Lithium Battery Parameter Identification Using Capacity Change Rate
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Solution Overview
Problem
Conventional methods for identifying electrochemical model parameters of lithium batteries face accuracy issues due to the difficulty in maintaining constant current operating conditions, leading to lower data accuracy and unreliable parameter identification.
Innovation Solution
A method and system that utilize capacity change rate to improve parameter identification accuracy by acquiring and cleaning actual operating data, generating simulated data sets, and adjusting parameters based on convergence coefficients and loss functions to align with actual battery conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If constant current operating conditions are used for parameter identification, then the identification process is simple, but data accuracy deteriorates because actual battery operation rarely maintains constant current conditions
Solution Approach 1:
The patent changes the operating condition parameter from constant current to capacity change rate-based dynamic conditions. By using capacity change rate as the controlling parameter and adjusting operating conditions dynamically during identification, the method achieves both operational simplicity and high data accuracy that reflects actual battery behavior.
Solution Approach 2:
The patent implements feedback by continuously monitoring capacity change rate during battery operation and using this information to guide the parameter identification process. The capacity change rate serves as a feedback signal that adjusts the identification methodology to match actual operating conditions, thereby improving data accuracy.
2Measurement precision
If actual operating data is used for parameter identification, then data accuracy improves, but data cleaning and processing complexity increases
Solution Approach 1:
The patent extracts the capacity change rate parameter from the complex actual operating data, using it as a key filtering and selection criterion. By focusing on data points where capacity change rate meets specific criteria, the method simplifies the data cleaning process while maintaining high data accuracy for parameter identification.
Solution Approach 2:
The capacity change rate acts as an intermediary parameter that bridges actual operating data and parameter identification. Instead of directly processing complex multi-parameter operating data, the method uses capacity change rate as an intermediate filter that simplifies data selection and processing while preserving essential information for accurate parameter identification.
3Loss of time
If single piece of cleaned data is used for parameter identification, then processing time is reduced, but parameter identification accuracy deteriorates
Solution Approach 1:
The patent applies partial action by using capacity change rate constraints to selectively process only the most relevant portions of operating data. Instead of processing all available data, the method identifies and processes data segments where capacity change rate meets identification criteria, achieving sufficient accuracy with reduced processing time.
Data Source
AI summary
The invention provides a method and system for identifying electrochemical model parameters based on capacity change rate. The method includes: acquiring operating data from an actual operation process of a lithium battery and cleaning an actual operating data set from the operating data; generating a simulated operating data set through simulation of a preset electrochemical model; performing parameter identification based on a preset first loss function, the actual operating data set, and the simulated operating data set; calculating capacity convergence coefficient; comparing capacity convergence coefficient with a preset convergence threshold value; when greater than the preset convergence threshold value, regenerating the simulated operating data set; and when not greater than the preset convergence threshold value, outputting an electrochemical model parameter set as a parameter identification result. The invention introduces capacity change rate into the parameter identification process for lithium battery electrochemical models, improving accuracy of parameter identification.