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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on January 7, 2026 has been entered.
Response to Arguments
Applicant’s arguments, see Pages 6-8, filed January 7, 2026, with respect to the rejection(s) of claim(s) 1-20 under 35 U.S.C. 102 and/or 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Li et al. (US 20150097512; hereinafter Li).
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1-4, 7-12, 14-18, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Money et al. (US 20200017097; hereinafter Money) in view of Li et al. (US 20150097512; hereinafter Li).
In regards to claim 1, Money discloses of an apparatus comprising:
an energy storage device configured to absorb energy of a primary braking system (“Battery 103 is a rechargeable battery and can power electric motor 108 or other electric motors for vehicle 100. Examples of battery 103 can include lead-acid, nickel-cadmium, nickel-metal hydride, lithium ion, lithium polymer, or other types of rechargeable batteries. For one example, battery 103 can be located on the floor and run along the bottom of vehicle 100. As a rechargeable battery, for one example, battery 103 can be charged by being plugged into an electrical outlet. And, for another example, battery 103 can be charged during regenerative braking when electric motor 108 is inverted (not supplying torque to drive wheels 109) and converting kinetic energy from rotating wheels 109 into electrical energy used for recharging battery 103. The location and number of batteries is not limited to one and can be located throughout vehicle 100 in any location.” (Para 0024)); and
a controller coupled to the energy storage device to receive data indicating conditions of the energy storage device (“The following detailed description provides embodiments and examples to implement a downhill charge sustain battery protection strategy. For one example, a vehicle includes a vehicle control unit (VCU). The VCU detects a charge sustain event condition to trigger a braking strategy of switching between regenerative braking and friction braking that can sustain a sufficient charge for the battery without exceeding its maximum limits and even prevent braking components from overheating.” (Para 0019) and “One example condition to trigger a charge sustain event is a vehicle at or near a top of a hill or going down a hill in a lift condition (no pedals pressed) and the battery is fully charged at its maximum state of charge (SOC) or voltage limit. In this condition, the vehicle may experience a break-away speed situation and instead of continuously applying regenerative braking, which can charge the battery beyond is maximum SOC and voltage limit, the VCU can switch the vehicle between regenerative braking and friction such that the battery does not exceed its maximum SOC and voltage limit. If a temperature of one of the braking components exceeds a maximum limit, the VCU can also blend-out friction braking and blend-in regenerative braking thereby preventing braking components from overheating.” (Para 0020)), the controller configured to:
…
predict a point at which the energy storage device will exhibit reduced capability to absorb energy (“One example condition to trigger a charge sustain event is a vehicle at or near a top of a hill or going down a hill in a lift condition (no pedals pressed) and the battery is fully charged at its maximum state of charge (SOC) or voltage limit. In this condition, the vehicle may experience a break-away speed situation and instead of continuously applying regenerative braking, which can charge the battery beyond is maximum SOC and voltage limit, the VCU can switch the vehicle between regenerative braking and friction such that the battery does not exceed its maximum SOC and voltage limit. If a temperature of one of the braking components exceeds a maximum limit, the VCU can also blend-out friction braking and blend-in regenerative braking thereby preventing braking components from overheating.” (Para 0020) and “As shown in graphs 404 and 406, as the state of charge (SOC) of battery 103 rises when regenerative braking is on and the electric motor 203 operates as a power generator to charge battery 103. As the SOC rises to near or at full charge, regenerative braking is turned off and friction braking is turned on.” (Para 0048), and “In the event of the battery charging during a runaway condition, this can be problematic because the battery may overcharge beyond its maximum limit causing the voltage level in the individual cells of the battery to surge. As a result, the thermal level in the battery can spike, possibly causing the battery to catch on fire. Such an event can be dangerous to the driver and passengers and may cause severe damage to the vehicle.” (Para 0003) and “For one example, VCU 107 of the powertrain system 120 can detect a charge sustain event condition and trigger brake system 110 and powertrain system 120 to implement a battery protection strategy of switching between regenerative braking and friction braking. For example, VCU 107 can receive location data for vehicle 100 to determine that vehicle 100 is at or near a top of a hill or going down a hill. VCU 107 can also receive sensor data or signals from vehicle components indicating that the vehicle 100 is in a lift condition (no pedals pressed) and battery 103 is fully charged at its maximum state of charge (SOC) or voltage limit. In this condition, VCU 107 can determine vehicle 100 is in a charge sustain event because vehicle 100 may enter a break-away speed situation that continuously recharges battery 103 during regenerative braking because electric motor 108 is not driving wheels 109. Alternatively, if this condition is detected, VCU 107 can trigger a battery protection strategy of switching between regenerative braking and friction braking. VCU 107 can control switching of regenerative braking and friction braking such that the charge on battery 103 does not exceed its maximum SOC and voltage limit while sustaining a sufficient charge for the battery 103.” (Para 0028)) …
