub.max. Accordingly, the maximum battery consumption energy E.sub.consumption2,motor which may be consumed in the middle section becomes “SOC.sub.2−SOC.sub.min”, the maximum regeneration energy in the final section is “SOC.sub.max−SOC.sub.min”, and, thus, actual SOCs may be corrected as below.)
For Claim 17, Son teaches A heavy-duty vehicle comprising a computer system according to claim 1. ([0029] Furthermore, control logic of the present invention may be embodied as non-transitory computer readable media on a computer readable medium containing executable program instructions executed by a processor, controller/control unit or the like. Examples of the computer readable mediums include, but are not limited to, ROM, RAM, compact disc (CD)-ROMs, magnetic tapes, floppy disks, flash drives, smart cards and optical data storage devices. The computer readable recording medium can also be distributed in network coupled computer systems so that the computer readable media is stored and executed in a distributed fashion, e.g., by a telematics server or a Controller Area Network (CAN).)
For Claim 18, Son teaches A computer-implemented method performed by a computer system in a heavy-duty vehicle comprising a fuel-cell system and an electrical energy storage system, ESS, where the heavy-duty vehicle comprises a fuel-cell system arranged to provide power to a trip to be traversed by the heavy-duty vehicle the method comprising ([0027] It is understood that the term “vehicle” or “vehicular” or other similar term as used herein is inclusive of motor vehicles in general such as passenger automobiles including sports utility vehicles (SUV), buses, trucks, various commercial vehicles, watercraft including a variety of boats and ships, aircraft, and the like, and includes hybrid vehicles, electric vehicles, plug-in hybrid electric vehicles, hydrogen-powered vehicles and other alternative fuel vehicles (e.g. fuels derived from resources other than petroleum). As referred to herein, a hybrid vehicle is a vehicle that has two or more sources of power, for example both gasoline-powered and electric-powered vehicles.)
identifying, by processing circuitry of the computer system, a downhill portion of a trip to be undertaken by the vehicle, ([0047] The traffic information may include at least one cycle of traffic lights, an average speed in each section, acceleration/deceleration information in each section, or traffic jam degree/traffic volume information in each section. Further, the geographic information may include slope information of each section, section length information, etc. The weather information may include wind velocity, wind direction, rain, snow and humidity information, etc., which are required to calculate a driving load.
[0046] First, information input to the driving load calculation unit 241 may be driving environment information which may influence energy change based on driving of the vehicle along each of at least one path located between a point of departure and a destination. For example, the driving environment information may include at least one of traffic information, geographic information or weather information.
[0047] The traffic information may include at least one cycle of traffic lights, an average speed in each section, acceleration/deceleration information in each section, or traffic jam degree/traffic volume information in each section. Further, the geographic information may include slope information of each section, section length information, etc. The weather information may include wind velocity, wind direction, rain, snow and humidity information, etc., which are required to calculate a driving load.
[0052] Next, operations of the output/brake energy calculation unit 243 and the consumption/regeneration energy and SOC calculation unit 245 will be described with reference to FIG. 6 and FIGS. 7A-7B. FIG. 6 is a graph illustrating a method of calculating energy in accordance with one exemplary embodiment of the present invention, and FIGS. 7A-7B are graphs illustrating a method of calculating and correcting an SOC in accordance with one exemplary embodiment of the present invention. In FIG. 6 and FIGS. 7A-7B, it may be assumed that one path is divided into three sections according to slope. In particular, an initial section is a flat section, a middle section is an uphill section having a shorter distance than that of the initial section, and a final section is a downhill section having a relatively long distance.
[0051] In the determination of the driving load, the driving load calculation unit 241 may determine the driving load using slope information, as exemplarily shown in FIG. 5B. The driving load calculation unit 241 may be configured to calculate a driving load of the vehicle in each of a plurality of sections constituting each of at least one path from a point of departure to a destination using the driving environment information, as described above.
[0063] Information regarding the determined path may be output to the outside (e.g., the navigation system), and guidance of the path having the minimized energy consumption may be provided to a driver. Through the above-described path search method, an optimum path may be provided to a driver intending to minimize energy consumed to reach a destination regardless of time and distance, using characteristics (e.g., ISG, regenerative braking, efficiency characteristics, etc.) of hybrid electric vehicles using both an internal combustion engine and a motor and various information (e.g., precise traffic information, road slopes, weather, etc.).
[0006] FIG. 1 is a graph illustrating one example of a general method of calculating energy consumption in consideration of a driving path. With reference to FIG. 1, a path on which energy consumption is calculated includes a flatland section, an uphill section and a downhill section. Energy consumptions E.sub.output1, E.sub.output2 and E.sub.output3 in the respective sections may be calculated by multiplying a driving load by the distances of the respective sections, and the energy consumption E.sub.output3 in the downhill section may be zero (i.e., E.sub.output3=0) unless a driver separately accelerates the vehicle. Accordingly, total energy consumption E.sub.sum on the path may be calculated as “E.sub.output1+E.sub.output2+E.sub.output3”.
[0064] For example, a section, in which a vehicle stoppage situation caused by traffic lights, congested areas, etc. is continued but energy may be effectively used, may be selected to minimize energy consumption in this section even if the time required to pass through the section is longer. Further, since regeneration efficiency is considered, a path having a high downward slope may be searched and, thus, regeneration energy may be maximized. In particular, in a section having a high SOC, a path on which a downhill section comes after an uphill section rather than a path on which an uphill section comes after a downhill section may be searched in consideration of a limit in a quantity of regeneration and, in a section having a low SOC, a path on which an uphill section comes after a downhill section rather than a path on which a downhill section comes after an uphill section may be searched to secure the SOC.)
determining, by the processing circuitry, at least two candidate routes leading from a starting location along the trip to the end of the trip, including an onset of the downhill portion of the trip, ([0014] According to the purpose of the invention, as embodied and broadly described herein, a method of searching for a path of a hybrid electric vehicle may include acquiring driving environment information, determining a driving load of the vehicle in each of a plurality of sections of at least one path from a point of departure to a destination, determining output energy and brake energy in each of the sections based on the determined driving load, determining consumption energy and regeneration energy in each of the sections based on the output energy and the brake energy in each of the sections, determining energy consumption on each of the at least one path by summing the consumption energies and the regeneration energies in the sections, and determining an energy minimization path by comparing the determined energy consumptions on the at least one path.
