DETAILED ACTION
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 .
Status of Claims
This Office Action is in response to the application filed on 29 April 2026. Claims 1-15 are presently pending and are presented for examination.
Response to Amendment
In response to Applicant’s amendments dated 29 April 2026, Examiner withdraws the previous claim objections; withdraws the previous specification objections; withdraws the previous objections to the drawings; withdraws the previous 35 U.S.C. 112(b) rejections; and maintains the previous prior art rejections.
Response to Arguments
Applicant's arguments, see Remarks, filed 29 April 2026, have been fully considered but they are not persuasive.
Applicant argues, see Remarks, pg. 1-3, that US-20180334012-A1 (“Geller”) “merely describes ‘an optimal setting’ at which the engine may perform most efficiently” and does not teach “determine a plurality of operating points of at least one mobility component of the plurality of mobility components of the EV, based on the driving cycle data.” Examiner respectfully disagrees. Regarding the “optimal setting,” Geller teaches “operating points of at least one mobility component” that are “parameterized by a desired torque and speed of the EV” (see Geller, para. 0034). Geller also teaches determining “a plurality of operating points of at least one mobility component…based on the driving cycle data.” Geller teaches a system, a method, and a non-transitory computer readable medium with instructions for an electrified vehicle (EV) that generates driving cycle data of the EV based on physical state data of the EV and then uses that driving cycle data to determine a plurality of operating points of at least one mobility component of the EV. For example, Geller teaches generating driving cycle data, represented by the EV’s location data and previous power demand data, using that data to predict an upcoming acceleration, and commanding the operation of at least one mobility component to achieve the predicted and actual power demand for that upcoming acceleration [i.e., determining operating points of at least one mobility component] (see Geller, para. 0059). In another example, Geller teaches generating driving cycle data, represented by data about the terrain the EV is traveling on, like an upcoming hill, using that data to predict an upcoming acceleration, and commanding the operation of at least one mobility component to achieve the predicted and actual power demand for that upcoming uphill acceleration [i.e., determining operating points of at least one mobility component] (see Geller, para. 0059). While Geller’s invention can optimize operating points of at least one mobility component with the concept of the “optimal setting“ (see Geller, para. 0034), it is not limited to only that optimization. Geller’s invention is also capable of determining a plurality of operating points, based on driving cycle data. For these reasons, examiner is unpersuaded and maintains the corresponding rejections.
The remaining arguments are essentially the same as those addressed above and/or below and are unpersuasive for at least the same reasons. Therefore, examiner is unpersuaded and maintains the corresponding rejections.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-3, 8-10, and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over US-20210268867-A1, hereinafter “Salter” (previously of record), in view of US-20180334012-A1, hereinafter “Geller” (previously of record).
Regarding claim 1, and analogous claims 8 and 15, Salter discloses A controller for controlling an electric vehicle (EV) (Salter, para. 0035: “The vehicle 10 may include one or more propulsion devices 14 for propelling the vehicle 10. Each propulsion device 14 may be employed as an available drive source for the vehicle 10…the propulsion device 14 is an electric machine (i.e., an electric motor, a generator, or a combined motor/generator) when the vehicle 10 is configured as a BEV [i.e., an electric vehicle (EV)].”; para. 0052: “Although schematically illustrated as a single controller in FIG. 2, the control module 44 may be part of an overall vehicle control system, such as a vehicle system controller (VSC) [i.e., A controller for controlling an electric vehicle (EV)], that includes a plurality of additional control modules for interfacing with and commanding operation of the various components of the vehicle 10…”).
Regarding analogous claims 8 and 15, Salter discloses a computer-implemented method for controlling an electric vehicle (EV) (Salter, para. 0071: “The method 100 may be stored as executable instructions in the memory 50 of the control module 44, and the executable instructions may be embodied within any computer readable medium that can be executed by the processing unit 48 of the control module 44 [i.e., computer-implemented method].”; para. 0016: “A method according to another exemplary aspect of the present disclosure includes, among other things, automatically activating, via a control module located onboard a vehicle [i.e., controlling an electric vehicle], an economical (ECO) mode of a climate control system of the vehicle.”; para. 0034: “The teachings of this disclosure are applicable to any type of vehicle. For example, the vehicle 10 could be a conventional motor vehicle that is powered by an internal combustion engine, a battery electric vehicle (BEV) that is powered by a battery powered electric machine [i.e., an electric vehicle], a hybrid (HEV) or plug-in hybrid (PHEV) vehicle that is powered by one or more electric machines…”) and a non-transitory computer readable medium having stored thereon instructions that when executed by a computer, cause the computer to perform a method for controlling an electric vehicle (EV) (Salter, para. 0053: “The control module 44 may include a processing unit 48 and non-transitory memory 50 for executing the various control strategies and modes of the climate control system 12…”).