provide a control signal to control a secondary braking system to provide braking capability in advance of the predicted point (“One example condition to trigger a charge sustain event is a vehicle at or near a top of a hill or going down a hill in a lift condition (no pedals pressed) and the battery is fully charged at its maximum state of charge (SOC) or voltage limit. In this condition, the vehicle may experience a break-away speed situation and instead of continuously applying regenerative braking, which can charge the battery beyond is maximum SOC and voltage limit, the VCU can switch the vehicle between regenerative braking and friction such that the battery does not exceed its maximum SOC and voltage limit. If a temperature of one of the braking components exceeds a maximum limit, the VCU can also blend-out friction braking and blend-in regenerative braking thereby preventing braking components from overheating.” (Para 0020) and “As shown in graphs 404 and 406, as the state of charge (SOC) of battery 103 rises when regenerative braking is on and the electric motor 203 operates as a power generator to charge battery 103. As the SOC rises to near or at full charge, regenerative braking is turned off and friction braking is turned on.” (Para 0048), and “For one example, VCU 107 of the powertrain system 120 can detect a charge sustain event condition and trigger brake system 110 and powertrain system 120 to implement a battery protection strategy of switching between regenerative braking and friction braking. For example, VCU 107 can receive location data for vehicle 100 to determine that vehicle 100 is at or near a top of a hill or going down a hill. VCU 107 can also receive sensor data or signals from vehicle components indicating that the vehicle 100 is in a lift condition (no pedals pressed) and battery 103 is fully charged at its maximum state of charge (SOC) or voltage limit. In this condition, VCU 107 can determine vehicle 100 is in a charge sustain event because vehicle 100 may enter a break-away speed situation that continuously recharges battery 103 during regenerative braking because electric motor 108 is not driving wheels 109. Alternatively, if this condition is detected, VCU 107 can trigger a battery protection strategy of switching between regenerative braking and friction braking. VCU 107 can control switching of regenerative braking and friction braking such that the charge on battery 103 does not exceed its maximum SOC and voltage limit while sustaining a sufficient charge for the battery 103.” (Para 0028)).
However, Money does not specifically disclose of receive upcoming segment information including surface condition information;
determine an estimate of upcoming braking energy produced by upcoming regenerative braking using the upcoming segment information and determine the conditions of the energy storage device;
predict a point at which the energy storage device will exhibit reduced capability to absorb energy using the estimate of the upcoming braking energy and the conditions of the energy storage device.
Li, in the same field of endeavor, teaches of receive upcoming segment information including surface condition information (“A solution is to determine the charge setpoint based on a future battery maximum net SOC increase during the next trip. The greatest future battery SOC increases or maximum net SOC increase may be for multiple reasons including regenerative braking based on the upcoming route, engine use and driving behavior. The upcoming route may be the next route and/or next destination. The upcoming route may be determined at the end of the "previous" trip before the vehicle is connected to a battery charger, or sometime before departure to the next route. The input of the next route can be done in multiple ways including but not limited to (i) direct driver input of the next trip, (ii) predicting battery SOC increases based on the driver's previous driving history, (iii) using GPS or other navigation data to determine the elevation and routes from the current location. In the event that the driver does not input future trip information before exiting the vehicle, a predictive system may be used to determine future SOC increases and profile. If the upcoming destination is obtained, the vehicle may calculate the most likely route to that destination and the associated SOC profile.” (Para 0029), “Conditional driving behavior predicted through past driving history provides information regarding energy usage or energy recuperation potentials. The conditional driving behavior includes road information, traffic information, posted speed limits, and traffic signs, etc. Generic analysis on the energy profiles may be derived from predicted or assigned destinations with route information. Driver's average behavior on given road condition (posted speed, road grade, curvature, time of day, weather, traffic, traffic lights, road signs, etc.) is data used to influence the energy analysis.” (Para 0030), “After determining the future route and driving behavior, the system analyzes the next entered, determined or predicted route in order to predict the energy increases or decreases at each point along the route. This is a predicted calculation of the SOC increase for each segment of the route due to SOC increases including regenerative braking in a "brake section" or engine-generator energy generation and SOC decreases during energy uses including "climbing a hill" between braking sections or battery accessory uses. The relationship between geographical attributes and SOC contribution is inverted; downhill driving gives an upwards slope or positive net contribution of SOC and uphill driving gives a downwards slope or negative net consumption of SOC.” (Para 0031));
