Secondary Battery Lifetime Estimation Using Impedance Parameters
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Solution Overview
Problem
Existing methods for predicting the lifetime of lithium-ion secondary batteries are inaccurate due to individual differences and varying environmental conditions, leading to potential electric power shortages in electric vehicles, especially when multiple batteries with differing deterioration rates are connected.
Innovation Solution
A lifetime estimation system that includes a measuring unit, temperature sensing unit, and microcomputer using a nonlinear regression equation and neural network to calculate the predicted deterioration line of the secondary battery, considering factors like temperature, voltage, and cycle number, to accurately estimate capacity retention and detect abnormalities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional lifetime prediction methods are used, then the prediction process is simple, but the prediction accuracy is low due to individual differences and environmental variations
Solution Approach 1:
The patent transforms the lifetime prediction problem by changing parameters from direct capacity measurement to impedance spectrum analysis. By using equivalent circuit model parameters (R0, R1, C1, C2) derived from impedance measurements at different frequencies, the system achieves more sensitive and accurate degradation tracking that accounts for individual battery differences and environmental conditions without requiring complex full-capacity testing protocols
Solution Approach 2:
The patent replaces traditional electrochemical impedance spectroscopy (EIS) measurement systems with a simplified equivalent circuit model approach. Instead of using complex mechanical/electrochemical testing equipment to measure capacity degradation directly, the system uses electrical impedance measurements combined with circuit modeling to infer battery health, significantly reducing measurement system complexity while improving prediction accuracy through parameter-based analysis
2Quantity of substance
If multiple secondary batteries with different deterioration rates are connected, then the battery capacity increases, but the reliability decreases due to uneven deterioration and potential overcharge/overdischarge
Solution Approach 1:
The patent implements individualized lifetime prediction for each battery in the series connection using impedance-based equivalent circuit parameters. The system continuously monitors and predicts the remaining lifetime of each battery separately, providing feedback that enables the control system to manage charge/discharge cycles to prevent overcharge or overdischarge of any individual battery, thereby maintaining system reliability while utilizing multiple batteries with different deterioration rates
Solution Approach 2:
The patent segments the battery management approach by treating each battery in the series connection as an independent unit with its own degradation characteristics. Instead of managing the battery pack as a single homogeneous unit, the system divides management into individual battery-level predictions using separate equivalent circuit models for each cell, allowing customized monitoring and control strategies for batteries at different stages of deterioration
3Measurement precision
If the lifetime prediction does not account for environmental conditions, then the prediction model is simple, but the accuracy deteriorates when temperature and voltage change
Solution Approach 1:
The patent incorporates environmental parameters (temperature, voltage, charge/discharge rate) as variables in the equivalent circuit model. By making the model parameters (R0, R1, C1, C2) temperature-dependent and voltage-dependent, the system accurately reflects how environmental conditions affect battery impedance and degradation, achieving high prediction accuracy under varying conditions while maintaining model simplicity through the established equivalent circuit framework
Data Source
AI summary
An object is to predict a deterioration state of a secondary battery even in an environment where temperature and a charging voltage change. A lifetime estimation device of the secondary battery includes a measuring unit for measuring the capacity of the secondary battery in the full charging state; a temperature sensing unit for sensing the ambient temperature of the secondary battery; and a storage unit for storing a table of a proportional coefficient corresponding to temperature in advance, and a predicted deterioration line of the secondary battery is calculated with the use of a nonlinear regression equation approximated to a measured deterioration line obtained by the measuring unit. The lifetime estimation device may construct a lifetime estimation system with the use of a neural network.