IP Library Granted Patent US 12,313,691
Granted Patent B2
US 12,313,691 · App. 17/048,995 · Granted May 27, 2025

System and method for battery selection

Inventors: Zhihong Jin (Pewaukee, WI); Michael Thomas Ballo (Glendale, WI); Zhenli Zhang (Glendale, WI); Diego Hernan Diaz Martinez (Milwaukee, WI); Raul Jacinto Arredondo Cardenas (Brookfield, WI)
Assignee: CPS Technology Holdings LLC
G01R31/392B60L58/16G01R31/007G01R31/367G07C5/0808H01M10/4285H01M10/48B60K6/28B60Y2200/92H01M10/486H01M2220/20
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Quick Facts
Patent No.
US 12,313,691
App. No.
17/048,995
Granted
May 27, 2025
Kind
B2
Abstract

Disclosed is a vehicle comprising a vehicle system having a system having a number of loads defining a load profile; a validated battery comprising one or more batteries which can fulfill the load profile; an integrated battery selected from the validated battery, the integrated battery selected for longevity relative to other batteries; wherein the validated battery is provided within the vehicle. Further disclosed is a battery longevity predictor comprising a plurality of battery factors; a plurality of electrical load factors; a plurality of cycling or crank data; an output; wherein the output comprises a battery longevity predictor based on the plurality of battery factors, plurality of vehicle loads, and the plurality of cycling or crank data.

Claims (69)

1. A battery simulator for use with a vehicle having a vehicle control module, the battery simulator comprising:

a data input receiving data from the vehicle control module, the data including:

a plurality of battery factors including amperage hour throughput, depth of discharge, state of charge, peak current, and battery contribution to fuel economy;

a plurality of electrical load factors including driver factors and environmental factors, wherein the driver factors include driving patterns and driving context and wherein the environmental factors include ambient temperature, under vehicle hood temperature, humidity, road condition, and battery placement in vehicle; and

a plurality of cycling or crank data;

a processor, and

a memory operatively connected to the processor, the memory storing instructions that, when executed by the processor, cause the processor to use the plurality of battery factors, plurality of electrical load factors, and the plurality of cycling or crank data to create a vehicle simulation and performance analysis of the battery, and provide an output based on the vehicle simulation and performance analysis, the output comprising a battery recommendation or feedback to a user regarding battery longevity.

2. The battery simulator of claim 1 , comprising a plurality of influencing factors comprising vehicle data, automotive enhancements, and load management strategy used by the battery simulator.

3. The battery simulator of claim 2 , wherein the vehicle data includes vehicle type.

4. The battery simulator of claim 2 , wherein the load management strategy is a load profile comprising a vehicle load including size, user impact, load, and battery management system.

5. The battery simulator of claim 1 , wherein the plurality of electrical load factors is obtained from a general repository of electrical load factors.

6. The battery simulator of claim 1 , wherein the output is delivered at an interface at a point of sale or operational tool.

7. The battery simulator of claim 6 , wherein the interface is a display.

8. The battery simulator of claim 6 , wherein the operational tool is a business management tool for warranty planning.

9. A vehicle comprising:

a system having a number of loads defining a load profile;

a validated battery group comprising one or more batteries which can fulfill the load profile;

an integrated battery selected from the validated battery group, the integrated battery selected for longevity relative to other batteries; and

the integrated battery is provided for use with the vehicle.

10. The vehicle of claim 9 , wherein the load profile comprises battery factors including amperage hour throughput, depth of discharge, state of charge, peak current, battery size, and battery contribution to fuel economy.

11. The vehicle of claim 9 , wherein the load profile comprises environmental factors including ambient temperature, under vehicle hood temperature, humidity, road condition, and battery placement in vehicle.

12. The vehicle of claim 9 , wherein the load profile comprises driver factors including driving patterns and driving context.

13. The vehicle of claim 9 , wherein the load profile comprises vehicle loads including vehicle display, auto-park, autopilot, biometrics, navigation or global positioning system (GPS), and electrical devices.

14. A battery selector comprising:

a plurality of battery factors;

a plurality of electrical load factors comprising electrical demand factors, driver factors, and environmental factors, wherein the driver factors include driving patterns and driving context and wherein the environmental factors include ambient temperature, under vehicle hood temperature, humidity, road condition, and battery placement in vehicle;

a plurality of cycling or crank data;

a display;

a processor, and

a memory operatively connected to the processor, the memory storing instructions that, when executed by the processor, cause the processor to provide an output on the display, the output comprising a battery selection based on the plurality of battery factors, plurality of electrical load factors, and the plurality of cycling or crank data.

15. The battery selector of claim 14 , further comprising a battery simulator having the plurality of battery factors, the plurality of electrical load factors, and/or the plurality of cycling or crank data.

16. The battery selector of claim 15 , wherein the battery simulator is configured to use the plurality of battery factors, the plurality of electrical load factors, and the plurality of cycling or crank data to create a vehicle simulation and performance analysis of the battery and wherein the battery selection is further based on the vehicle simulation and performance analysis.

17. The battery selector of claim 14 , wherein the electrical load factors comprise electrical demand influencing factors.