[0059] When the consumption/regeneration energy and SOC calculation unit 245 determines consumption energy and regeneration energy in each section in consideration of the SOC, the path determination unit 247 may be configured to determine energy consumption on each of the respective paths by summing the consumption energies in the respective sections of each path, and determine a path having the lowest energy consumption by comparing the energy consumptions on the respective paths. Information regarding the determined path may be output to the outside (e.g., the navigation system may be configured to output the information to a driver within the vehicle).
There can be more than one path to consider.)
predicting, by the processing circuitry, a state of energy, SoE, of the ESS at the onset of the downhill portion for each candidate route, and ([0061] A driving load F.sub.load of the vehicle in each of sections of each of a plurality of paths may be calculated through the driving environment information (e.g., F.sub.load=ma+F.sub.aero+F.sub.R.R+mg sin θ) (Operation S820), output/brake energies in each section may be calculated based on the driving load F.sub.load (Operation S830), and consumption/regeneration energies in each section may be calculated based on the output/brake energies (Operation S840). A SOC in each section may be calculated in consideration of the consumption/regeneration energies in each section, a fuel/battery consumption ratio according to the driving load, and maximum/minimum SOCs (Operation S850). Operations S820 to S850 were described above in detail with reference to FIGS. 5A-7B, and a redundant description thereof will thus be omitted because it is considered to be unnecessary.)
selecting, by the processing circuitry, a proposed route out of the candidate routes at least in part based on the predicted SoE for each candidate route and on an estimated amount of energy regenerated by traversing the downhill portion of the trip. ([0062] When the consumption energy and the regeneration energy in each section in consideration of the SOC may be determined, energy consumption on each path may be calculated by summing the consumption energies and the regeneration energies in the respective sections of each path (Operation S860), and a path having the lowest energy consumption may be determined by comparing the energy consumptions on the respective paths (Operation S870).
[0063] Information regarding the determined path may be output to the outside (e.g., the navigation system), and guidance of the path having the minimized energy consumption may be provided to a driver. Through the above-described path search method, an optimum path may be provided to a driver intending to minimize energy consumed to reach a destination regardless of time and distance, using characteristics (e.g., ISG, regenerative braking, efficiency characteristics, etc.) of hybrid electric vehicles using both an internal combustion engine and a motor and various information (e.g., precise traffic information, road slopes, weather, etc.).)
Son does not teach that the vehicle is heavy duty
That the fuel cell system is arranged to preemptively charge the ESS prior to an uphill portion of a trip,
Determining at least two candidate routes leading from a starting location along the trip to an onset of the downhill portion of the trip.
Lane, however, does teach that the vehicle is heavy duty. ([0016] The machine 102 can, in some examples, be a commercial or work machine, such as a mining machine, earth-moving machine, backhoe, scraper, dozer, loader (e.g., large wheel loader, track-type loader, etc.), shovel, truck (e.g., mining truck, haul truck, on-highway truck, off-highway truck, articulated truck, etc.), a crane, a pipe layer, farming equipment, or any other type of mobile machine or vehicle. As noted above, the machine 102 can operate at, and/or travel around, the worksite 100. The worksite 100 can be a mine site, a quarry, a construction site, or any other type of worksite or work environment. As an example, the machine 102 can be a haul truck that moves dirt, rocks, gravel, and/or other material around the worksite 100. In other examples, the machine 102 can be an electric automobile or other type of mobile machine used for personal transportation, commercial transportation, or other purposes, such as an electric vehicle configured to travel on public and/or private roads. In these examples, the worksite 100 can include navigable areas through which the machine 102 can travel.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Lane so that the vehicle is a heavy duty vehicle because heavy duty vehicles would also be expected to benefit from methods that optimize energy efficiency and maintaining the energy level of a battery within a range because it would prevent the vehicle from running out of energy, and it would prevent regenerative braking from being wasted when a battery is already fully charged during regenerative braking.
Son, however, does teach that in situations in which uphill portions are upcoming, a high SoC is preferred. ([0064] For example, a section, in which a vehicle stoppage situation caused by traffic lights, congested areas, etc. is continued but energy may be effectively used, may be selected to minimize energy consumption in this section even if the time required to pass through the section is longer. Further, since regeneration efficiency is considered, a path having a high downward slope may be searched and, thus, regeneration energy may be maximized. In particular, in a section having a high SOC, a path on which a downhill section comes after an uphill section rather than a path on which an uphill section comes after a downhill section may be searched in consideration of a limit in a quantity of regeneration and, in a section having a low SOC, a path on which an uphill section comes after a downhill section rather than a path on which a downhill section comes after an uphill section may be searched to secure the SOC.)
Lane, however, does teach ensuring that the vehicle has a sufficient state of charge prior to an uphill portion of a trip. ([0039] As a non-limiting example, the dispatch controller 120 and/or the ECM 122 may determine that travel through the route 110 would cause the SoC of the battery 104 to drop below the target SoC 112 of a service operation by the time the machine 102 reaches the maintenance station 108. The dispatch controller 120 and/or the ECM 122 can accordingly cause the machine 102 to visit the charging station 106 or another charging station 106 to increase the SoC of the battery 104 to a target starting SoC before beginning travel along the route 110, as discussed further below. In this example, the dispatch controller 120 and/or the ECM 122 can determine the target starting SoC as an SoC that, if decreased by an amount of energy predicted to be consumed during traversal of the route 110 by the machine 102, would cause the SoC of the battery 104 to satisfy the target SoC 112 associated with the service operation when the machine 102 reaches the maintenance station.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Lane such that the fuel cell system is arranged to preemptively charge the ESS prior to an uphill portion of a trip.
