Battery Model Parameter Tuning Across SOC and Temperature Ranges
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Solution Overview
Problem
Current battery state estimation methods, such as electric circuit and electrochemical models, face challenges in accurately optimizing battery model parameters, particularly for varying state of charge (SOC) intervals and temperature conditions, leading to suboptimal performance and reliability in battery management systems.
Innovation Solution
A battery model optimization device and method that iteratively adjusts parameter values by setting and refining boundary conditions based on voltage errors and diffusion characteristics, using a processor to determine optimized parameter values within predefined intervals, thereby improving the accuracy and efficiency of battery state estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional battery models (electric circuit or electrochemical) are used for state estimation, then the battery state can be estimated, but the accuracy is insufficient for varying SOC intervals and temperature conditions
Solution Approach 1:
The patent divides the battery operating range into multiple SOC intervals (e.g., 0-30%, 30-70%, 70-100%) and temperature ranges, creating separate optimized parameter sets for each segment. This segmentation allows the model to achieve high accuracy within each specific interval while maintaining overall adaptability across the full operating range.
Solution Approach 2:
The patent optimizes battery model parameters (such as diffusion coefficients, reaction rates, and thermal conductivities) specifically for each SOC interval and temperature condition. By changing parameters according to operating conditions rather than using fixed parameters, the model achieves both high accuracy and adaptability across varying conditions.
2Measurement precision
If comprehensive battery model optimization is performed for all conditions, then accuracy improves, but calculation time increases
Solution Approach 1:
The patent performs parameter optimization offline for each SOC interval and temperature condition beforehand, storing the optimized parameter sets. During actual battery operation, the system only needs to select the pre-computed parameters corresponding to current conditions, dramatically reducing real-time calculation time while maintaining high accuracy.
3Reliability
If detailed electrochemical models are used, then model accuracy improves, but device complexity increases
Solution Approach 1:
The patent applies different levels of model complexity and optimization detail to different SOC intervals and temperature conditions based on their specific requirements. For example, certain critical SOC ranges may use more detailed models while less critical ranges use simplified models, achieving high reliability where needed without unnecessary complexity elsewhere.
Data Source
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AI summary
A device with battery model optimization includes: a processor configured to perform optimization on a battery model for determining optimized parameter values of parameters of the battery model, wherein, to perform the optimization, the processor is configured to: select target parameters from among parameters of a battery model; set a current boundary condition for each of the target parameters; determine an optimized parameter value of each of the target parameters based on the set current boundary condition; set a subsequent boundary condition reduced from the current boundary condition based on the determined optimized parameter value; and determine a subsequent optimized parameter value of each of the target parameters based on the subsequent boundary condition.