determine an estimate of upcoming braking energy produced by upcoming regenerative braking using the upcoming segment information and determine the conditions of the energy storage device (“After determining the future route and driving behavior, the system analyzes the next entered, determined or predicted route in order to predict the energy increases or decreases at each point along the route. This is a predicted calculation of the SOC increase for each segment of the route due to SOC increases including regenerative braking in a "brake section" or engine-generator energy generation and SOC decreases during energy uses including "climbing a hill" between braking sections or battery accessory uses. The relationship between geographical attributes and SOC contribution is inverted; downhill driving gives an upwards slope or positive net contribution of SOC and uphill driving gives a downwards slope or negative net consumption of SOC.” (Para 0031), “FIG. 6 is a plot of the SOC level 602 with respect to trip distance 504 which is the spatial location of the vehicle along the trip. In this example plot, the maximum SOC level 604 and the minimum SOC level 606 provide a battery operating range. The complete SOC profile 500 is adjusted such that the maximum SOC contribution 516 is aligned with the maximum SOC level 604. From this the desired starting SOC value 608 can be determined. Also, the intersection point 610 at which the battery SOC profile 500 will intersect the minimum SOC level 606 can be determined. The intersection point 610 is where the vehicle control will transition from normal operation to a charge sustaining mode of operation.” (Para 0035), see also Figs 6-7);
predict a point at which the energy storage device will exhibit reduced capability to absorb energy using the estimate of the upcoming braking energy and the conditions of the energy storage device (“FIG. 5 shows an example complete SOC contribution profile 500. This SOC profile 500 is a plot of the SOC contribution 502 with respect to trip distance 504 which is the spatial location of the vehicle along the trip. The upwards slopes 506 are positive contribution of energy from predicted regenerative braking and the downward slopes 508 are negative contribution of energy for the up-hill sections where the vehicle consumes energy to go up the hills. The upwards slopes 506 have a corresponding positive SOC change rate 520, and the downwards slopes 508 have a corresponding negative SOC change rate 522. In the example, the driver starts his trip with a slight downhill section 510, followed by a longer uphill section 512 and then another downhill section 514.” (Para 0033), “After determining the future route and driving behavior, the system analyzes the next entered, determined or predicted route in order to predict the energy increases or decreases at each point along the route. This is a predicted calculation of the SOC increase for each segment of the route due to SOC increases including regenerative braking in a "brake section" or engine-generator energy generation and SOC decreases during energy uses including "climbing a hill" between braking sections or battery accessory uses. The relationship between geographical attributes and SOC contribution is inverted; downhill driving gives an upwards slope or positive net contribution of SOC and uphill driving gives a downwards slope or negative net consumption of SOC.” (Para 0031), “FIG. 6 is a plot of the SOC level 602 with respect to trip distance 504 which is the spatial location of the vehicle along the trip. In this example plot, the maximum SOC level 604 and the minimum SOC level 606 provide a battery operating range. The complete SOC profile 500 is adjusted such that the maximum SOC contribution 516 is aligned with the maximum SOC level 604. From this the desired starting SOC value 608 can be determined. Also, the intersection point 610 at which the battery SOC profile 500 will intersect the minimum SOC level 606 can be determined. The intersection point 610 is where the vehicle control will transition from normal operation to a charge sustaining mode of operation.” (Para 0035), see also Figs 5-7 and Para 0028)
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the prediction of a point where an energy storage device will exhibit reduced capability to absorb energy, as taught by Money, to include being based on an estimated upcoming braking energy produced based on received segment information and a condition of an energy storage device, as taught by Li, with a reasonable expectation of success in order to maintain the battery SOC within prescribed limits to avoid decreasing the performance or life of the battery (Li Para 0002).