It would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in this way because it could allow the vehicle to utilize both sources of energy during the uphill climb, in case that becomes necessary to power the vehicle up the hill. Additionally, it is important to note that the limitation does not specifically cite that the fuel cell system charges the ESS, or that it does so in response to detecting an uphill portion of a trip, only that it is arranged to do so prior to an uphill portion of a trip. Any fuel cell system that is attached to an electric battery that could potentially charge an ESS before an uphill portion of the trip would meet this limitation. The examiner understands that it is common for fuel cell hybrid systems to be capable of this task.
Lane, however, does teach that if the state of charge of the vehicle is too high at the end of the trip, the trip can be adjusted to add more loops, work, or following a less direct path. [0048] As a non-limiting example, if the target SoC 112 is a specific SoC value or a specific range of SoC values, and the expected energy consumption level 144 for the route 110 would cause the SoC of the battery 104 to be above the target SoC 112 at the end of the route 110, the path of the route 110 can be changed to increase the expected energy consumption level 144 to a value equal to a difference between the current SoC 126 and the target SoC 112. For instance, the dispatch controller 120 or the ECM 122 can adjust the path of the route 110 to increase a total travel distance associated with the route 110 by following a less-direct path to the maintenance station 108 and/or by adding loops or repeated sections of the path, thereby increasing the expected energy consumption level 144 associated with the route 110. As another example, the dispatch controller 120 or the ECM 122 can adjust one or more portions of the route 110 to go up steeper hills or grades, and thereby increase the expected energy consumption level 144 associated with the route 110.
[0049] As still another example, the dispatch controller 120 or the ECM 122 can increase the expected energy consumption level 144 associated with the route 110 by adjusting the route 110 so that the machine 102 performs one or more work operations along the route 110. For instance, the dispatch controller 120 or the ECM 122 can have a list of work tasks to be performed by the machine 102 and/or any other machine, and can assign one or more of the work tasks to the machine 102. As an example, if the machine 102 is a haul truck, the dispatch controller 120 can assign the haul truck to pick up a payload at a first location on the route 110, carry the payload to a second location on the route 110, and drop off the payload at the second location before continuing to further locations along the route 110. The dispatch controller 120 or the ECM 122 can accordingly adjust the route 110 and/or corresponding dispatch data 134 to cause the machine 102 to travel to one or more work locations, perform one or more work operations, pick up and transport one or more payloads through one or more portions of the route 110, and/or otherwise consume additional energy by performing one or more work operations along the route 110.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Lane such that the method will be determining at least two candidate routes leading from a starting location along the trip to an onset of the downhill portion of the trip.
It would be obvious to one of ordinary skill in the art prior to the effective filing date to do this because in a situation in which there is expected to be too much charge at the end of the trip or segment such that damage could be caused to the vehicle, then it would be useful to ensure that there is less charge before that segment begins. Modifying the route or taking an alternative route would be one expected way to do this, as taught by Lane.
For Claim 19, Son teaches A computer program product comprising program code for performing, when executed by the processing circuitry, the method of claim 18. ([0028] Although exemplary embodiment is described as using a plurality of units to perform the exemplary process, it is understood that the exemplary processes may also be performed by one or plurality of modules. Additionally, it is understood that the term controller/control unit refers to a hardware device that includes a memory and a processor. The memory is configured to store the modules and the processor is specifically configured to execute said modules to perform one or more processes which are described further below.)
For Claim 20, Son teaches A non-transitory computer-readable storage medium comprising instructions, which when executed by the processing circuitry, cause the processing circuitry to perform the method of claim 18. ([0028] Although exemplary embodiment is described as using a plurality of units to perform the exemplary process, it is understood that the exemplary processes may also be performed by one or plurality of modules. Additionally, it is understood that the term controller/control unit refers to a hardware device that includes a memory and a processor. The memory is configured to store the modules and the processor is specifically configured to execute said modules to perform one or more processes which are described further below.)
Claims 5-7 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Son in light of Lane in light of Dalum et al (US Pub 2013/0179007 A1), hereafter known as Dalum.
For Claim 5, Son teaches The computer system according to claim 1, where the processing circuitry is configured to implement a calculation of the energy system of the heavy-duty vehicle, and to predict the SoE of the ESS at the onset of the downhill portion for each candidate route at least in part based on the calculation. ([0061] A driving load F.sub.load of the vehicle in each of sections of each of a plurality of paths may be calculated through the driving environment information (e.g., F.sub.load=ma+F.sub.aero+F.sub.R.R+mg sin θ) (Operation S820), output/brake energies in each section may be calculated based on the driving load F.sub.load (Operation S830), and consumption/regeneration energies in each section may be calculated based on the output/brake energies (Operation S840). A SOC in each section may be calculated in consideration of the consumption/regeneration energies in each section, a fuel/battery consumption ratio according to the driving load, and maximum/minimum SOCs (Operation S850). Operations S820 to S850 were described above in detail with reference to FIGS. 5A-7B, and a redundant description thereof will thus be omitted because it is considered to be unnecessary.)
Son does not teach the use of a digital twin.
