Battery Component Placement Optimization via Integer Programming
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Solution Overview
Problem
Large-scale batteries composed of modular sub-units face performance variability due to individual cell and component differences, affecting overall battery performance.
Innovation Solution
A method and system that determine operational parameters of storage and electrical components, generate equations based on rules and constraints, and use integer optimization to optimize component placement in a battery design layout, providing a solution set for optimal battery configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If large-scale batteries are constructed using hundreds or thousands of individual COTS battery cells in modular sub-units, then the battery capacity and power requirements can be met, but performance variability arises due to differences in individual cell and component performance
Solution Approach 1:
The patent applies local quality by creating heterogeneous groups of battery cells where each group has specific performance characteristics tailored to its position and function within the battery assembly. Instead of treating all cells uniformly, the system assigns cells with different operational parameters to different locations based on their individual characteristics, thereby optimizing overall battery performance while accommodating variability among individual cells
Solution Approach 2:
The patent utilizes parameter changes by measuring and utilizing the operational parameters of individual battery cells (such as capacity, impedance, voltage) to determine their optimal placement within the battery assembly. The system transforms the variability in cell parameters from a problem into a solution by using these parameter differences to create balanced groups that achieve consistent overall battery performance
2Reliability
If integer optimization is used to determine optimal component placement and combinations, then battery performance and efficiency are improved, but computational complexity and processing requirements increase
Solution Approach 1:
The patent applies segmentation by dividing the battery assembly into multiple modular sub-units, each containing a specific number and configuration of battery cells. This segmentation allows the optimization problem to be broken down into smaller, more manageable subsets that can be solved independently or in a hierarchical manner, reducing the overall computational complexity while still achieving optimal performance
Solution Approach 2:
The patent implements preliminary action by pre-measuring and cataloging the operational parameters of individual battery cells before assembly. This advance characterization allows the optimization algorithm to work with pre-processed data rather than raw measurements, reducing computational burden during the optimization phase while ensuring accurate placement decisions
Data Source
AI summary
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.