Furthermore, Salter discloses a memory configured to store computer-executable instructions and a set of models corresponding to a plurality of functional components of the EV, a plurality of mobility components of the EV, and a plurality of thermal components of the EV (Salter, para. 0052: “Although schematically illustrated as a single controller in FIG. 2, the control module 44 may be part of an overall vehicle control system, such as a vehicle system controller (VSC), that includes a plurality of additional control modules for interfacing with and commanding operation of the various components of the vehicle 10 [i.e., a set of models corresponding to…a plurality of mobility components of the EV,]…”; para. 0053: “The control module 44 may include a processing unit 48 and non-transitory memory 50 for executing the various control strategies [i.e., a memory configured to store computer-executable instructions] and modes of the climate control system 12, including but not limited to the ability to automatically modify the temperature set point of the HVAC system 24 [i.e., a set of models corresponding to a plurality of functional components of the EV,]…The control module 44 may additionally include a pulse width modulation (PWM) circuit 52 for controlling the flow of power from a power supply to the heating/cooling element 38 of the seat 20 [i.e., a set of models corresponding to…a plurality of thermal components of the EV].”); and
a processor configured to execute the computer-executable instructions (Salter, para. 0053: “The control module 44 may include a processing unit 48 and non-transitory memory 50 for executing the various control strategies and modes…”) to:
collect physical state data of the EV and a driver command input corresponding to a functional component of the plurality of functional components of the EV (Salter, para. 0049: “The HVAC system 24 may be configured as discussed above for directing a conditioned air 46 (i.e., heated or cooled air) into the passenger cabin 18. A vehicle occupant may select a desired temperature set point of the HVAC system 24 using the HMI 22 [i.e., collect...a driver command input corresponding to a functional component of the plurality of functional components of the EV]. The vehicle occupant may additionally turn the heating/cooling element 38 of the seat 20 ON/OFF, select either heating or cooling, etc. using the HMI 22 [i.e., collect...a driver command input corresponding to a functional component of the plurality of functional components of the EV].”; para. 0050: “The sensor system 40 may include one or more sensors that are configured to provide input signals to the control module 44. In an embodiment, the sensor system 40 includes a vehicle speed sensor configured to monitor a speed of the vehicle 10 [i.e., collect physical state data of the EV]. In another embodiment, the sensor system 40 includes an external temperature sensor configured to sense an ambient temperature of the environment surrounding the vehicle 10. In another embodiment, the sensor system 40 includes various sensors configured for monitoring a state of charge (SOC) of a high voltage traction battery pack or any other energy source of the vehicle 10 [i.e., collect physical state data of the EV]. In yet another embodiment, the sensor system 40 includes each of the vehicle speed sensor, the external temperature sensor, and the sensors for monitoring the battery SOC [i.e., collect physical state data of the EV].”; para. 0051: “The navigation system 42 may include a global positioning system (GPS) configured for communicating drive route information of the vehicle 10 to the control module 44 [i.e., collect physical state data of the EV]…The navigation system 42 is also capable of determining a distance the vehicle 10 will travel and a total travel time for reaching the desired location indicated by the pre-planned drive route.”);
generate driving cycle data for the EV, based on the physical state data (Salter, para. 0050: “The sensor system 40 may include one or more sensors that are configured to provide input signals to the control module 44. In an embodiment, the sensor system 40 includes a vehicle speed sensor configured to monitor a speed of the vehicle 10 [i.e., based on the physical state data].”; para. 0051: “The navigation system 42 may include a global positioning system (GPS) configured for communicating drive route information of the vehicle 10 to the control module 44 [i.e., based on the physical state data]…The navigation system 42 is also capable of determining a distance the vehicle 10 will travel and a total travel time for reaching the desired location [i.e., generate driving cycle data for the EV] indicated by the pre-planned drive route.”)…
Salter does not appear to explicitly disclose the following:
…determine a plurality of operating points of at least one mobility component of the plurality of mobility components of the EV, based on the driving cycle data, wherein each operating point of the plurality of operating points is parameterized by a desired torque and speed of the EV; generate a set of control commands for the functional component, based on the plurality of operating points, the set of models stored in the memory, and the driver command input; and control the functional component, based on the set of control commands.