Dalum, however, does teach the use of simulations to predict energy usage. ([0060] If the total expected job site energy usage is greater than the energy storage capacity, then hybrid vehicle drive system 12 may be operated in a charge sustain or charge accumulate mode when in transit and reserve all stored energy for job site usage (step 67). First prime mover 30 and/or APU may be operated at job site(s) 54 to provide additional energy. If the total expected job site energy usage is less than the energy storage capacity, then hybrid vehicle drive system 12 may be periodically operated in a charge deplete mode when in transit (step 68). Control system 14 may be utilized to monitor the amount of energy stored in rechargeable energy source 34 and maintain a sufficient energy level for expected job site usage. In one preferred embodiment, vehicle 10 is controlled with a goal to reduce on-site idling to power vehicle 10 and equipment 40 by ensuring that sufficient energy for equipment 40 is present in sources 34 and 38 at the job site. A model of the efficiency of vehicle 10 may reside in the software of the control system 14, fleet management system 17, or in another system such as a cloud based program or storage area. The model can be a mathematical representation that simulates the performance of various hybrid components, the vehicle power train and other inputs in one embodiment. Simulation can be validated against the actual performance of various components and the overall system. Once the model is working, adjustable parameters or software effecting performance of vehicle drive system 12 can be adjusted to determine whether overall efficiency of the vehicle 10 would be increased, or other goals met in accordance with one embodiment. The model may likely reside in a land based server or cloud, but could also be located in the controller of the vehicle 10 (e.g., control system 14) or other component on vehicle 10.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Lane such that a digital twin is used because simulations and digital twins are known to be effective methods of simulating hypothetical events for situations in which the physics of the environment are known and can be estimated. Using a digital twin would allow the system to accurately predict energy usage and would be expected to be useful in effectively estimating energy usage and generation.
For Claim 6, Son teaches The computer system according to claim 1,
Son does not teach where the processing circuitry is configured to receive prerecorded SoE profile data from on-board data storage and/or from a remote server for at least a part of the trip.
Dalum, however, does teach where the processing circuitry is configured to receive prerecorded SoE profile data from on-board data storage and/or from a remote server for at least a part of the trip. ([0059] Referring to FIGS. 4-5, a method estimates vehicle energy usage for job sites 54 and transit along an optimized route 56 to and from job sites 54. The location of job sites 54 and an optimized route 56 to and from job sites 54 is first determined (step 60). The available data for the expected job sites 54 is analyzed (step 62). If historical data is available for the job sites (e.g., historical data stored in internal database 16 and/or external database 18), it is used to estimate the total expected job site energy usage. If no historical data is available, the total expected job site usage is estimated using available data, such as the type and expected duration of job(s) (step 63). The available data for the expected route 56 is analyzed (step 64). If historical data is available for the route (e.g., historical data stored in internal database 16 and/or external database 18) it is used to estimate the total expected transit energy usage. If no historical data is available, the total expected transit usage is estimated using available data, such as route length, vehicle weight, road types, traffic patterns, etc (step 65). The total expected job site energy usage is then compared to the energy storage capabilities of vehicle 10 (e.g., the capacity and current charge levels of first rechargeable energy source 34) (step 66). The energy storage capabilities of vehicle 10 may be adjusted to account for expected gains while vehicle 10 is operating in a charge accumulate mode when in transit along route 56 to job sites 54.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Dalum so that historic data is used to calculate the SoE because if the same or similar vehicles are traveling the same or similar routes, then roughly the same results may be assumed to occur after the vehicle travels. Using this information could assist in generating accurate information regarding consumption or creation of energy during the vehicle’s route.
For Claim 7, Son teaches The computer system according to claim 6, where the processing circuitry is configured to predict the SoE of the ESS at the onset of the downhill portion for each candidate route. ([0061] A driving load F.sub.load of the vehicle in each of sections of each of a plurality of paths may be calculated through the driving environment information (e.g., F.sub.load=ma+F.sub.aero+F.sub.R.R+mg sin θ) (Operation S820), output/brake energies in each section may be calculated based on the driving load F.sub.load (Operation S830), and consumption/regeneration energies in each section may be calculated based on the output/brake energies (Operation S840). A SOC in each section may be calculated in consideration of the consumption/regeneration energies in each section, a fuel/battery consumption ratio according to the driving load, and maximum/minimum SOCs (Operation S850). Operations S820 to S850 were described above in detail with reference to FIGS. 5A-7B, and a redundant description thereof will thus be omitted because it is considered to be unnecessary.)
Son does not teach that the SoE is based at least in part on the prerecorded SoE profile data.
Dalum, however, does teach that determining SoE is based at least in part on the prerecorded SoE profile data. ([0059] Referring to FIGS. 4-5, a method estimates vehicle energy usage for job sites 54 and transit along an optimized route 56 to and from job sites 54. The location of job sites 54 and an optimized route 56 to and from job sites 54 is first determined (step 60). The available data for the expected job sites 54 is analyzed (step 62). If historical data is available for the job sites (e.g., historical data stored in internal database 16 and/or external database 18), it is used to estimate the total expected job site energy usage. If no historical data is available, the total expected job site usage is estimated using available data, such as the type and expected duration of job(s) (step 63). The available data for the expected route 56 is analyzed (step 64). If historical data is available for the route (e.g., historical data stored in internal database 16 and/or external database 18) it is used to estimate the total expected transit energy usage. If no historical data is available, the total expected transit usage is estimated using available data, such as route length, vehicle weight, road types, traffic patterns, etc (step 65). The total expected job site energy usage is then compared to the energy storage capabilities of vehicle 10 (e.g., the capacity and current charge levels of first rechargeable energy source 34) (step 66). The energy storage capabilities of vehicle 10 may be adjusted to account for expected gains while vehicle 10 is operating in a charge accumulate mode when in transit along route 56 to job sites 54.
