# US 12,109,909 B2 · Goal-based electric vehicle charging > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,109,909 B2 - Document ID: US12109909B2 - Status: Granted - Kind: B2 - Application number: 17/885,698 - Filed: 2022-08-11 - Published: 2024-02-15 - Granted: 2024-10-08 - Earliest claimed: 2022-08-11 - Assignees: GM Global Technology Operations LLC - Applicants: GM Global Technology Operations LLC - Inventors: Bharatkumar Hegde; Ibrahim Haskara - Web page: https://patentgrep.com/patent/US12109909B2 ## CPC - B60L 58/12: responding to state of charge [SoC] - G01C 21/3608: {using speech input, e.g. using speech recognition} - B60L 3/12: Recording operating variables {; Monitoring of operating variables} - B60L 53/62: in response to charging parameters, e.g. current, voltage or electrical charge - B60L 58/16: responding to battery ageing, e.g. to the number of charging cycles or the state of health [SoH] - B60L 58/18: of two or more battery modules - G01C 21/3407: {specially adapted for specific applications} - G01R 31/3835: involving only voltage measurements - H02J 7/92: with prioritisation of loads or sources - B60L 2240/62: Vehicle position - B60L 2240/80: Time limits - B60L 2250/14: by input of vehicle departure time - B60L 2260/44: by parameter estimation - B60L 2260/52: drive range estimation, e.g. of estimation of available travel distance - B60L 2260/54: Energy consumption estimation - B60L 2260/58: Departure time prediction - G01R 31/392: Determining battery ageing or deterioration, e.g. state of health - H02J 2105/37: exchanging power with electric vehicles [EV] or with hybrid electric vehicles [HEV] - B60L: PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES (arrangements or mounting of electrical propulsion units or of plural diverse prime-movers for mutual or common propulsion in vehicles B60K1/00, B60K6/20; arrangements or mounting of electrical gearing in vehicles B60K17/12, B60K17/14; preventing wheel slip by reducing power in rail vehicles B61C15/08; dynamo-electric machines H02K; control or regulation of electric motors H02P); SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES (electric coupling devices combined with mechanical couplings of vehicles B60D1/64; electric heating for vehicles B60H1/00); ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL (control or regulation of electric motors H02P); MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) - G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12) - H02J: ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY ## Abstract A system in a vehicle includes memory to store driving history and charging history of the vehicle. The system also includes a processor to obtain a predicted battery life of one or more battery packs of the vehicle based on the driving history and the charging history, obtain a targeted battery life of a user indicating a mileage goal for a specific charge capacity of the one or more battery packs, and determine a difference between the predicted battery life and the targeted battery life. The processor solves an optimization problem to determine a future charging strategy to achieve the targeted battery life and controls an onboard charging system or an external charger based on the future charging strategy or controls routing or navigation based on the future charging strategy. ## Claims ### Claim 1 A system in a vehicle comprising: memory configured to store driving history and charging history of the vehicle; and a processor configured to obtain a predicted battery life of one or more battery packs of the vehicle based on the driving history and the charging history, to obtain a targeted battery life of a user indicating a mileage goal for a specific charge capacity of the one or more battery packs, to determine a difference between the predicted battery life and the targeted battery life, to solve an optimization problem to determine a future charging strategy to achieve the targeted battery life, and to control an onboard charging system or an external charger based on the future charging strategy or to control routing or navigation based on the future charging strategy. ### Claim 2 (depends on 1) The system according to claim 1, wherein the processor is configured to obtain the predicted battery life using a physics-based or empirical aging model. ### Claim 3 (depends on 1) The system according to claim 1, wherein the processor is configured to obtain the predicted battery life based additionally on historical and current environmental conditions, including temperature, during use of the vehicle. ### Claim 4 (depends on 1) The system according to claim 1, wherein the processor is configured to obtain the predicted battery life based additionally on historical and current parameters of the one or more battery packs, including voltage, during use of the vehicle. ### Claim 5 (depends on 1) The system according to claim 1, wherein the processor is configured to obtain the targeted battery life based on selection of a mode by the user. ### Claim 6 (depends on 1) The system according to claim 1, wherein the processor is configured to set up the optimization problem with constraints including a constraint that a battery life, which indicates a charge capacity of the one or more battery packs, after a number of charges estimated to reach the mileage goal must exceed a battery life at an end of life of the one or more battery packs. ### Claim 7 (depends on 6) The system according to claim 6, wherein the processor is configured to solve the optimization problem using dynamic programming or a stochastic search. ### Claim 8 (depends on 1) The system according to claim 1, wherein the processor is configured to control a duration of charging, a type of charging, or a charging profile by the onboard charging system based on the future charging strategy. ### Claim 9 (depends on 1) The system according to claim 1, wherein the processor is configured to control a duration of charging, a type of charging, or a charging profile by the external charger based on the future charging strategy. ### Claim 10 (depends on 1) The system according to claim 1, wherein the processor is configured to determine routing or navigation that facilitates a duration of charging indicated by the future charging strategy. ### Claim 11 A controller including a non-transitory computer-readable medium storing instructions that, when processed by one or more processors of the controller, implement a method in a vehicle, the method comprising: storing driving history and charging history of the vehicle; obtaining a predicted battery life of one or more battery packs of the vehicle based on the driving history and the charging history; obtaining a targeted battery life of a user indicating a mileage goal for a specific charge capacity of the one or more battery packs; determining a difference between the predicted battery life and the targeted battery life; solving an optimization problem to determine a future charging strategy to achieve the targeted battery life; and controlling an onboard charging system or an external charger based on the future charging strategy or controlling routing or navigation based on the future charging strategy. ### Claim 12 (depends on 11) The method according to claim 11, wherein the obtaining the predicted battery life includes using a physics-based or empirical aging model. ### Claim 13 (depends on 11) The method according to claim 11, wherein the obtaining the predicted battery life is based additionally on historical and current environmental conditions, including temperature, during use of the vehicle. ### Claim 14 (depends on 11) The method according to claim 11, wherein the obtaining the predicted battery life is based additionally on historical and current parameters of the one or more battery packs, including voltage, during use of the vehicle. ### Claim 15 (depends on 11) The method according to claim 11, wherein the obtaining the targeted battery life is based on selection of a mode by the user. ### Claim 16 (depends on 11) The method according to claim 11, further comprising setting up the optimization problem with constraints including a constraint that a battery life, which indicates a charge capacity of the one or more battery packs, after a number of charges estimated to reach the mileage goal must exceed a battery life at an end of life of the one or more battery packs. ### Claim 17 (depends on 16) The method according to claim 16, further comprising solving the optimization problem using dynamic programming or a stochastic search. ### Claim 18 (depends on 11) The method according to claim 11, further comprising controlling a duration of charging, a type of charging, or a charging profile implemented by the onboard charging system based on the future charging strategy. ### Claim 19 (depends on 11) The method according to claim 11, further comprising controlling a duration of charging, a type of charging, or a charging profile implemented by the external charger based on the future charging strategy. ### Claim 20 (depends on 11) The method according to claim 11, wherein the controlling the routing or navigation includes determining the routing or navigation that facilitates a duration of charging indicated by the future charging strategy.