Battery Capacity Estimation Using Kalman Filter
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Solution Overview
Problem
Existing methods for estimating the capacity of electric batteries are either not robust, require extensive and costly data collection, or cannot be applied during normal use due to the need for complete discharge and charge cycles or calibrated signals.
Innovation Solution
A method using an electronic battery management device that estimates battery capacity by selecting measurement periods, measuring charge and state of charge variations, and applying a Kalman filter with a consensus criterion to provide a robust estimate, allowing for regular capacity estimation during normal use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complete discharge and charge cycles are used to measure battery capacity, then measurement accuracy is improved, but operation complexity and time consumption increase
Solution Approach 1:
The patent applies partial action by using partial discharge and charge cycles instead of complete cycles. The method performs capacity estimation during normal partial charging and discharging operations, selecting measurement periods that provide sufficient data without requiring full battery depletion or charging. This reduces operational complexity and time consumption while maintaining adequate measurement accuracy for capacity estimation.
2Measurement precision
If complete discharge and charge cycles are used to measure battery capacity, then measurement accuracy is improved, but time consumption increases
Solution Approach 1:
The patent uses partial discharge and charge cycles rather than complete cycles. By selecting appropriate measurement periods during normal battery operation that provide sufficient charge/discharge data, the method achieves adequate capacity estimation accuracy without the time penalty of waiting for complete cycles, thus reducing time consumption significantly.
3Ease of operation
If traditional estimation methods are used during normal battery use, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent implements feedback through the Kalman filter algorithm that continuously processes measurements of charge variations (ΔQ) and state of charge variations (ΔSOC) during normal battery operation. The filter uses the relationship between these measured variations to recursively update and refine the capacity estimation, providing accurate results while maintaining ease of operation during normal use without requiring special test conditions.
Data Source
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AI summary
This description relates to a method for estimating the capacity of an electric battery, implemented by an electronic battery management device, comprising the following steps: a) during a charging and/or discharging phase of the battery, selecting a plurality of measurement periods and, for each period, measuring the change in charge ΔQ and estimating the change in state of charge ΔSOC of the battery between the beginning and the end of the measurement period (201); and b) estimating the capacity of the battery using a Kalman filter from the values ΔQ and ΔSOC determined in step a).