Iterative SOC Estimation Using Kalman Filter and Low-Pass Filtering
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Solution Overview
Problem
Lithium ion batteries face challenges in determining the state of charge (SOC) in real-time due to internal resistance and the need for a relaxation period, which hinders accurate SOC measurements, especially when current is being drawn.
Innovation Solution
A method using a Kalman filter to iteratively determine the SOC of a battery cell by selecting the cell with the lowest measured voltage, applying a weighted correction factor based on voltage and current measurements, and updating error covariance to improve accuracy, with low-pass filtering to reduce noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional coulomb counting is used to determine SOC, then the method is simple to implement, but measurement precision deteriorates due to internal resistance and relaxation period requirements
Solution Approach 1:
The patent implements feedback by using the measured terminal voltage to correct the predicted SOC value iteratively. The correction factor is calculated based on the difference between measured and predicted terminal voltages, and this correction is fed back to update the SOC estimate in each iteration, improving measurement accuracy while maintaining a manageable algorithm structure
Solution Approach 2:
The patent applies preliminary action by pre-calculating and storing open-circuit voltage (OCV) lookup tables and hysteresis models before runtime. These pre-computed data structures enable the iterative algorithm to quickly access correction information without performing complex real-time calculations, thus improving measurement precision without proportionally increasing device complexity
2Speed
If SOC is determined during high current conditions, then real-time monitoring is achieved, but measurement precision deteriorates due to internal resistance effects
Solution Approach 1:
The patent introduces terminal voltage as an intermediary measurement that indirectly reflects SOC status. Instead of directly measuring SOC during high current conditions (which is inaccurate), the system uses terminal voltage as a mediator to infer SOC through the iterative correction process, enabling real-time monitoring while compensating for internal resistance effects
Solution Approach 2:
The patent replaces direct electrical measurement methods with a computational model-based approach. Instead of relying on direct voltage or current measurements that are affected by internal resistance, the system uses an iterative algorithm that substitutes physical measurement limitations with mathematical modeling and correction, achieving both real-time performance and accuracy
3Measurement precision
If iterative correction is applied to improve SOC accuracy, then measurement precision improves, but loss of time increases due to multiple iterations
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing OCV lookup tables and hysteresis characteristics before the iterative process begins. During runtime, the algorithm only needs to perform lookups and simple arithmetic operations rather than complex calculations, significantly reducing the time loss per iteration while maintaining high measurement precision
Solution Approach 2:
The patent implements partial action by performing a fixed number of iterations (e.g., 3-5 iterations) rather than continuing until convergence. This partial execution of the iterative process achieves sufficient accuracy for practical applications while limiting the time loss, balancing measurement precision with computational efficiency
Data Source
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AI summary
A method and system for iteratively determining state of charge (SOC) of a battery cell "selected cell" using a controller. For each of the iterations, the controller determines a predicted SOC of the selected cell (206); a predicted error covariance of the predicted SOC; and updates the predicted SOC and the predicted error covariance for use in subsequent iterations of the method (218, 220). The updated SOC is treated as the SOC of the selected cell for that iteration of the method. Cell voltage used to determine the updated SOC may be low-pass filtered prior to its use. When the selected cell is one of multiple cells in a battery pack, the selected cell may be selected to have the lowest SEV of the cells in the pack (306, 308). The error covariance may also vary directly with pack current magnitude to model inaccuracies that generally directly vary with current flow.