Battery SoP Prediction Using Nested ECM Control Loops
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Solution Overview
Problem
Existing battery management systems (BMS) face inaccuracies in predicting battery State-of-Power (SoP), leading to potential current and voltage overshoot and excessive wear due to overestimation or underestimation of power limits.
Innovation Solution
A device employing nested control loops, including an inner and outer control loop, uses an equivalent circuit model (ECM) to predict maximum current and voltage within predefined intervals, updating the ECM based on voltage and current errors to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conservative power limits are set with sufficient margins to ensure cell current and voltage limits are not violated, then reliability is improved, but power output is reduced
Solution Approach 1:
The system implements a feedback mechanism where predicted cell voltage errors are continuously monitored and used to adjust the equivalent circuit model parameters. This closed-loop approach allows the BMS to adapt power limits based on actual battery behavior, ensuring reliability while maximizing power output by eliminating excessive conservative margins.
Solution Approach 2:
The system dynamically changes parameters of the equivalent circuit model based on predicted voltage errors. By adjusting model parameters rather than using fixed conservative limits, the system can accurately predict maximum current and power output while ensuring cell limits are not violated, thus resolving the contradiction between reliability and power output.
2Power
If adaptive SoP-prediction algorithms are used to minimize predicted cell voltage error by tuning parameters, then power output is improved, but measurement precision deteriorates due to overestimation and underestimation
Solution Approach 1:
The system employs a nested structure where an inner control loop handles voltage error correction and an outer control loop handles current error correction. This hierarchical nesting allows the system to address multiple sources of prediction error systematically, improving both power output and measurement precision by correcting errors at different control levels.
Solution Approach 2:
The system performs preliminary corrections to the equivalent circuit model using predicted voltage errors before final current and power calculations are made. By pre-adjusting model parameters based on voltage predictions, the system eliminates subsequent overestimation and underestimation errors, thereby improving measurement precision while maintaining high power output.
3Device complexity
If a single control loop is used for SoP prediction, then device complexity is reduced, but measurement precision is insufficient due to inability to correct both voltage and current errors
Solution Approach 1:
The control system is segmented into distinct inner and outer control loops, each responsible for specific error corrections. The inner loop corrects voltage prediction errors while the outer loop corrects current prediction errors. This segmentation allows comprehensive error correction that would be impossible in a single control loop, significantly improving measurement precision without creating an unmanageably complex system.
Data Source
AI summary
A device for State-of-Power prediction is provided. The device implements an inner and outer control loop. In the inner loop, an equivalent circuit model is used to predict a maximum allowed current so as not to go beyond a predefined voltage limit at an end of a predefined time period/interval. A voltage error between the predefined voltage limit and an actual voltage at the end of the time interval is used to update the ECM. In the outer loop, a current error between the maximum allowed current and an actual current at the end of the interval is used to update the same ECM. The ECM is used to predict future voltage, that together with the maximum allowed current is used to determine a maximum power for the interval.