Battery Deterioration Assessment Using Impedance Regression Models
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Solution Overview
Problem
Existing methods for evaluating the deterioration of secondary batteries, such as lithium ion batteries, lack accuracy in assessing the degree of deterioration.
Innovation Solution
A battery state determination device that utilizes multiple regression analysis using model parameters derived from reference secondary batteries to evaluate the degree of deterioration of target secondary batteries, incorporating complex impedance measurements and equivalent circuit models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods for evaluating battery deterioration are used, then the evaluation process is simple, but the accuracy of deterioration assessment is insufficient
Solution Approach 1:
The patent transforms the battery deterioration evaluation from direct voltage measurement to a parameter-based approach using impedance spectroscopy. Multiple frequency points are measured to obtain impedance parameters (real part, imaginary part, phase angle), which are then converted to equivalent circuit model parameters (resistance, capacitance). This parameter transformation enables more accurate deterioration assessment by capturing frequency-dependent battery characteristics that simple voltage measurements miss.
Solution Approach 2:
The patent introduces an equivalent circuit model as an intermediary between impedance measurements and deterioration evaluation. The measured impedance parameters are fitted to an equivalent circuit model (such as Randles circuit) to extract physical parameters like solution resistance, charge transfer resistance, and double-layer capacitance. These intermediate parameters provide a more accurate representation of battery degradation mechanisms than direct voltage measurements.
2Measurement precision
If multiple regression analysis with multiple model parameters is used, then the evaluation accuracy is improved, but the computational complexity increases
Solution Approach 1:
The patent performs preliminary fitting of impedance data to equivalent circuit models for multiple reference batteries before constructing the regression model. The model parameters (resistance, capacitance values) are pre-calculated and stored for each reference battery at different states of charge and temperature conditions. This preliminary action reduces the computational burden during actual evaluation, as only regression calculation against pre-computed parameters is needed rather than full impedance fitting.
Solution Approach 2:
The patent transforms the complex impedance spectrum into a smaller set of discrete model parameters through equivalent circuit fitting. Instead of using the entire frequency-range impedance data in regression analysis, the patent uses fitted parameters (typically 3-5 parameters per battery) as input variables. This parameter reduction maintains evaluation accuracy while significantly simplifying the regression computation.
Data Source
AI summary
A device is capable of evaluating the degree of deterioration of a secondary battery by executing regression analysis processing using, as a target variable, the degree of deterioration of the secondary battery. Multiple regression analysis is executed by using, as explanatory variables, respective values of plural model parameters that define a secondary battery model based on a measurement result of complex impedance of each reference secondary battery, and a degree of deterioration evaluated according to the secondary battery model as a target variable. Then, a degree of deterioration of a target secondary battery is evaluated according to a multiple regression equation obtained as a result of the multiple regression analysis.