Secondary Battery Deterioration Estimation Using Voltage Change Sections
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Solution Overview
Problem
The accuracy of state of health (SOH) estimation for secondary batteries is compromised when the state of charge (SOC) is included as an estimation value in input data, leading to decreased estimation accuracy.
Innovation Solution
A deterioration state estimation system that measures state variables such as output current and voltage, preprocesses data by setting sections based on charge/discharge amounts and calculating voltage changes, and uses a trained model to estimate battery deterioration, incorporating techniques like recurrent neural networks (RNNs) and long/short-term memory (LSTM) for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If SOC estimation value is included in input data for SOH estimation, then the model can operate continuously, but the accuracy of SOH estimation decreases
Solution Approach 1:
The patent extracts and removes the SOC estimation value from the input data to eliminate the source of accuracy degradation. By separating the SOC estimation function from the SOH estimation function and using only measured state variables (current, voltage, temperature) as input, the system maintains continuous operation while improving SOH estimation accuracy.
Solution Approach 2:
The patent introduces an intermediary approach by using a dedicated SOC estimation module that operates independently from the SOH estimation model. This intermediary SOC module provides accurate SOC values through separate measurement and calculation mechanisms, which are then used as input to the SOH estimation model without compromising accuracy.
2Measurement precision
If section data based on charge/discharge and voltage changes is incorporated, then estimation accuracy improves, but data processing complexity increases
Solution Approach 1:
The patent segments the data processing into distinct sections: state variable measurement, section definition (large amount/small amount charge-discharge sections), voltage change calculation, and model input preparation. This segmentation allows complex processing to be broken down into manageable steps, improving accuracy while maintaining systematic control over processing complexity.
Solution Approach 2:
The patent changes the parameters used for data processing by introducing charge/discharge amount thresholds (large amount vs. small amount sections) and calculating voltage changes specific to these sections. This parameter transformation enhances the informative content of the input data, improving estimation accuracy while keeping the processing methodology systematic and controlled.
Data Source
AI summary
A deterioration state estimation system of a secondary battery includes: a state variable measurement unit which measures a state variable including an output current and an output voltage of the secondary battery in operation at each prescribed timing; a preprocessing unit which outputs input data calculated on the basis of the measured state variable; and a deterioration state estimation unit which estimates a deterioration state of the secondary battery in operation through a trained deterioration state model using the input data, wherein the preprocessing unit includes a state variable processing unit which sets a unit amount of charge/discharge and a most recent section closest to a current time and one or more previous sections before the most recent section as a desired section based on the unit amount of charge/discharge used for calculating the input data, calculates, as section data, an amount of voltage change based on the state variable for each set section, includes the calculated section data in the input data, and outputs the input data.