However, in the same field of endeavor, Geller teaches:
determine a plurality of operating points of at least one mobility component of the plurality of mobility components of the EV, based on the driving cycle data, wherein each operating point of the plurality of operating points is parameterized by a desired torque and speed of the EV (Geller, para. 0051: “For example, the power source may include a combination of a battery and motor-generator [i.e., EV], an engine, a fuel cell [i.e., EV], or a hybrid [i.e., EV] including any combination of the above.”; para. 0033: “In order to control the vehicle 100 to perform in an efficient manner, the ECU 102 may make predictions regarding use of the vehicle in certain situations and may control one or more of the engine 112 [i.e., at least one mobility component of the plurality of mobility components of the EV], the battery 114 [i.e., plurality of mobility components of the EV], the motor-generator 116 [i.e., plurality of mobility components of the EV], and/or the transmission 118 based on the prediction.”; para. 0034: “The engine 112 may have an optimal setting at which it may perform most efficiently. For example, the optimal setting may include an optimal engine speed and an optimal torque. In that regard, when the ECU 102 predicts that the vehicle will accelerate to 65 mph [i.e., based on the driving cycle data], the ECU 102 may control the engine 112 to turn on and operate at the optimal engine speed and torque [i.e., wherein each operating point of the plurality of operating points is parameterized by a desired torque and speed] before the predicted acceleration begins.”; para. 0058: “In block 308, the ECU may predict that an acceleration of the vehicle will occur within the predetermined distance or the predetermined amount of time [i.e., determine a plurality of operating points of at least one mobility component of the plurality of mobility components of the EV, based on the driving cycle data].”; para. 0059: “In block 312, the ECU may determine or predict an amount of power that will be required for the predicted acceleration of the vehicle. This determination or prediction may be based on previously detected data and/or other information received by the ECU. For example, if previous accelerations at a certain location have required 5 Kilowatt-hours (kWh) of power then the ECU may predict that upcoming acceleration of will likewise require about 5 kWh of power [i.e., determine a plurality of operating points of at least one mobility component of the plurality of mobility components of the EV, based on the driving cycle data]. Similarly, the ECU may receive or retrieve information corresponding to the environment such as whether the vehicle is approaching a hill. For example, the ECU may predict an amount of power that will be required to accelerate the vehicle up an upcoming hill based on the length of the hill, the grade of the hill, or the like [i.e., determine a plurality of operating points of at least one mobility component of the plurality of mobility components of the EV, based on the driving cycle data].”);
generate a set of control commands for the functional component, based on the plurality of operating points, the set of models stored in the memory, and the driver command input (Geller, para. 0035: “At times, this may be desirable to reduce the power load on at least one of the engine 112 and/or the motor-generator 116. For example, if the battery 114 does not include enough electrical energy to allow the vehicle 100 to perform a requested acceleration without running the engine 112 above the optimal engine speed and torque [i.e., based on the plurality of operating points, the set of models stored in the memory], it may be desirable for total power consumption of the vehicle 100 to be reduced. In that regard, the ECU 102 may decrease an amount of power used by the HVAC system 128 [i.e., generate a set of control commands for the functional component] based on a predicted action of the vehicle 100 [i.e., based on…the driver command input].”); and
control the functional component, based on the set of control commands (Geller, para. 0035: “In that regard, the ECU 102 may decrease an amount of power used by the HVAC system 128 based on a predicted action of the vehicle 100.”).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Salter, with the concept of determining torque and speed operating points of a vehicle based on drive cycle data, generating control commands for a functional component of the vehicle based on the operating points, a set of models and driver command input and control the functional component based on the control commands, taught by Geller, in order to operate the vehicle efficiently by optimizing the usage of propulsion components by decreasing the load demand of other vehicle components (Geller, para. 0037: “Thus, by predicting accelerations and decelerations of the vehicle 100 and controlling the power consumed by the HVAC system 128 based on the prediction, the ECU 102 may further increase efficiency of the vehicle 100.”).