[0078] Referring still to FIG. 1, control system 14 may monitor the operation of system 12 along a route 56 and collect data to better estimate the expected power usage of system 12 along route 56 and at job sites 54. For example, control system 14 may monitor a wide variety of parameters, such as total vehicle travel distance; fuel economy, brake use; cruise control use; accelerator pedal position; torque, rotational speed, temperatures, and operational times of various devices in hybrid vehicle drive system 12; first rechargeable energy source 34 voltage; and activity of on-board devices such as air conditioner activity, ePTO activity; heater activity, charger activity, etc. The recorded parameters may be utilized to refine initial estimates and create a historical database to provide more accurate estimates for subsequent trips. The recorded parameters may be stored in an internal database 16 or may be transferred to an external database 18 (e.g., via a fleet control system 17). The recorded parameters may be transferred by modem 19 to an external database 18 when vehicle 10 with a wired connection has returned to a home location or with a wireless connection. For example, control system 14 may transmit data on vehicle performance to fleet control system 17 using wireless interface, such as cellular, satellite or wireless area network. External data may also be transmitted using a wired interface through a charge station at a home location. A charge station provides external power from the grid 42 to vehicle 10 in order to recharge first rechargeable energy source 34. Such a signal may be sent through a low voltage communications wire (conductor) or through a digital interface connected to the high voltage conductor. In one exemplary embodiment, control system 14 may communicate wirelessly with a smart phone via a wireless technology such as a Bluetooth connection or a Wi-Fi connection. The smart phone may be loaded with software to store and/or analyze the data or the smart phone may be utilized to transfer the data wirelessly to external database 18. By uploading the data to an external database 18, fleet control system 17 may receive and analyze the collected data from many vehicles and refine power usage estimates and optimized routes in real time.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Dalum such that the SoE at the onset of the downhill slope is based on historic data because historic data could provide useful insights or guidance on how much energy the vehicle uses and creates as it travels along segments. This could provide more accurate information that would be useful so that the vehicle does not overcharge or run out of charge.
For Claim 15, Son teaches The computer system according to claim 1,
Son does not teach where the processing circuitry is configured to record an SoE profile along the trip as function of location of the heavy-duty vehicle.
Dalum, however, does teach where the processing circuitry is configured to record an SoE profile along the trip as function of location of the heavy-duty vehicle. ([0059] Referring to FIGS. 4-5, a method estimates vehicle energy usage for job sites 54 and transit along an optimized route 56 to and from job sites 54. The location of job sites 54 and an optimized route 56 to and from job sites 54 is first determined (step 60). The available data for the expected job sites 54 is analyzed (step 62). If historical data is available for the job sites (e.g., historical data stored in internal database 16 and/or external database 18), it is used to estimate the total expected job site energy usage. If no historical data is available, the total expected job site usage is estimated using available data, such as the type and expected duration of job(s) (step 63). The available data for the expected route 56 is analyzed (step 64). If historical data is available for the route (e.g., historical data stored in internal database 16 and/or external database 18) it is used to estimate the total expected transit energy usage. If no historical data is available, the total expected transit usage is estimated using available data, such as route length, vehicle weight, road types, traffic patterns, etc (step 65). The total expected job site energy usage is then compared to the energy storage capabilities of vehicle 10 (e.g., the capacity and current charge levels of first rechargeable energy source 34) (step 66). The energy storage capabilities of vehicle 10 may be adjusted to account for expected gains while vehicle 10 is operating in a charge accumulate mode when in transit along route 56 to job sites 54.
[0078] Referring still to FIG. 1, control system 14 may monitor the operation of system 12 along a route 56 and collect data to better estimate the expected power usage of system 12 along route 56 and at job sites 54. For example, control system 14 may monitor a wide variety of parameters, such as total vehicle travel distance; fuel economy, brake use; cruise control use; accelerator pedal position; torque, rotational speed, temperatures, and operational times of various devices in hybrid vehicle drive system 12; first rechargeable energy source 34 voltage; and activity of on-board devices such as air conditioner activity, ePTO activity; heater activity, charger activity, etc. The recorded parameters may be utilized to refine initial estimates and create a historical database to provide more accurate estimates for subsequent trips. The recorded parameters may be stored in an internal database 16 or may be transferred to an external database 18 (e.g., via a fleet control system 17). The recorded parameters may be transferred by modem 19 to an external database 18 when vehicle 10 with a wired connection has returned to a home location or with a wireless connection. For example, control system 14 may transmit data on vehicle performance to fleet control system 17 using wireless interface, such as cellular, satellite or wireless area network. External data may also be transmitted using a wired interface through a charge station at a home location. A charge station provides external power from the grid 42 to vehicle 10 in order to recharge first rechargeable energy source 34. Such a signal may be sent through a low voltage communications wire (conductor) or through a digital interface connected to the high voltage conductor. In one exemplary embodiment, control system 14 may communicate wirelessly with a smart phone via a wireless technology such as a Bluetooth connection or a Wi-Fi connection. The smart phone may be loaded with software to store and/or analyze the data or the smart phone may be utilized to transfer the data wirelessly to external database 18. By uploading the data to an external database 18, fleet control system 17 may receive and analyze the collected data from many vehicles and refine power usage estimates and optimized routes in real time.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Dalum so that profile data is gathered along the trip as a function of location, as it would allow that data to be used in the future for more accurate planning. Historic data may be more accurate than estimated data or other maps, and could improve predictions of energy usage.
For Claim 16, Son teaches The computer system according to claim 15,
Son does not teach where the processing circuitry is configured to transmit the recorded SoE profile along the trip to on-board data storage and/or to a remote server.
