Systems and methods for optimizing component placement in a battery design

• US 10,318,656 B2
• Filed: 04/26/2016
• Issued: 06/11/2019
• Est. Priority Date: 04/26/2016
• Status: Active Grant

• Current Assignee: The Boeing Co.
• Original Assignee: The Boeing Co.
• Inventors: Cox, Kelsea, Kang, Laura S., Hall, David E., Dominguez, Vincent O., Coates, Dwaine K.
• Primary Examiner(s): Ho, Andy
• Application Number:
  US15/138,815
• Publication Number:
  US 20170308623A1
• Time in Patent Office: 1,141 Days
• Field of Search: 703 2, 703 1
• CPC Class Codes: G06F 17/11 for solving equations , e.g. nonlinear equations, general mathematical optimization problems optimization specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06F 2111/04 Constraint-based CAD
• CPC Class Codes: G06F 2111/06 Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA]
• CPC Class Codes: G06F 30/00 Computer-aided design [CAD]
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: H01M 10/04 Construction or manufacture in general H01M10/058, H01M10/12, H01M10/28, H01M10/38 take precedence
• CPC Class Codes: Y02E 60/10 Energy storage using batteries
• CPC Class Codes: Y02P 70/50 Manufacturing or production processes characterised by the final manufactured product

Abstract

Systems, computer readable media, and method concern determining operational parameters of an inventory of components to be included in a battery. The components can include storage components and electrical components. The method includes generating a system of equations that describe suitable combinations of components in locations in a battery design layout for the battery, the system of equations being generated based at least partially on rules and constraints, and includes analyzing the system of equations using integer optimization. The integer optimization can optimizes, based at least partially on the operational parameters, one or more objective functions in the system of equations to determine at least one solution for the battery design layout, and the at least one solution can include a set of the components for the locations in the battery design layout for the battery. The method includes providing, via an interface, the at least one solution.

Claims

1. A method, comprising:

determining operational parameters of an inventory of components to be included in a battery, wherein the components include storage components and electrical components;

generating a system of equations that describe suitable combinations of components in locations in a battery design layout for the battery, the system of equations being generated based at least partially on rules and constraints, wherein the generating further comprises receiving, for a user, at least one of an optimality gap for a solution that provides for a margin by which the solution for the battery is within a predetermined percentage of optimal or a time limit of optimization, wherein integer optimization optimizes one or more objective functions within the optimality gap or until the time limit has been reached;

analyzing the system of equations using integer optimization,

wherein the integer optimization optimizes, based at least partially on the operational parameters, one or more objective functions in the system of equations to determine at least one solution for the battery design layout,

wherein the at least one solution comprises a set of the components for the locations in the battery design layout for the battery

providing, via an interface, the at least one solution to the user; and

testing, by a battery testing equipment, the battery based on the battery design layout under operating conditions.

2. The method of claim 1, wherein the battery design layout of the battery comprises a partial set of the components to be included in the battery.

3. The method of claim 1, wherein the one or more objective functions comprise minimizing difference in capacity of virtual cells in the battery, minimizing difference in impedance of a module comprising the virtual cells, and minimizing difference in impedance in the virtual cells.

4. The method of claim 1, wherein the rules and constraints comprise a constraint that an individual component in the components only being used at one location in the locations in the battery design layout for the battery and each location is populated with exactly one combination of one or more individual components.

5. The method of claim 1, wherein the operational parameters comprise capacity of the components, impedance of the components, voltage of the components, and current of the components.

6. The method of claim 1, wherein the storage components comprise a plurality of one or more of lithium ion (Li-ion) cells, nickel cadmium (NiCad) cells, and nickel metal hydride (NiMh) cells, and wherein the electrical components comprise include a plurality of one or more of fuses, pass transistors, diodes, thermosensors, and an indicator.

7. A system, comprising:

one or more memory devices storing instructions; and

one or more processors coupled to the one or more memory devices and configured to execute the instructions to perform a method comprising;

determining operational parameters of an inventory of components to be included in a battery, wherein the components include storage components and electrical components;

generating a system of equations that describe suitable combinations of components in locations in a battery design layout for the battery, the system of equations being generated based at least partially on rules and constraints, wherein the generating further comprises receiving, for a user, at least one of an optimality clap for a solution that provides for a margin by which the solution for the battery is within a predetermined percentage of optimal or a time limit of optimization, wherein integer optimization optimizes one or more objective functions within the optimality gap or until the time limit has been reached;

analyzing the system of equations using integer optimization,

wherein the integer optimization optimizes, based at least partially on the operational parameters, one or more objective functions in the system of equations to determine at least one solution for the battery design layout, and

wherein the at least one solution comprises a set of the components for the locations in the battery design layout for the battery; and

providing, via an interface, the at least one solution to the user; and

testing, by a battery testing equipment, the battery based on the battery design layout under operating conditions.

8. The system of claim 7, wherein the battery design layout of the battery comprises a partial set of the components to be included in the battery.

9. The system of claim 7, wherein the one or more objective functions comprise minimizing difference in capacity of virtual cells in the battery, minimizing difference in impedance of a module comprising the virtual cells, and minimizing difference in impedance in the virtual cells.

10. The system of claim 7, wherein the rules and constraints comprise a constraint that an individual component in the components only being used at one location in the locations in the battery design layout for the battery and each location is populated with exactly one combination of one or more individual components.

11. The system of claim 7, wherein the operational parameters comprise capacity of the components, impedance of the components, voltage of the components, and current of the components.

12. The system of claim 7, wherein the storage components comprise a plurality of one or more of lithium ion (Li-ion) cells, nickel cadmium (NiCad) cells, and nickel metal hydride (NiMh) cells, and wherein the electrical components comprise include a plurality of one or more of fuses, pass transistors, diodes, thermosensors, and an indicator.

13. A non-transitory computer readable medium storing instructions for causing one or more processors to perform a method, the method comprising:

determining operational parameters of an inventory of components to be included in a battery, wherein the components include storage components and electrical components;

generating a system of equations that describe suitable combinations of components in locations in a battery design layout for the battery, the system of equations being generated based at least partially on rules and constraints, wherein the generating further comprises receiving, for a user, at least one of an optimality gap for a solution that provides for a margin by which the solution for the battery is within a predetermined percentage of optimal or a time limit of optimization, wherein integer optimization optimizes one or more objective functions within the optimality gap or until the time limit has been reached;

analyzing the system of equations using integer optimization,

wherein the integer optimization optimizes, based at least partially on the operational parameters, one or more objective functions in the system of equations to determine at least one solution for the battery design layout, and

wherein the at least one solution comprises a set of the components for the locations in the battery design layout for the battery; and

providing, via an interface, the at least one solution to the user; and

testing the battery based on the battery design layout under operating conditions.

14. The non-transitory computer readable medium of claim 13, wherein the battery design layout of the battery comprises a partial set of the components to be included in the battery.

15. The non-transitory computer readable medium of claim 13, wherein the one or more objective functions comprise minimizing difference in capacity of virtual cells in the battery, minimizing difference in impedance of a module comprising the virtual cells, and minimizing difference in impedance in the virtual cells.

16. The non-transitory computer readable medium of claim 13, wherein the rules and constraints comprise a constraint that an individual component in the components only being used at one location in the locations in the battery design layout for the battery and each location is populated with exactly one combination of one or more individual components.

17. The non-transitory computer readable medium of claim 13, wherein the operational parameters comprise capacity of the components, impedance of the components, voltage of the components, and current of the components.