Systems and methods for monitoring and enhancing utilization of batteries for electric vehicles based on vehicle usage

Patent metadata

Field	Value
Publication number	US-11420532-B2
Application number	US-201615349205-A
Country	US
Kind code	B2
Filing date	Nov 11, 2016
Priority date	Nov 11, 2015
Publication date	Aug 23, 2022
Grant date	Aug 23, 2022

Abstract

Methods and systems for monitoring and optimizing utilization of batteries for electric vehicles are described. Data of battery usage of electric vehicles are monitored using battery monitoring sensors at the electric vehicles for a plurality of users who share use of electric vehicles. Battery usage metrics are determined for the batteries of the electric vehicles based on the data of battery usage and determining user impact metrics based on measured quantities relating to driving of the electric vehicles for the plurality of users, the user impact metrics being indicative of degrees of driving severity placed on the vehicles associated with use habits of particular users. The battery usage metrics and the user impact metrics for the plurality of users are analyzed at a computer processing system to determine a particular user to assign to a particular electric vehicle in a given time period to counteract battery degradation of the battery in a particular electric vehicle, and a particular user is paired with the particular electric vehicle.

First claim

What is claimed is:

1. A method of monitoring and enhancing battery utilization for a group of electric vehicles, comprising:
monitoring data of battery usage of electric vehicles using battery monitoring sensors at the electric vehicles for a plurality of users who share use of electric vehicles;
determining battery usage metrics for the batteries of the electric vehicles based on the data of battery usage;
determining user impact metrics based on sensor measurements and measured quantities of the battery usage metrics corresponding to driving of the electric vehicles by the plurality of users;
analyzing the battery usage metrics and the user impact metrics for the plurality of users at a computer processing system to balance the user impact metrics and the battery usage metrics between the plurality of electric vehicles over time by setting assignments of different ones of the plurality of users to each of the electric vehicles over time;
analyzing the battery usage metrics, charging history, and/or battery usage forecast to determine a particular battery charging profile that indicates how quickly to charge the battery of a particular vehicle; and
determining a surcharge owed to a third party for charging the battery more rapidly than indicated by the particular battery charging profile.

2. The method of claim 1 , wherein the battery usage metrics for the batteries comprise at least one of an average battery discharge rate, a maximum battery discharge rate, and a median battery discharge rate.

3. The method of claim 1 , wherein the user impact metrics further comprise at least one of average acceleration, median acceleration, and maximum acceleration attributable to the plurality of users.

4. The method of claim 1 , comprising determining compensation for an owner of the battery of the particular electric vehicle based on battery usage of the particular electric vehicle during a time period, the owner of the battery being different than an owner of the particular electric vehicle.

5. The method of claim 1 , wherein the data of battery usage comprises battery charging rates.

6. The method of claim 1 , wherein determining the user impact metrics comprises determining braking habits comprising deceleration, braking force, or braking use from the sensors at the electric vehicles.

7. The method of claim 1 , wherein determining the user impact metrics comprises determining HVAC use from the sensors at the electric vehicles.

8. A system for monitoring and enhancing battery utilization for a group of electric vehicles, comprising:
a computer processing system; and
a computer memory,
wherein the processing system is configured to execute steps comprising:
receiving data of battery usage of electric vehicles obtained with battery monitoring sensors at the electric vehicles for a plurality of users who share use of electric vehicles;
determining battery usage metrics for the batteries of the electric vehicles based on the data of battery usage;
determining user impact metrics based on sensor measurements and measured quantities of the battery usage metrics corresponding to driving of the electric vehicles by the plurality of users;
analyzing the battery usage metrics and the user impact metrics for the plurality of users to balance the user impact metrics and the battery usage metrics between the plurality of electric vehicles over time by setting assignments of different ones of the plurality of users to each of the electric vehicles over time;
analyze the battery usage metrics, charging history, and/or battery usage forecast to determine a particular battery charging profile that indicates how quickly to charge the battery of a particular vehicle; and
determine a surcharge owed to a third party for charging the battery more rapidly than indicated by the particular battery charging profile.

9. The system of claim 8 , wherein the battery usage metrics for the batteries further comprise at least one of an average battery discharge rate, a maximum battery discharge rate, and a median battery discharge rate.

10. The system claim 8 , wherein the user impact metrics further comprise at least one of average acceleration, median acceleration, and maximum acceleration attributable to the plurality of users.

11. The system of claim 8 , wherein the data of battery usage comprises battery charging rates.

12. The system of claim 8 , wherein determining the user impact metrics comprises determining braking habits comprising deceleration, braking force, or braking use from the sensors at the electric vehicles.

13. The system of claim 8 , wherein determining the user impact metrics comprises determining HVAC use from the sensors at the electric vehicles.

14. A non-transitory computer readable medium comprising program instructions for monitoring and enhancing battery utilization for a group of electric vehicles, the program instructions when executed causing a computer processing system to execute steps comprising:
receiving data of battery usage of electric vehicles using battery monitoring sensors at the electric vehicles for a plurality of users who share use of electric vehicles;
determining battery usage metrics for the batteries of the electric vehicles based on the data of battery usage;
determining user impact metrics based on sensor measurements and measured quantities of the battery usage metrics corresponding to driving of the electric vehicles by the plurality of users;
analyzing the battery usage metrics and the user impact metrics for the plurality of users to balance the user impact metrics and the battery usage metrics between the plurality of electric vehicles over time by setting assignments of different ones of the plurality of users to each of the electric vehicles over time;
analyze the battery usage metrics, charging history, and/or battery usage forecast to determine a particular battery charging profile that indicates how quickly to charge the battery of a particular vehicle; and
determine a surcharge owed to a third party for charging the battery more rapidly than indicated by the particular battery charging profile.

15. The non-transitory computer readable medium of claim 14 , wherein the battery usage metrics for the batteries comprise at least one of an average battery discharge rate, a maximum battery discharge rate, and a median battery discharge rate.

16. The non-transitory computer readable medium of claim 14 , wherein the user impact metrics further comprise at least one of average acceleration, median acceleration, and maximum acceleration attributable to the plurality of users.

17. The non-transitory computer readable medium of claim 14 , wherein the data of battery usage comprises battery charging rates.

18. The non-transitory computer readable medium of claim 14 , wherein determining the user impact metrics comprises determining braking habits comprising deceleration, braking force, or braking use from the sensors at the electric vehicles.

19. The non-transitory computer readable medium of claim 14 , wherein determining the user impact metrics comprises determining HVAC use from the sensors at the electric vehicles.

Assignees

• Rivian Ip Holdings Llc

Inventors

• Scaringe Robert J

Classifications

• H02J7/84

  Control of state of health [SOH] · CPC title

• H02J7/80

  including monitoring or indicating arrangements · CPC title

• H02J7/40

  characterised by the exchange of charge or discharge related data · CPC title

• H02J7/82

  Control of state of charge [SOC] · CPC title

• B60L53/80

  Exchanging energy storage elements, e.g. removable batteries · CPC title