Regarding claim 2, and analogous claim 9, Salter and Geller teach The controller of claim 1, and Salter further discloses the following:
wherein the functional component comprise a Heating Ventilation and Air Conditioning (HVAC) subsystem of the EV (Salter, para. 0004: “A vehicle according to an exemplary aspect of the present disclosure includes, among other things, a climate control system including a heating, ventilation, and air conditioning (HVAC) system and a heated/cooled seat, and a control module configured to automatically activate an economical (ECO) mode of the climate control system during operation of the vehicle.”),
wherein the plurality of mobility components comprise one or more propulsion systems of the EV (Salter, para. 0035: “…the propulsion device 14 is an electric machine (i.e., an electric motor, a generator, or a combined motor/generator) [i.e., plurality of mobility components comprise one or more propulsion systems of the EV] when the vehicle 10 is configured as a BEV.”; para. 0036: “One or more energy sources 16 may supply power to the propulsion device(s) 14. The energy source 16 may include a fuel system when the propulsion device 14 is an engine or a high voltage traction battery pack [i.e., plurality of mobility components comprise one or more propulsion systems of the EV] when the propulsion device 14 is an electric machine.”), and
wherein the plurality of thermal components comprise heat sources in the EV (Salter, para. 0043: “The climate control system 12 may additionally include one or more heating/cooling elements 38 for warming/cooling the seats 20 [i.e., the plurality of thermal components comprise heat sources in the EV]. The seat 20 and the heating/cooling element 38 may be collectively referred to herein as a heated/cooled seat.”).
Regarding claim 3, and analogous claim 10, Salter and Geller teach The controller of claim 2, and Salter further discloses the following:
wherein the set of control commands define one or more temperature setpoints for a cabin of the EV, a cooling air temperature entering the cabin of the EV, one or more mass flow rates of coolant in the HVAC subsystem, and a temperature of the coolant when exiting a compressor of the HVAC subsystem (Salter, para. 0040: “The HVAC system 24 is equipped to raise or lower the temperature inside the passenger cabin 18. The HVAC system 24 may include a heating element 30, a cooling element 32, and a blower 34...Alternatively, when cooling is demanded within the passenger cabin 18, a refrigerant may be communicated to the cooling element 32. The refrigerant is expanded in the cooling element 32 and thus absorbs heat from the airflow that is blown across the cooling element 32 by the blower 34. The airflow may then be communicated as cooled air into the passenger cabin 18 [i.e., wherein the set of control commands define one or more…a cooling air temperature entering the cabin of the EV,].”; para. 0053: “The control module 44 may include a processing unit 48 and non-transitory memory 50 for executing the various control strategies and modes of the climate control system 12, including but not limited to the ability to automatically modify the temperature set point of the HVAC system 24 [i.e., wherein the set of control commands define one or more temperature setpoints for a cabin of the EV,] by an offset value in combination with activating the heating/cooling element 38 of the seat 20 when certain vehicle conditions exist in order to achieve a commanded occupant comfort level in an energy efficient manner.”).
Claim(s) 4-7 and 11-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Salter, in view of Geller, as applied to claims 2 and 9, above, and further in view of US-20180273018-A1, hereinafter “Follen” (previously of record).
Regarding claim 4, and analogous claim 11, Salter and Geller teach The controller of claim 2, and Salter further discloses the following:
wherein the physical state data comprises acceleration data of the EV, travelled distance data of the EV, location data of the EV, temperature data of the EV, battery status data of the EV (Salter, para. 0033: “For example, the decision to activate the ECO mode of the climate control system may be a function of one or more variables including, but not limited to, vehicle speed [i.e., physical state data comprises acceleration data of the EV; It is commonly known that acceleration is the second derivative of speed.], vehicle speed differentials, ambient temperatures [i.e., physical state data comprises…temperature data of the EV], temperature differentials [i.e., physical state data comprises…temperature data of the EV], battery state of charge [i.e., physical state data comprises…battery status data of the EV], predicted low battery state of charge, etc.”; para. 0051: “The navigation system 42 may include a global positioning system (GPS) configured for communicating drive route information of the vehicle 10 to the control module 44. Using satellite navigation, the GPS of the navigation system 42 can pinpoint a location of the vehicle 10 [i.e., physical state data comprises…location data of the EV] and correlate the position to a road database that is stored in a memory device of the navigation system…The navigation system 42 is also capable of determining a distance the vehicle 10 will travel [i.e., physical state data comprises…travelled distance data of the EV] and a total travel time for reaching the desired location indicated by the pre-planned drive route.”), and
Salter and Geller do not appear to explicitly teach the following:
wherein the physical state data comprises…pressure data of the HVAC subsystem.