In regards to claim 2, Money in view of Li teaches of the apparatus of claim 1, wherein the controller is configured to predict the point based on state of charge of the energy storage device (“As shown in graphs 404 and 406, as the state of charge (SOC) of battery 103 rises when regenerative braking is on and the electric motor 203 operates as a power generator to charge battery 103. As the SOC rises to near or at full charge, regenerative braking is turned off and friction braking is turned on.” (Money Para 0048), and “For one example, VCU 107 of the powertrain system 120 can detect a charge sustain event condition and trigger brake system 110 and powertrain system 120 to implement a battery protection strategy of switching between regenerative braking and friction braking. For example, VCU 107 can receive location data for vehicle 100 to determine that vehicle 100 is at or near a top of a hill or going down a hill. VCU 107 can also receive sensor data or signals from vehicle components indicating that the vehicle 100 is in a lift condition (no pedals pressed) and battery 103 is fully charged at its maximum state of charge (SOC) or voltage limit. In this condition, VCU 107 can determine vehicle 100 is in a charge sustain event because vehicle 100 may enter a break-away speed situation that continuously recharges battery 103 during regenerative braking because electric motor 108 is not driving wheels 109. Alternatively, if this condition is detected, VCU 107 can trigger a battery protection strategy of switching between regenerative braking and friction braking. VCU 107 can control switching of regenerative braking and friction braking such that the charge on battery 103 does not exceed its maximum SOC and voltage limit while sustaining a sufficient charge for the battery 103.” (Money Para 0028)).
In regards to claim 3, Money in view of Li teaches of the apparatus of claim 1, wherein the conditions include a temperature (“For one example, VCU 107 of the powertrain system 120 can detect a charge sustain event condition and trigger brake system 110 and powertrain system 120 to implement a battery protection strategy of switching between regenerative braking and friction braking. For example, VCU 107 can receive location data for vehicle 100 to determine that vehicle 100 is at or near a top of a hill or going down a hill. VCU 107 can also receive sensor data or signals from vehicle components indicating that the vehicle 100 is in a lift condition (no pedals pressed) and battery 103 is fully charged at its maximum state of charge (SOC) or voltage limit. In this condition, VCU 107 can determine vehicle 100 is in a charge sustain event because vehicle 100 may enter a break-away speed situation that continuously recharges battery 103 during regenerative braking because electric motor 108 is not driving wheels 109. Alternatively, if this condition is detected, VCU 107 can trigger a battery protection strategy of switching between regenerative braking and friction braking. VCU 107 can control switching of regenerative braking and friction braking such that the charge on battery 103 does not exceed its maximum SOC and voltage limit while sustaining a sufficient charge for the battery 103.” (Money Para 0028) and “For other examples, VCU 107 can detect other types of charge sustain events including detecting a temperature of one or more braking components at or beyond a threshold or limit, a temperature related to battery 103 at or beyond a threshold or limit, or a SOC or voltage level of the battery 103 at or beyond a threshold or limit or any combination of these conditions. Thus, such a battery protection strategy can also prevent braking components from overheating. Although VCU 107 is shown as part of powertrain system 120, VCU 107 can be a separate controller within vehicle 100 and part of other systems to communicate with any number of ECUs controlling other operations and functions for vehicle 100.” (Money Para 0029)).
In regards to claim 4, Money in view of Li teaches of the apparatus of claim 1, wherein the controller is configured to control the secondary braking system and the primary braking system based on predicted braking usage of the primary braking system (“As shown in graphs 404 and 406, as the state of charge (SOC) of battery 103 rises when regenerative braking is on and the electric motor 203 operates as a power generator to charge battery 103. As the SOC rises to near or at full charge, regenerative braking is turned off and friction braking is turned on.” (Para 0048), and “For one example, VCU 107 of the powertrain system 120 can detect a charge sustain event condition and trigger brake system 110 and powertrain system 120 to implement a battery protection strategy of switching between regenerative braking and friction braking. For example, VCU 107 can receive location data for vehicle 100 to determine that vehicle 100 is at or near a top of a hill or going down a hill. VCU 107 can also receive sensor data or signals from vehicle components indicating that the vehicle 100 is in a lift condition (no pedals pressed) and battery 103 is fully charged at its maximum state of charge (SOC) or voltage limit. In this condition, VCU 107 can determine vehicle 100 is in a charge sustain event because vehicle 100 may enter a break-away speed situation that continuously recharges battery 103 during regenerative braking because electric motor 108 is not driving wheels 109. Alternatively, if this condition is detected, VCU 107 can trigger a battery protection strategy of switching between regenerative braking and friction braking. VCU 107 can control switching of regenerative braking and friction braking such that the charge on battery 103 does not exceed its maximum SOC and voltage limit while sustaining a sufficient charge for the battery 103.” (Money Para 0028)).
