Battery Pack SoH-Based Cell Selection for Usable Capacity Estimation
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Solution Overview
Problem
Existing battery management systems for electric vehicles face errors in estimating battery state and calculating current limits due to deviations in battery cell internal resistance and capacity, leading to reduced efficiency and stability, as they rely on a representative voltage that may not accurately represent the entire battery pack.
Innovation Solution
A battery management system that selects high-risk battery cells by calculating state information such as SoC and SoH for each cell, identifying cells likely to exceed operating voltage limits, and calculates the actual usable capacity of the battery pack using these selected cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a representative voltage is used to estimate battery state, then the system complexity is reduced, but the measurement precision of battery state estimation deteriorates
Solution Approach 1:
The battery pack is segmented into multiple battery cells, each monitored individually for voltage, SoC, and SoH. This segmentation allows precise identification of high-risk cells without requiring complex system-wide modeling, resolving the contradiction between simplicity and precision.
Solution Approach 2:
The system performs preliminary calculation of SoC and SoH for each battery cell before determining the current limit value. This preliminary action enables accurate identification of high-risk cells in advance, improving estimation precision while maintaining systematic simplicity.
2Reliability
If the battery state is estimated with high precision using individual cell data, then the reliability of battery management improves, but the device complexity increases
Solution Approach 1:
The system applies local quality monitoring by calculating SoC and SoH specifically for each battery cell based on its individual voltage characteristics. This localized approach improves reliability for high-risk cell identification without requiring complex system-wide analysis.
Solution Approach 2:
The system changes parameters by calculating both SoC (state of charge) and SoH (state of health) for each cell, then uses these parameter changes to identify high-risk cells. This parameter-based approach improves reliability while maintaining manageable system complexity through standardized calculations.
3Ease of operation
If current limit calculation is based on representative voltage, then the ease of operation is improved, but the productivity of battery charging/discharging is reduced
Solution Approach 1:
The system performs preliminary identification of high-risk battery cells using SoC and SoH calculations before determining the current limit value. This preliminary action enables efficient current limit setting that maximizes charging/discharging productivity while preventing cell deterioration.
Solution Approach 2:
The system uses parameter changes in SoC and SoH to identify high-risk cells, then determines the current limit value based on these changes. This approach improves productivity by enabling faster, more accurate current limit calculation compared to representative voltage methods.
Data Source
AI summary
Provided are a battery management system and a battery management method using the same. According to the present invention, it is possible to select high-risk battery cells that are highly likely to be out of an operating voltage range by applying a change amount according to SoH for each of the battery cells to each SoC for each of the battery cells, and calculate the representative SoH of the battery pack based on the selected high-risk battery cells, and then calculate the actual usable capacity of the battery pack.