However, in the same field of endeavor, Follen teaches:
wherein the physical state data comprises…pressure data of the HVAC subsystem (Follen, para. 0028: “The HVAC system 125 (also referred to herein as the HVAC unit) may be structured to control or manage a cabin temperature of the vehicle 100. The HVAC system 125 may include any component that may be included in an HVAC system for an on-road or off-road vehicle. In this regard, the HVAC system 125 may include, but is not limited to, piping/conduit for circulating coolant, a coolant reservoir, a cabin air filter, a condenser, an evaporator, various temperature, pressure, and fluid flow sensors [i.e., pressure data of the HVAC subsystem], a thermostat, a pump, a compressor, a valve such as an expansion valve, a blower fan, etc.”).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Salter, as modified by Geller, with the concept of an electric vehicle controller that collects pressure data of the vehicle’s HVAC system, taught by Follen, in order to increase the efficiency of the HVAC system by using data about the vehicle and the HVAC system, to better anticipate HVAC system loads (Follen, para. 0032: “Advantageously, the electrified HVAC system may enable the decoupling of engine speed and compressor speed to thereby lead to higher efficiency of the conventional and electric compressors. Further, engineers may select more “right sized” conventional and electric compressors due to better control of the conventional and electric compressor speed and cooling capacities. As a result, higher efficiency of the electrified HVAC system 125 may result than that of traditional, conventional HVAC systems.”).
Regarding claim 5, Salter, Geller, and Follen teach The controller of claim 4, and Geller further teaches the following:
wherein to generate the driving cycle data, the processor is configured to: derive route information for the EV, real-time traffic information for the EV, and a current location of the EV, based on the physical state data (Geller, para. 0052: “In block 304, various sensors of the vehicle [i.e., based on the physical state data] may detect data that is usable to predict an upcoming acceleration or deceleration of the vehicle [i.e., generate the driving cycle data]. For example, the sensors may include a GPS sensor [i.e., a current location of the EV] or an IMU sensor, a camera, a radar detector, a LIDAR detector [i.e., derive route information for the EV], or a network access device capable of receiving, data corresponding to traffic conditions [i.e., real-time traffic information for the EV].”);
generate a route-traffic specific profile of the EV, based on the route information, the real-time traffic information, and the current location of the EV (Geller, para. 0052: “In block 304, various sensors of the vehicle may detect data that is usable to predict an upcoming acceleration or deceleration of the vehicle [i.e., generate a route-traffic specific profile of the EV]. For example, the sensors may include a GPS sensor or an IMU sensor, a camera, a radar detector, a LIDAR detector, or a network access device capable of receiving, data corresponding to traffic conditions [i.e., based on the route information, the real-time traffic information, and the current location of the EV].”); and
generate a driver-route-traffic-specific driving cycle using the route-traffic specific profile of the EV and a dynamic model representing driver characteristics (Geller, para. 0053: “In block 306, the ECU may analyze the data detected in block 304 to predict whether the vehicle will accelerate or decelerate within a predetermined distance or a predetermined amount of time. The predetermined distance or the predetermined amount of time may correspond to a sufficient distance or amount of time [i.e., generate a…driving cycle] for the power source to be prepared to most efficiently handle the acceleration or deceleration.”; para. 0054: “The location data detected by the GPS or the IMU may be compared to a map and other stored data corresponding to previous actions by the driver. If the driver has previously accelerated at a certain location, the ECU may predict that the vehicle will accelerate in a similar manner when the vehicle reaches the certain location. [i.e., generate a driver-route-traffic-specific driving cycle using the route-traffic specific profile of the EV and a dynamic model representing driver characteristics]”, see also [0045], [0049], [0071]).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Salter, as modified by Geller and Follen, with the concept of generating vehicle drive cycle data that includes route information based on physical state data, generating a route-traffic specific profile and generating a driver-route-traffic-specific driving cycle using a route-traffic specific profile and a dynamic model of a driver, taught by Geller, in order to more accurately predict the loads that will be experienced by the vehicle and optimize the power required by vehicle systems, like the HVAC system, to improve vehicle efficiency (Geller, para. 0037: “Thus, by predicting accelerations and decelerations of the vehicle 100 and controlling the power consumed by the HVAC system 128 based on the prediction, the ECU 102 may further increase efficiency of the vehicle 100.”).