In regards to claim 7, Money in view of Li teaches of the apparatus of claim 4, wherein the controller is further configured to determine a braking power needed from the secondary braking system to prevent derating of machine performance due to aggregate deration of braking systems (“One example condition to trigger a charge sustain event is a vehicle at or near a top of a hill or going down a hill in a lift condition (no pedals pressed) and the battery is fully charged at its maximum state of charge (SOC) or voltage limit. In this condition, the vehicle may experience a break-away speed situation and instead of continuously applying regenerative braking, which can charge the battery beyond is maximum SOC and voltage limit, the VCU can switch the vehicle between regenerative braking and friction such that the battery does not exceed its maximum SOC and voltage limit. If a temperature of one of the braking components exceeds a maximum limit, the VCU can also blend-out friction braking and blend-in regenerative braking thereby preventing braking components from overheating.” (Para 0020) and “For signal 294, VCU 207 informs BCU 212 of the amount of friction brake torque target and modulation speed for friction braking to be applied by brake system 210. For example, VCU 207 informs BCU 212 of the rate at which switching or blending of friction braking and regenerative braking should occur during the charge sustain event condition. For one example, VCU 207 informs BCU 212 to switch or alternate friction braking at a modulation speed or frequency in the range of around 100 hertz (Hz) and less than 400 Hz.” (Money Para 0038)).
In regards to claim 8, Money in view of Li teaches of the apparatus of claim 7, wherein the controller is further configured to implement a controlling algorithm to control the secondary braking system (“One example condition to trigger a charge sustain event is a vehicle at or near a top of a hill or going down a hill in a lift condition (no pedals pressed) and the battery is fully charged at its maximum state of charge (SOC) or voltage limit. In this condition, the vehicle may experience a break-away speed situation and instead of continuously applying regenerative braking, which can charge the battery beyond is maximum SOC and voltage limit, the VCU can switch the vehicle between regenerative braking and friction such that the battery does not exceed its maximum SOC and voltage limit. If a temperature of one of the braking components exceeds a maximum limit, the VCU can also blend-out friction braking and blend-in regenerative braking thereby preventing braking components from overheating.” (Para 0020) and “As shown in graphs 404 and 406, as the state of charge (SOC) of battery 103 rises when regenerative braking is on and the electric motor 203 operates as a power generator to charge battery 103. As the SOC rises to near or at full charge, regenerative braking is turned off and friction braking is turned on.” (Money Para 0048), and “For one example, VCU 107 of the powertrain system 120 can detect a charge sustain event condition and trigger brake system 110 and powertrain system 120 to implement a battery protection strategy of switching between regenerative braking and friction braking. For example, VCU 107 can receive location data for vehicle 100 to determine that vehicle 100 is at or near a top of a hill or going down a hill. VCU 107 can also receive sensor data or signals from vehicle components indicating that the vehicle 100 is in a lift condition (no pedals pressed) and battery 103 is fully charged at its maximum state of charge (SOC) or voltage limit. In this condition, VCU 107 can determine vehicle 100 is in a charge sustain event because vehicle 100 may enter a break-away speed situation that continuously recharges battery 103 during regenerative braking because electric motor 108 is not driving wheels 109. Alternatively, if this condition is detected, VCU 107 can trigger a battery protection strategy of switching between regenerative braking and friction braking. VCU 107 can control switching of regenerative braking and friction braking such that the charge on battery 103 does not exceed its maximum SOC and voltage limit while sustaining a sufficient charge for the battery 103.” (Money Para 0028)).