Dalum, however, does teach where the processing circuitry is configured to transmit the recorded SoE profile along the trip to on-board data storage and/or to a remote server. ([0059] Referring to FIGS. 4-5, a method estimates vehicle energy usage for job sites 54 and transit along an optimized route 56 to and from job sites 54. The location of job sites 54 and an optimized route 56 to and from job sites 54 is first determined (step 60). The available data for the expected job sites 54 is analyzed (step 62). If historical data is available for the job sites (e.g., historical data stored in internal database 16 and/or external database 18), it is used to estimate the total expected job site energy usage. If no historical data is available, the total expected job site usage is estimated using available data, such as the type and expected duration of job(s) (step 63). The available data for the expected route 56 is analyzed (step 64). If historical data is available for the route (e.g., historical data stored in internal database 16 and/or external database 18) it is used to estimate the total expected transit energy usage. If no historical data is available, the total expected transit usage is estimated using available data, such as route length, vehicle weight, road types, traffic patterns, etc (step 65). The total expected job site energy usage is then compared to the energy storage capabilities of vehicle 10 (e.g., the capacity and current charge levels of first rechargeable energy source 34) (step 66). The energy storage capabilities of vehicle 10 may be adjusted to account for expected gains while vehicle 10 is operating in a charge accumulate mode when in transit along route 56 to job sites 54.
[0078] Referring still to FIG. 1, control system 14 may monitor the operation of system 12 along a route 56 and collect data to better estimate the expected power usage of system 12 along route 56 and at job sites 54. For example, control system 14 may monitor a wide variety of parameters, such as total vehicle travel distance; fuel economy, brake use; cruise control use; accelerator pedal position; torque, rotational speed, temperatures, and operational times of various devices in hybrid vehicle drive system 12; first rechargeable energy source 34 voltage; and activity of on-board devices such as air conditioner activity, ePTO activity; heater activity, charger activity, etc. The recorded parameters may be utilized to refine initial estimates and create a historical database to provide more accurate estimates for subsequent trips. The recorded parameters may be stored in an internal database 16 or may be transferred to an external database 18 (e.g., via a fleet control system 17). The recorded parameters may be transferred by modem 19 to an external database 18 when vehicle 10 with a wired connection has returned to a home location or with a wireless connection. For example, control system 14 may transmit data on vehicle performance to fleet control system 17 using wireless interface, such as cellular, satellite or wireless area network. External data may also be transmitted using a wired interface through a charge station at a home location. A charge station provides external power from the grid 42 to vehicle 10 in order to recharge first rechargeable energy source 34. Such a signal may be sent through a low voltage communications wire (conductor) or through a digital interface connected to the high voltage conductor. In one exemplary embodiment, control system 14 may communicate wirelessly with a smart phone via a wireless technology such as a Bluetooth connection or a Wi-Fi connection. The smart phone may be loaded with software to store and/or analyze the data or the smart phone may be utilized to transfer the data wirelessly to external database 18. By uploading the data to an external database 18, fleet control system 17 may receive and analyze the collected data from many vehicles and refine power usage estimates and optimized routes in real time.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Dalum so that profile data is gathered along the trip as a function of location, and sent to a remote server as it would allow the system to use that data in the future, or share that data with other users who are traveling on the same routes or using similar vehicles. This would allow the use of historic data which would be expected to be useful.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Son in light of Lane in light of Ogaki et al (US Pub 2018/0281618 A1), hereafter known as Ogaki.
For Claim 9, Son teaches The computer system according to claim 8,
Son does not teach where the processing circuitry is configured to determine a current energy storage capacity of the ESS based at least in part on ambient temperature.
Ogaki, however, does teach where the processing circuitry is configured to determine a current energy storage capacity of the ESS based at least in part on ambient temperature. (Figure 3.
[0071] The effective capacity change estimation unit 165 estimates an effective capacity West of the storage battery 103 when the heater 115 generates heat through current flowing due to power supplied from an external power supply and heats the storage battery 103 to a target temperature. When estimating the effective capacity West, the effective capacity change estimation unit 165 also uses the map based on the graph indicating an effective capacity corresponding to the temperature and SOC of the storage battery 103 in FIG. 3. At this time, the target temperature is used as the temperature of the storage battery 103, and the SOC derived by the SOC derivation unit 159 is used as the SOC of the storage battery 103.
[0005] However, even when the storage battery is discharged at low temperature, a reduction in performance of the storage battery may occur in the same manner as the storage battery is charged. For example, although the state of charge (SOC) of the storage battery is high as illustrated in FIG. 14, the effective capacity of the storage battery may be reduced at temperatures below zero. Therefore, when the ambient temperature of the storage battery is low, the storage battery may be preferably heated before discharging is performed.
[0070] The SOC derivation unit 159 derives a SOC of the storage battery 103 from the open circuit voltage OCV calculated by the open circuit voltage calculation unit 157, using a map. The temperature acquisition unit 161 acquires a temperature Tbat of the storage battery 103, detected by the temperature sensor 111. The effective capacity derivation unit 163 derives the current effective capacity Wcur of the storage battery 103, according to the SOC of the storage battery 103, derived by the SOC derivation unit 159, and the temperature Tbat of the storage battery 103, acquired by the temperature acquisition unit 161. In order to derive the effective capacity Wcur, the effective capacity derivation unit 163 uses a map based on a graph indicating an effective capacity corresponding to the temperature and SOC of the storage battery 103 in FIG. 3.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Ogaki so that the storage capacity of the battery is determined based off of ambient temperature because it is known that the storage capacity of the battery is dependent upon the temperature, and considering this would allow more accurate estimates of the state of energy of the battery. It would allow the system to appropriately estimate the range of the vehicle, as well as understand how quickly energy is discharged or generated.
Claim 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Son in light of Lane in light of Semsey et al (US Pub 2016/0082843 A1), hereafter known as Semsey.
For Claim 10, Son teaches The computer system according to claim 1,
Son does not teach where the heavy-duty vehicle comprises an energy dissipation device, where the processing circuitry is configured to select the proposed route out of the candidate routes at least in part based on an energy dissipating capacity of the energy dissipation device.
