Battery SOH Estimation Using Nonlinear Deterioration Modeling
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Solution Overview
Problem
Conventional battery state of health (SOH) estimation methods fail to accurately account for various factors affecting battery deterioration, such as negative electrode side reactions, positive electrode side reactions, and transition metal dissolution, leading to inconsistencies in estimating the battery's state.
Innovation Solution
A battery SOH estimating apparatus and method that calculates deterioration information from battery information, reference information, and acceleration information using a non-linear estimation model, specifically employing a non-linear Kalman filter to consider non-linear factors like electrode side reactions and transition metal dissolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional SOH estimation methods are used, then the estimation process is simple, but the accuracy is insufficient due to inability to account for non-linear deterioration factors
Solution Approach 1:
The estimation process is divided into two independent parts: a linear estimation model for reference SOH calculation and a non-linear estimation model for corrected SOH calculation. This segmentation allows the system to handle complex non-linear deterioration factors separately from basic linear relationships, improving accuracy without overwhelming complexity in a single model.
Solution Approach 2:
The system changes the estimation parameter from simple capacity-based linear models to non-linear models that incorporate acceleration information and temperature-dependent criteria. By transforming the parameter space to include these additional dimensions, the model can accurately capture non-linear deterioration behaviors while maintaining computational feasibility.
2Loss of information
If conventional capacity-based estimation is used, then the calculation is straightforward, but the ability to identify deterioration factors is limited
Solution Approach 1:
Acceleration information serves as an intermediary parameter that bridges the gap between simple capacity measurements and complex deterioration mechanisms. By introducing this intermediate variable that captures the rate of change and its acceleration, the system can identify deterioration factors without directly measuring complex electrochemical processes.
Solution Approach 2:
The system replaces direct electrochemical measurement with a computational approach using non-linear estimation models. Instead of physically measuring deterioration factors, the system substitutes a mathematical model that processes available data (voltage, current, temperature, SOC) to infer deterioration information, achieving the same goal with simpler, more practical measurements.
3Reliability
If single-model estimation is used, then the system is simple, but the residual value varies due to inability to handle non-linear factors
Solution Approach 1:
The system merges the outputs of two estimation models (linear and non-linear) to produce a final corrected SOH value. The non-linear model's corrected SOH is combined with the linear model's reference SOH, allowing the system to benefit from both simple baseline estimation and complex factor correction, thereby improving reliability without relying on a single overly complex model.
Data Source
AI summary
A battery SOH estimating apparatus includes a battery information obtaining unit configured to obtain battery information including at least one of voltage, current, temperature, and SOC; and a control unit configured to calculate deterioration information for the battery from the battery information, preset reference information and preset acceleration information based on a preset deterioration model, and estimate SOH for the battery from the deterioration information based on a preset non-linear estimation model.