Regarding claim 12, Salter, Geller, and Follen teach The method of claim 11, and Geller further teaches the following:
wherein generating the driving cycle data further comprises: deriving route information for the EV, real-time traffic information for the EV, and a current location of the EV, based on the physical state data (Geller, para. 0052: “In block 304, various sensors of the vehicle [i.e., based on the physical state data] may detect data that is usable to predict an upcoming acceleration or deceleration of the vehicle [i.e., generating the driving cycle data]. For example, the sensors may include a GPS sensor [i.e., a current location of the EV] or an IMU sensor, a camera, a radar detector, a LIDAR detector [i.e., deriving route information for the EV], or a network access device capable of receiving, data corresponding to traffic conditions [i.e., real-time traffic information for the EV].”);
generating a route-traffic specific profile of the EV, based on the route information, the real-time traffic information, and the current location of the EV (Geller, para. 0052: “In block 304, various sensors of the vehicle may detect data that is usable to predict an upcoming acceleration or deceleration of the vehicle [i.e., generating a route-traffic specific profile of the EV]. For example, the sensors may include a GPS sensor or an IMU sensor, a camera, a radar detector, a LIDAR detector, or a network access device capable of receiving, data corresponding to traffic conditions [i.e., based on the route information, the real-time traffic information, and the current location of the EV].”); and
generating a driver-route-traffic-specific driving cycle using the route-traffic specific profile of the EV (Geller, para. 0053: “In block 306, the ECU may analyze the data detected in block 304 to predict whether the vehicle will accelerate or decelerate within a predetermined distance or a predetermined amount of time. The predetermined distance or the predetermined amount of time may correspond to a sufficient distance or amount of time [i.e., generating a…driving cycle] for the power source to be prepared to most efficiently handle the acceleration or deceleration.”; para. 0054: “The location data detected by the GPS or the IMU may be compared to a map and other stored data corresponding to previous actions by the driver. If the driver has previously accelerated at a certain location, the ECU may predict that the vehicle will accelerate in a similar manner when the vehicle reaches the certain location. [i.e., generating a driver-route-traffic-specific driving cycle using the route-traffic specific profile of the EV]”).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Salter, as modified by Geller and Follen, with the concept of generating vehicle drive cycle data that includes route information based on physical state data, generating a route-traffic specific profile and generating a driver-route-traffic-specific driving cycle, taught by Geller, in order to more accurately predict the loads that will be experienced by the vehicle and optimize the power required by vehicle systems, like the HVAC system, to improve vehicle efficiency (Geller, para. 0037: “Thus, by predicting accelerations and decelerations of the vehicle 100 and controlling the power consumed by the HVAC system 128 based on the prediction, the ECU 102 may further increase efficiency of the vehicle 100.”).