Semsey, however, where the heavy-duty vehicle comprises an energy dissipation device, where the processing circuitry is configured to make control decisions based on an energy dissipating capacity of the energy dissipation device. ([0033] One embodiment of the invention provides that after the diversion of the regenerative power (i.e. after the regenerative power is no longer conducted exclusively to the electrical storage device) the regenerative power is partially or completely conducted to the power resistor. The addition of the power resistor results in a further power sink which is in addition to or instead of the storage device. There is provision that the setpoint braking power value is reduced compared to the prespecified braking power value over a prespecified time period. In this context, the reduction is carried out in accordance with a prespecified time profile, for example in accordance with a constant reduction rate or in accordance with some other prespecified time profile. The prespecified time period prespecifies the time interval in which the power resistor has taken up the regenerative power. At the same time, the prespecified time period or the reduction or the reduction rate corresponds to a deviation, which can be compensated by the driver, of the setpoint braking power value from the prespecified braking power value. The time period is preferably less than a time period which would lead to overheating of the power resistor in the case of braking from a high speed (for example 100 km/h or 150 km/h). The time period can therefore depend on the thermal capacity of the power resistor, on a rated value of the setpoint braking power value or on the heat dissipation capacity of the power resistor if it dissipates heat. In addition, the time period therefore also depends on a rated operating temperature and on a maximum operating temperature. In this respect, the time period is, for example, below 2 minutes, 1 minute or 30 seconds. The maximum recall rate of the reduction is, for example, shorter than 50%, 20% or 10% of a rated value of the braking power of the regenerative braking device or of the prespecified braking power value with respect to 10, 20 or 30 seconds. This reduction rate permits, despite a reduction in the braking power, safe operator control of the vehicle such that the vehicle can adjust to the slow reduction. The power resistor is preferably configured thermally in such a way that, starting from a rated temperature (for example 20° C.), the temperature of said power resistor does not increase beyond a maximum temperature of the regenerative braking device during braking with a rated braking power of the regenerative braking device. This thermal configuration relates, in particular, to the thermal absorption capacity and/or to the thermal output power of the power resistor.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Semsey such that where the heavy-duty vehicle comprises an energy dissipation device, where the processing circuitry is configured to select the proposed route out of the candidate routes at least in part based on an energy dissipating capacity of the energy dissipation device.
It would be obvious to one of ordinary skill in the art to modify Son in this way in light of Semsey because Semsey teaches that there are time limits that a resistor can be used before it begins to operate ineffectively. By making sure that the routes chosen do not cause the resistor to be over used in a case in which the battery is overcharged, an unsafe operation of the vehicle can be prevented.
For Claim 11, Son teaches The computer system according to claim 10,
Son does not teach where the processing circuitry is configured to determine a current energy dissipating capacity of the energy dissipation device based at least in part on a current temperature of the energy dissipation device.
Semsey, however, does teach where the processing circuitry is configured to determine a current energy dissipating capacity of the energy dissipation device based at least in part on a current temperature of the energy dissipation device. ([0033] One embodiment of the invention provides that after the diversion of the regenerative power (i.e. after the regenerative power is no longer conducted exclusively to the electrical storage device) the regenerative power is partially or completely conducted to the power resistor. The addition of the power resistor results in a further power sink which is in addition to or instead of the storage device. There is provision that the setpoint braking power value is reduced compared to the prespecified braking power value over a prespecified time period. In this context, the reduction is carried out in accordance with a prespecified time profile, for example in accordance with a constant reduction rate or in accordance with some other prespecified time profile. The prespecified time period prespecifies the time interval in which the power resistor has taken up the regenerative power. At the same time, the prespecified time period or the reduction or the reduction rate corresponds to a deviation, which can be compensated by the driver, of the setpoint braking power value from the prespecified braking power value. The time period is preferably less than a time period which would lead to overheating of the power resistor in the case of braking from a high speed (for example 100 km/h or 150 km/h). The time period can therefore depend on the thermal capacity of the power resistor, on a rated value of the setpoint braking power value or on the heat dissipation capacity of the power resistor if it dissipates heat. In addition, the time period therefore also depends on a rated operating temperature and on a maximum operating temperature. In this respect, the time period is, for example, below 2 minutes, 1 minute or 30 seconds. The maximum recall rate of the reduction is, for example, shorter than 50%, 20% or 10% of a rated value of the braking power of the regenerative braking device or of the prespecified braking power value with respect to 10, 20 or 30 seconds. This reduction rate permits, despite a reduction in the braking power, safe operator control of the vehicle such that the vehicle can adjust to the slow reduction. The power resistor is preferably configured thermally in such a way that, starting from a rated temperature (for example 20° C.), the temperature of said power resistor does not increase beyond a maximum temperature of the regenerative braking device during braking with a rated braking power of the regenerative braking device. This thermal configuration relates, in particular, to the thermal absorption capacity and/or to the thermal output power of the power resistor.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Semsey such that the capacity is based on temperature, because it is known that the starting temperature of the resistive brakes will ultimately determine how much energy can be stored in them before they become unusuable or dangerous. By considering the ambient temperature, the starting temperature of the brakes can be considered, which would provide more accurate capacity predictions.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Son in light of Lane in light of Geis-Esser et al (US Pub 2022/0355796 A1), hereafter known as Geis-Esser.
For Claim 12, Son teaches The computer system according to claim 1,
Son does not teach where the processing circuitry is configured to select the proposed route out of the candidate routes at least in part based on endurance braking capacity and/or a cooling capacity of a service brake system of the heavy-duty vehicle.