In regards to claim 9, Money in view of Li teaches of the apparatus of claim 1, comprising a plurality of energy storage devices (“Battery 103 is a rechargeable battery and can power electric motor 108 or other electric motors for vehicle 100. Examples of battery 103 can include lead-acid, nickel-cadmium, nickel-metal hydride, lithium ion, lithium polymer, or other types of rechargeable batteries. For one example, battery 103 can be located on the floor and run along the bottom of vehicle 100. As a rechargeable battery, for one example, battery 103 can be charged by being plugged into an electrical outlet. And, for another example, battery 103 can be charged during regenerative braking when electric motor 108 is inverted (not supplying torque to drive wheels 109) and converting kinetic energy from rotating wheels 109 into electrical energy used for recharging battery 103. The location and number of batteries is not limited to one and can be located throughout vehicle 100 in any location.” (Money Para 0024)).
In regards to claim 10, Money in view of Li teaches of the apparatus of claim 9, wherein the plurality of energy storage devices comprises at least one battery. (“Battery 103 is a rechargeable battery and can power electric motor 108 or other electric motors for vehicle 100. Examples of battery 103 can include lead-acid, nickel-cadmium, nickel-metal hydride, lithium ion, lithium polymer, or other types of rechargeable batteries. For one example, battery 103 can be located on the floor and run along the bottom of vehicle 100. As a rechargeable battery, for one example, battery 103 can be charged by being plugged into an electrical outlet. And, for another example, battery 103 can be charged during regenerative braking when electric motor 108 is inverted (not supplying torque to drive wheels 109) and converting kinetic energy from rotating wheels 109 into electrical energy used for recharging battery 103. The location and number of batteries is not limited to one and can be located throughout vehicle 100 in any location.” (Money Para 0024)).
In regards to claim 11, the claim recites analogous limitations to claim 1, and is therefore rejected on the same premise.
In regards to claim 12, the claim recites analogous limitations to the combination of claims 2-3, and is therefore rejected on the same premise.
In regards to claims 14-15, the claims recite analogous limitations to the combination of claims 7-8, and are therefore rejected on the same premise.
In regards to claim 16, the claim recites analogous limitations to the combination of claims 9-10, and is therefore rejected on the same premise.
In regards to claim 17, the claim recites analogous limitations to the combination of claims 1 and 7, and is therefore rejected on the same premise.
In regards to claim 18, the claim recites analogous limitations to claim 4, and is therefore rejected on the same premise.
In regards to claim 20, the claim recites analogous limitations to claim 7, and is therefore rejected on the same premise.
Claim(s) 5-6, 13, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Money in view of Li as applied to claim 1 above, and further in view of Kobayashi et al. (US 20230234598; hereinafter Kobayashi; already of record from IDS).
In regards to claim 5, Money in view of Li teaches of the apparatus of claim 4.
However, Money in view of Li does not specifically teach of wherein the controller is configured to implement a machine learning algorithm to predict braking usage.
Kobayashi, in the same field of endeavor, teaches of wherein the controller is configured to implement a machine learning algorithm to predict braking usage (“The second estimation algorithm E2 indicates a relationship between the driving current (second deterioration parameter) of the corresponding MG 20 and the degree of deterioration of the MG 20. The second estimation algorithm E2 outputs the degree of deterioration of the corresponding MG 20 in response to an input of the value of the driving current for the MG 20 (current for driving the MG 20).” (Para 0089) and “The MG 20 is driven by the PCU 22 and rotates the drive wheels of the vehicle 1. The MG 20 generates regenerative power and supplies the generated electric power to the battery 160. The PCU 22 drives the MG 20 by using the electric power supplied from the battery 160. The PCU 22 drives the MG 20 with an electric power value (for example, a current value) given by an instruction from the ECU 21. In the present embodiment, the driving voltage of the MG 20 (voltage for driving the MG 20) is kept substantially constant. As the driving current of the MG 20 (current for driving the MG 20) increases, the force of the MG 20 for propelling the vehicle 1 (force for accelerating the vehicle 1) increases. The MG sensor 20a detects the driving current, the driving voltage, and the temperature of the MG 20. Detection results from the MG sensor 20a are output to the ECU 21.” (Para 0085), “In the present embodiment, an artificial intelligence (AI) algorithm is adopted as each estimation algorithm. Each estimation algorithm may be a trained model that has undergone machine learning using big data held by the server 500 (for example, data actually measured on a vehicle having the same specifications as those of the vehicle 1). The estimation algorithm is not limited to this, and may be a rule-based algorithm. Each estimation algorithm may be, for example, a mathematical expression or a map.” (Para 0090), see also claims 1 and 6, where the there is an AI algorithm for estimating a degree of deterioration for a component, including a braking device and a motor generator that performs regenerative braking).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the controller to control the first and second braking device, as taught by Money in view of Li, to include using a machine learning algorithm to predict braking usage, as taught by Kobayashi, with a reasonable expectation of success in order to determine the degree of deterioration of the brake components with a high level of accuracy (Kobayashi Para 0009).