18. The battery selector of claim 14 , wherein the driver factors include driver influencing factors.

19. The battery selector of claim 14 , wherein the plurality of electrical load factors includes an application obtained based on a user input.

20. A battery selector comprising:

a battery simulator having:

a plurality of battery factors, wherein the battery factors comprise amperage hour throughput, depth of discharge, state of charge, peak current and/or battery contribution to fuel economy;

a plurality of electrical load factors, wherein the electrical load factors comprise driver factors and environmental factors, wherein the driver factors comprise driving patterns and driving context and wherein the environmental factors include ambient temperature, under vehicle hood temperature, humidity, road condition, and battery placement in vehicle; and

a plurality of cycling or crank data;

a display,

a processor, and

a memory operatively connected to the processor, the memory storing instructions that, when executed by the processor, cause the processor to use the plurality of battery factors, the plurality of electrical load factors, and the plurality of cycling or crank data to create a vehicle simulation and performance analysis of the battery, and provide an output on the display, the output based on the vehicle simulation and performance analysis, the output comprising a battery recommendation or feedback to a user regarding battery longevity.

21. The battery selector of claim 20 , comprising a plurality of influencing factors comprising vehicle data, automotive enhancements, and load management strategy used by the battery simulator.

22. The battery selector of claim 21 , wherein the vehicle data includes vehicle type.

23. The battery selector of claim 21 , wherein the load management strategy is a load profile comprising a vehicle load, including size, user impact, load, and battery management system.

24. The battery selector of claim 20 , wherein plurality of electrical load factors is obtained from a general repository of electrical load factors.

25. The battery selector of claim 20 , wherein the output is delivered at an interface at a point of sale or operational tool.

26. The battery selector of claim 25 , wherein the operational tool is a business management tool for warranty planning.

27. The battery selector of claim 20 , further comprising a battery group, wherein the output includes one or more validated batteries selected from the battery group.

28. The battery selector of claim 27 , wherein the battery selector selects an integrated battery for use in a system from the one or more validated batteries.

29. A battery selector comprising:

a battery simulator for use with a vehicle having a vehicle control module, the battery simulator comprising:

a data input receiving data from the vehicle control module, the data including:

a plurality of battery factors including amperage hour throughput depth of discharge, state of charge, peak current, and battery contribution to fuel economy;

a plurality of electrical load factors including driver factors and environmental factors, wherein the driver factors include driving patterns and driving context and wherein the environmental factors include ambient temperature, under vehicle hood temperature, humidity, road condition, and battery placement in vehicle; and

a plurality of cycling or crank data;

a process; and

a memory operatively connected to the processor, the memory storing instructions that, when executed by the processor, cause the processor to use the plurality of battery factors, plurality of electrical load factors, and the plurality of cycling or crank data to create a vehicle simulation and performance analysis of the battery, and provide an output based on the vehicle simulation and performance analysis, the output comprising a battery recommendation or feedback to a user regarding battery longevity; and

wherein the battery selector is configured to select a battery from a battery group based on the output of the battery simulator.

30. A battery longevity predictor comprising:

a battery simulator for use with a vehicle having a vehicle control module, the battery simulator comprising:

a data input receiving data from the vehicle control module, the data including:

a plurality of battery factors including amperage hour throughput, depth of discharge, state of charge, peak current, and battery contribution to fuel economy;

a plurality of electrical load factors including driver factors and environmental factors, wherein the driver factors include driving patterns and driving context and wherein the environmental factors include ambient temperature, under vehicle hood temperature, humidity, road condition, and battery placement in vehicle; and

a plurality of cycling or crank data;

a processor; and

a memory operatively connected to the processor, the memory storing instructions that, when executed by the processor, cause the processor to use the plurality of battery factors, plurality of electrical load factors, and the plurality of cycling or crank data to create a vehicle simulation and performance analysis of the battery, and provide an output based on the vehicle simulation and performance analysis, the output comprising a battery recommendation or feedback to a user regarding battery longevity; and

wherein the battery longevity predictor is configured to provide a longevity prediction based on the output of the battery simulator.

Assignments (4)
ABL PATENT SECURITY AGREEMENT Recorded Jul 13, 2023
From: CLARIOS ADVANCED SOLUTIONS LLC; CPS TECHNOLOGY HOLDINGS LLC
To: CITIBANK, N.A., AS COLLATERAL AGENT
Reel/Frame 064272/0566 →
FIRST LIEN PATENT SECURITY AGREEMENT Recorded Jul 13, 2023
From: CLARIOS ADVANCED SOLUTIONS LLC; CPS TECHNOLOGY HOLDINGS LLC
To: CITIBANK, N.A., AS COLLATERAL AGENT
Reel/Frame 064272/0599 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 21, 2020
From: JOHNSON CONTROLS TECHNOLOGY COMPANY
To: CPS TECHNOLOGY HOLDINGS LLC
Reel/Frame 054159/0796 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 20, 2020
From: JIN, ZHIHONG H.; BALLO, MICHAEL THOMAS; ZHANG, ZHENLI; DIAZ MARTINEZ, DIEGO HERNAN; ARREDONDO CARDENAS, RAUL JACINTO
To: JOHNSON CONTROLS TECHNOLOGY COMPANY
Reel/Frame 054104/0158 →