Generic Battery Modeling for Real-Time Energy Storage Sizing
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Solution Overview
Problem
Current battery modeling methods, such as electrochemical and equivalent electric circuit models, are complex and impractical for real-time energy management in hybrid energy sources, as they require extensive data and computational resources, while empirical models lack accuracy without detailed data across various operating conditions.
Innovation Solution
A method involving empirical modeling of batteries by testing under different conditions, interpolating, and extrapolating results to create a generic battery model that predicts behavior and matches batteries to specific tasks, using techniques like linear point slope algorithms and polygonal approximations, implemented using tools like Matlab-Simulink for real-time operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electrochemical or equivalent electric circuit models are used for battery modeling, then measurement precision and reliability are improved, but device complexity and computational requirements increase significantly
Solution Approach 1:
The patent creates a simplified copy of the complex electrochemical model by using polynomial equations that replicate battery behavior without requiring the full electrochemical complexity. This allows accurate prediction of battery parameters while reducing computational burden and modeling complexity.
Solution Approach 2:
The patent transforms the complex electrochemical model into a simplified polynomial-based model by changing the mathematical parameters from differential equations to polynomial equations. This parameter transformation maintains prediction accuracy while significantly reducing computational complexity for real-time applications.
2Measurement precision
If detailed empirical data across various operating conditions is collected, then measurement precision improves, but loss of time and resources increase
Solution Approach 1:
The patent performs preliminary polynomial curve fitting during the offline model creation phase, storing the fitted parameters for later use. This preliminary action eliminates the need for extensive real-time data collection and processing, significantly reducing testing time while maintaining model accuracy.
Solution Approach 2:
The patent creates a simplified polynomial representation that copies the essential behavior patterns from limited empirical data. This polynomial copy captures battery characteristics across various operating conditions without requiring exhaustive testing at every possible condition, reducing time and resource requirements.
3Productivity
If real-time battery sizing and energy management is implemented, then productivity improves, but computational resources and device complexity increase
Solution Approach 1:
The patent replaces complex electrochemical calculations with polynomial equations that can be evaluated using simple arithmetic operations. This substitution enables real-time battery sizing and energy management computations to be performed efficiently with minimal computational resources, improving productivity without increasing device complexity.
Data Source
AI summary
A method of modeling a battery to match the battery to a task, the method comprises: selecting a battery, testing the battery for charge rate and discharge rate at different temperatures, collecting results; and interpolating in between and extrapolating around the collected results to produce a model of behavior of the battery and predict operating points, so that the battery may be sized and matched to given tasks.