Geis-Esser, does teach, however, that when planning how to carry out a route, doing so to consider the effectiveness or ability of a service brake to brake a load. ([0003] For commercial vehicles driven by means of electric driving machines, in particular the following options are available for implementing a permanent braking function: employment of a retarder, supply of a recuperation power of the driving machine to an electric energy storage, conversion of power generated generatively by the driving machine into heat by means of a braking resistor. The braking resistor and retarder are additional components requiring installation space in the vehicle and increasing the production costs of the vehicle. On the other hand, these technical solutions have an almost constant availability during the operation of the vehicle. The supply of recuperation power to the electric energy storage is the preferred method, since no further components are required to implement the function of the permanent brake. However, here, the availability depends on the absorbable amount of energy of the energy storage. If it cannot absorb any further energy by recuperation, also the function of the permanent brake can no longer be realized in such manner. Here, in particular the length of the driving route as well as its slope and the vehicle speed have an effect. If the energy storage is no longer capable of absorbing energy, either a change to a secondary system (e.g. braking resistor or retarder) has to be made, or the service brake has to be used, in which case driving has to be carried out particularly at reduced speed, as the service brake is not designed for such a load, which may cause damage to the service brake.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Geis-Esser such that where the processing circuitry is configured to select the proposed route out of the candidate routes at least in part based on endurance braking capacity and/or a cooling capacity of a service brake system of the heavy-duty vehicle.
It would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in this way because if the service brake must be used during a certain portion of a trip, understanding its capabilities and capacities would prevent overuse which could cause damage or unsafe operation of the vehicle.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Son in light of Lane in light of Fujitake et al (US Pub 11,535,119 B2) hereafter known as Fujitake.
For Claim 13, Son teaches The computer system according to claim 1,
Son does not teach where the processing circuitry is configured to propose an ESS discharge stop along the route prior to the downhill portion in case none of the candidate routes satisfies an SoE acceptance criteria at the onset of the downhill portion.
Fujitake, however, does teach that when the vehicle is likely to exceed the upper charge limit in the future, perform a discharge. (Page 13, Column 3 Line 53 to Column 4 Line 8
(22) For example, when a request to stop the system is made in one's home, company, or the like, a vehicle is expected to stop for a long period of time after the stop of the system. Contrastingly, when a request to stop the system is made in, for example, a parking lot of a convenience store, the system is expected to be activated again for a short period of time after the stop of the system. The electrically powered vehicle can thus set, as a prescribed location, a location in which the discharge process is performed when a request to stop the system is made with the SOC exceeding the upper control limit (e.g., one' home, company, or the like in which the vehicle is expected to stop for a long period of time), and does not perform the discharge process when the current position is not the prescribed location, assuming that the system is highly likely to be activated again in a short period of time after the stop of the system. This allows, while reducing accelerated degradation of the power storage device which is caused by the power storage device being left for a long period of time in the high SOC state, the power stored in the power storage device to be effectively used after activation of the system when a request to activate the system is made in a short period of time after the stop of the system.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Sons in light of Fujitake such that where the processing circuitry is configured to propose an ESS discharge stop along the route prior to the downhill portion in case none of the candidate routes satisfies an SoE acceptance criteria at the onset of the downhill portion.
It would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in this way because if there are predicted situations ahead in which the battery is going to be overcharged, then discharging the battery could prevent damage to the battery or other braking systems. By performing a discharge stop, the vehicle can ensure that its battery is ready to be recharged on the downhill portion, thus providing a safe outlet for the braking energy.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Son in light of Lane in light of Szubbecsev et al (US Pub 2019/0294173 A1), hereafter known as Szubbecsev.
For Claim 14, Son teaches The computer system according to claim 1,
Son does not teach where the starting location is a current location of the heavy-duty vehicle.
Szubbocsev, however, does teach where the starting location is a current location of the heavy-duty vehicle. ([0009] One or more embodiments of an ADV are configured as an electric vehicle. One or more embodiments of an ADV are configured as a hybrid electric vehicle. One or more embodiments of an ADV include an on-board computer comprising one or more processors programmed to autonomously navigate the vehicle along a current route to a predetermined geographical destination. One or more embodiments of an ADV include a battery device configured to provide electrical power to an autonomous driving vehicle. One or more embodiments of an ADV include one or more sensor devices communicatively coupled to the on-board computer. One or more embodiments of an ADV include one or more sensor devices that are configured to generate battery data including a state of charge of the battery device. One or more embodiments of an ADV are configured to determine a starting geographical location of the vehicle. One or more embodiments of an ADV are configured to generate mapping information for a geographical area that includes the starting location of the vehicle, the destination, one or more navigable pathways between the starting vehicle location and the destination and information concerning the one or more pathways. One or more embodiments of an ADV are configured to generate, utilizing the mapping information, the current route from the starting location of the vehicle to the destination that includes one or more of the navigable pathways. One or more embodiments of an ADV are configured to determine a current route time that represents a time that it will take to navigate the vehicle along the current route from the starting location to reach the destination. One or more embodiments of an ADV are configured to receive the state of charge of the battery device from the at least one sensor device. One or more embodiments of an ADV are configured to determine an estimated total amount of electrical power required to navigate the vehicle along the current route to reach the destination. One or more embodiments of an ADV are configured to determine, utilizing the state of charge of the battery device and the total amount of electrical power, if the on-board computer can navigate the vehicle along the current route from the starting location to the destination without having to charge the battery device utilizing an external power source. One or more embodiments of an ADV are configured to, in response to determining that the on-board computer can navigate the vehicle along the current route to reach the destination without having to charge the battery device utilizing the external power source, autonomously navigate the vehicle from the starting location to the destination along the current route. One or more embodiments of an ADV include a data storage device communicatively coupled to the one or more processors for retrievably storing data. One or more embodiments of an ADV include an in-memory processing system that includes the at least one of the one or more processors to perform in-memory processing of data received from one or more devices included in the system.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify Son in light of Szubbocsev such that the starting location is the current position because it would allow the system to be used while the vehicle is at a particular spot and wants to move to a new location immediately. By allowing the starting location to be the current position, the routes do not need to be planned in advance or only between particular depots or locations.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Dufford et al (US Pub 9,695,760 B2) relates to energy efficiency on routes.
Murphy et al (US Pub 2021/0178907 A1) relates to resistor braking methods.
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/T.J.G./Examiner, Art Unit 3656
/KHOI H TRAN/Supervisory Patent Examiner, Art Unit 3656