Goal-based electric vehicle charging

Patent metadata

Field	Value
Publication number	US-12109909-B2
Application number	US-202217885698-A
Country	US
Kind code	B2
Filing date	Aug 11, 2022
Priority date	Aug 11, 2022
Publication date	Oct 8, 2024
Grant date	Oct 8, 2024

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.

First claim

What is claimed is:

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.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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.

7. The system according to claim 6 , wherein the processor is configured to solve the optimization problem using dynamic programming or a stochastic search.

8. 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.

9. 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.

10. 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.

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.

12. The method according to claim 11 , wherein the obtaining the predicted battery life includes using a physics-based or empirical aging model.

13. 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.

14. 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.

15. The method according to claim 11 , wherein the obtaining the targeted battery life is based on selection of a mode by the user.

16. 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.

17. The method according to claim 16 , further comprising solving the optimization problem using dynamic programming or a stochastic search.

18. 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.

19. 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.

20. 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.

Assignees

• Gm Global Tech Operations Llc

Inventors

• Hegde Bharatkumar
• Haskara Ibrahim

Classifications

• H02J2105/37

  exchanging power with electric vehicles [EV] or with hybrid electric vehicles [HEV] · CPC title

• H02J7/92

  with prioritisation of loads or sources · CPC title

• G01C21/3407

  specially adapted for specific applications · CPC title

• B60L58/16

  responding to battery ageing, e.g. to the number of charging cycles or the state of health [SoH] · CPC title

• B60L58/18

  of two or more battery modules · CPC title