In regards to claim 6, Money in view of Li in view of Kobayashi teaches of the apparatus of claim 5, wherein the machine learning algorithm is based on inputs including historical braking trends, a working route of the work machine or a working route of a fleet of work machines (“When the control device 150 determines in S14 that neither the brake pad constituting the hydraulic disc brake device 10 nor the MG 20 needs to be replaced (NO in S14), the process proceeds to S15. In S15, the control device 150 updates the first estimation algorithm E1 and the second estimation algorithm E2 by using the results of the current performance test and the results of the performance test executed in the past.” (Kobayashi Para 0109), “In the present embodiment, an artificial intelligence (AI) algorithm is adopted as each estimation algorithm. Each estimation algorithm may be a trained model that has undergone machine learning using big data held by the server 500 (for example, data actually measured on a vehicle having the same specifications as those of the vehicle 1). The estimation algorithm is not limited to this, and may be a rule-based algorithm. Each estimation algorithm may be, for example, a mathematical expression or a map.” (Kobayashi Para 0090) and “For one example, VCU 107 of the powertrain system 120 can detect a charge sustain event condition and trigger brake system 110 and powertrain system 120 to implement a battery protection strategy of switching between regenerative braking and friction braking. For example, VCU 107 can receive location data for vehicle 100 to determine that vehicle 100 is at or near a top of a hill or going down a hill. VCU 107 can also receive sensor data or signals from vehicle components indicating that the vehicle 100 is in a lift condition (no pedals pressed) and battery 103 is fully charged at its maximum state of charge (SOC) or voltage limit. In this condition, VCU 107 can determine vehicle 100 is in a charge sustain event because vehicle 100 may enter a break-away speed situation that continuously recharges battery 103 during regenerative braking because electric motor 108 is not driving wheels 109. Alternatively, if this condition is detected, VCU 107 can trigger a battery protection strategy of switching between regenerative braking and friction braking. VCU 107 can control switching of regenerative braking and friction braking such that the charge on battery 103 does not exceed its maximum SOC and voltage limit while sustaining a sufficient charge for the battery 103.” (Money Para 0028)).
The motivation for combining Money, Li, and Kobayashi is the same as that recited for claim 5 above.
In regards to claim 13, the claim recites analogous subject matter to claims 4-6 and is rejected on the same premise, but further teaches further comprising communication circuitry configured to transmit and receive data related to a fleet of work machines, (“In the present embodiment, an artificial intelligence (AI) algorithm is adopted as each estimation algorithm. Each estimation algorithm may be a trained model that has undergone machine learning using big data held by the server 500 (for example, data actually measured on a vehicle having the same specifications as those of the vehicle 1). The estimation algorithm is not limited to this, and may be a rule-based algorithm. Each estimation algorithm may be, for example, a mathematical expression or a map.” (Kobayashi Para 0090) and “The vehicle 1 described above can be adopted as one component of a Mobility-as-a-Service (MaaS) system. The MaaS system includes, for example, a mobility service platform (MSPF). The MSPF is a unified platform connected to various mobility services (for example, various mobility services provided by ride-sharing companies, car-sharing companies, insurance companies, car-rental companies, and taxi companies). The server 500 is a computer that manages and releases information for the mobility services on the MSPF to the public. The server 500 manages information on various mobilities and provides information (for example, API and information on collaboration between mobilities) in response to requests from business operators. The business operators that provide services can use various functions provided by the MSPF by using the API publicly available on the MSPF. For example, an API required for ADK development is publicly available on the MSPF.” (Kobayashi Para 0061)).
The motivation for combining Money, Li, and Kobayashi is the same as that recited for claim 5 above.
In regards to claim 19, the claim recites analogous limitations to the combination of claims 5-6, and is therefore rejected on the same premise.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Igarashi et al. (US 20150097512) discloses of determining a SOC increase of decrease for each segment of a route.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kyle J Kingsland whose telephone number is (571)272-3268. The examiner can normally be reached Monday-Friday from 8:00-4:30.
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/KYLE J KINGSLAND/Primary Examiner, Art Unit 3663
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