Regarding claim 6, and analogous claim 13, Salter, Geller, and Follen teach The controller of claim 5, and Geller further teaches the following:
wherein to determine the plurality of operating points of the at least one mobility component, the processor is configured to: obtain a body model of the EV (Geller, para. 0005: “The system further includes an electronic control unit (ECU) coupled to the power source, the sensor, and the HVAC system. The ECU is designed to predict that the vehicle will accelerate or decelerate within a predetermined distance or a predetermined amount of time [i.e., determining the plurality of operating points of the at least one mobility component further comprises: obtaining a body model of the EV] based on the data detected by the sensor.”; para. 0006: “The system includes a power source configured to generate power to propel the vehicle. The system also includes a sensor configured to detect data that is usable to predict an upcoming acceleration or deceleration of the vehicle… The ECU is designed to predict that the vehicle will accelerate or decelerate within a predetermined distance or a predetermined amount of time based on the data detected by the sensor and to decrease the power that is provided to the HVAC system when the ECU predicts that the vehicle will accelerate within the predetermined distance or the predetermined amount of time in order to increase efficiency of the power source.”); and
determine the plurality of operating points as mobility commands for the at least one mobility component, based on the body model of the EV and the driver-route-traffic-specific driving cycle (Geller, para. 0034: “The engine 112 may have an optimal setting at which it may perform most efficiently. For example, the optimal setting may include an optimal engine speed and an optimal torque [i.e., determining the plurality of operating points as mobility commands for the at least one mobility component]. In that regard, when the ECU 102 predicts that the vehicle will accelerate to 65 mph [i.e., based on the body model of the EV and the driver-route-traffic-specific driving cycle], the ECU 102 may control the engine 112 to turn on and operate at the optimal engine speed and torque [i.e., plurality of operating points as mobility commands for the at least one mobility component] before the predicted acceleration begins.”; para. 0035: “At times, this may be desirable to reduce the power load on at least one of the engine 112 and/or the motor-generator 116. For example, if the battery 114 does not include enough electrical energy to allow the vehicle 100 to perform a requested acceleration without running the engine 112 above the optimal engine speed and torque, it may be desirable for total power consumption of the vehicle 100 to be reduced. In that regard, the ECU 102 may decrease an amount of power used by the HVAC system 128 based on a predicted action of the vehicle 100.”).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Salter, as modified by Geller and Follen, with the concept of determining a plurality of operating points as mobility (propulsion) commands for at least one mobility component based on a vehicle model and a driver-route-traffic-specific driving cycle, taught by Geller, in order to more accurately predict the loads that will be experienced by the vehicle and optimize the power required by vehicle systems, like the HVAC system, to improve vehicle efficiency (Geller, para. 0014: “The systems and methods provide various benefits and advantages such as improving vehicle efficiency and durability of vehicle components. Because the system allows for a change in the total power consumption of vehicle accessories, the vehicle can more efficiently prepare for an upcoming acceleration or deceleration. For example, the vehicle may reduce power provided to the HVAC system in order to allow an engine to power through the acceleration at an optimally efficient torque and engine speed.”).
Regarding claim 7, and analogous claim 14, Salter, Geller, and Follen teach The controller of claim 6, and Geller further teaches the following:
wherein the processor is further configured to control the at least one mobility component in accordance with the mobility commands, wherein the mobility commands specify preferred torques and speeds of the at least one mobility component (Geller, para. 0034: “The engine 112 may have an optimal setting at which it may perform most efficiently. For example, the optimal setting may include an optimal engine speed and an optimal torque. In that regard, when the ECU 102 predicts that the vehicle will accelerate to 65 mph, the ECU 102 may control the engine 112 [i.e., controlling the at least one mobility component in accordance with the mobility commands] to turn on and operate at the optimal engine speed and torque [i.e., the mobility commands specify preferred torques and speeds of the at least one mobility component] before the predicted acceleration begins.”).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Salter, as modified by Geller and Follen, with the concept of controlling at least one mobility component of a vehicle with mobility commands that specify preferred torques and speeds, taught by Geller, in order to operate the vehicle efficiently by optimizing the usage of propulsion [i.e., mobility] components (Geller, para. 0037: “Thus, by predicting accelerations and decelerations of the vehicle 100 and controlling the power consumed by the HVAC system 128 based on the prediction, the ECU 102 may further increase efficiency of the vehicle 100.”).
Additional Relevant Art
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure:
US-20230234418-A1 (2023-07-27) | “An electric vehicle thermal management system and method utilizing power demand models for both propulsion and auxiliary systems, and an intelligent thermal load management module. A navigation unit formulates potential routes to a destination that is either set by a driver or predicted by a drive cycle prediction module. The routes are used to inform the propulsion power demand model, while historical driving patterns based on GPS data and time-dependent climate inputs inform the auxiliary power demand model. The expected power demands for the individual systems and overall combined system are accounted for in calculations performed by optimization algorithms in an intelligent thermal load management module. The calculations produce desired temperature setpoints which send heating and cooling requests to refrigerant and coolant fluid handlers and subsequent actuators that control the refrigerant and coolant fluid loops.” Relevant to claim(s) 1, 8, and 15.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Leah N Miller whose telephone number is (703)756-1933. The examiner can normally be reached M-Th 8:30am - 5:30pm ET.
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/L.N.M./Examiner, Art Unit 3663
/ABBY J FLYNN/Supervisory Patent Examiner, Art Unit 3663
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