Battery Capacity Estimation Using Adaptive Weighting
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Solution Overview
Problem
Existing battery management systems face challenges in accurately determining the capacity of lithium-ion battery cells, particularly due to measurement errors, which can lead to inaccurate residual capacity assessments and inefficient battery life monitoring.
Innovation Solution
A method that measures battery cell current and open circuit voltage at the beginning and end of a measurement period, calculates total battery cell current and states of charge, estimates capacity based on these values, and adjusts the capacity value using a weight factor that accounts for measurement errors, ensuring a monotonic relationship between the new and known capacity values to minimize errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If capacity measurement is performed frequently to improve accuracy, then measurement precision improves, but the capacity value becomes unstable due to high measurement errors
Solution Approach 1:
The patent applies dynamics by making the weighting between estimated capacity and measured capacity adaptive rather than fixed. The weighting factor dynamically adjusts based on the reliability assessment of each measurement, allowing the system to optimize between using recent measurements when they are reliable and relying on historical data when measurements are noisy. This resolves the contradiction by making the capacity estimation system flexible and context-aware.
Solution Approach 2:
The patent changes the parameter of capacity estimation from a direct measurement approach to a weighted combination approach, where the weighting parameter is adjusted based on measurement quality. By introducing a quality metric and using it to modulate the contribution of new measurements versus historical data, the system transforms a static estimation problem into a dynamic parameter optimization problem that resolves the accuracy-stability trade-off.
2Reliability
If capacity measurement is performed infrequently to maintain stability, then capacity value stability improves, but measurement precision deteriorates
Solution Approach 1:
The patent implements feedback by continuously assessing the quality of capacity measurements and using this quality information to adjust how much weight is given to new measurements versus historical data. The quality metric provides feedback about measurement reliability, and this feedback loops back to modify the estimation process, creating a closed-loop system that automatically adapts to measurement conditions and resolves the stability-precision contradiction.
Solution Approach 2:
The system dynamically adjusts the effective measurement frequency by varying the weighting factor based on quality assessments. When measurements are high quality, the system effectively uses them more frequently; when measurements are noisy, it reduces their frequency of influence. This dynamic adjustment resolves the contradiction between frequent measurement for precision and infrequent measurement for stability.
3Measurement precision
If weight factor is increased to emphasize estimated capacity, then capacity estimation accuracy improves, but responsiveness to actual capacity changes decreases
Solution Approach 1:
The patent makes the weight factor dynamic rather than static, allowing it to vary based on the quality of available measurements and the detected rate of capacity degradation. When capacity is degrading rapidly, the system increases responsiveness by adjusting the weight factor, while maintaining high accuracy when measurements are reliable. This dynamic weighting resolves the contradiction between accuracy and responsiveness.
Solution Approach 2:
The system changes the weighting parameter based on operational conditions and measurement quality, transforming a fixed trade-off into an adaptive parameter optimization. By monitoring capacity degradation trends and measurement reliability, the system adjusts the weight factor to maintain both accuracy and appropriate responsiveness to actual capacity changes.
Data Source
AI summary
The invention relates to a method for determining the capacity of a battery cell. A battery cell current I is measured during a measurement period, and an open terminal voltage UOCV1,UOCV2 of the battery cell is measured at the beginning and end of the measuring period. The method has the steps of ascertaining a total battery cell current Iges from the measured battery cell current I, ascertaining charge states SOC1, SOC2 at the beginning and end of the measurement period using the measured open terminal voltage UOCV1,UOCV2, ascertaining an estimated value of the capacity Qest using the total battery cell current Iges and a difference between the charge states SOC1, SOC2, ascertaining a total measurement error of the estimated value of the capacity Qest from measurement errors of the total battery cell current Iges and the charge states SOC1, SOC2, and ascertaining a new value of the capacity Qnew using a known value of the capacity Qact, the estimated value of the capacity Q, and the total measurement error. The new value of the capacity Qnew is in a monotonic relationship with the known value of the capacity Qact and the estimated value of the capacity Qest such that the new value of the capacity Qnew is determined more strongly from the estimated value of the capacity Qest in the case of at least one first value of the total measurement error than in the case of at least one second value of the total measurement error, said second value lying above the at least one first value, and the new value of the capacity Qnew is determined less strongly from the known value of the capacity Qest in the case of the first value of the value of the total measurement error than in the case of the second value of the total measurement error. The invention further relates to a computer program, a battery management system (2), and a motor vehicle which are designed to carry out the method.