Battery SOC Calibration Using OCV Mapping and Error Feedback
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Solution Overview
Problem
Existing methods for estimating the state of charge (SOC) of batteries, particularly lithium iron phosphate batteries, face challenges in real-time accuracy due to the voltage-SOC estimation method's limitations and the current integration method's reliance on accurate initial values, which can be affected by measurement errors and require cumbersome full charging calibration processes.
Innovation Solution
A battery system that calibrates the initial SOC value using accumulated data without full charging, by storing mapping data of SOC and open circuit voltages, estimating relationships, calculating error values, and determining calibration based on a cost function to ensure the error falls within a predetermined range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the voltage-SOC estimation method is used to estimate SOC by measuring open circuit voltage, then the estimation process is simple, but accurate real-time estimation is difficult because current remains in the battery after cutoff requiring pause time
Solution Approach 1:
The patent applies preliminary action by pre-storing multiple SOC-OCV relationship graphs for different temperature conditions before actual SOC estimation is needed. When estimating SOC, the system selects the appropriate pre-stored graph based on current temperature, eliminating the need for time-consuming pause periods and enabling immediate accurate estimation without requiring the battery to be in a complete rest state.
2Measurement precision
If the current integration method is used to estimate SOC, then real-time estimation is possible, but measurement errors of current sensor and ADC errors accumulate continuously during estimation
Solution Approach 1:
The patent implements feedback by continuously monitoring the difference between SOC values estimated from current integration and those derived from OCV measurements. When the deviation exceeds a threshold, the system triggers a calibration process that uses the OCV-based estimation to correct the accumulated errors in the current integration method, thereby maintaining long-term accuracy without requiring full battery charging cycles.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting the initial SOC value based on temperature-dependent SOC-OCV relationships. Instead of using a fixed initial value, the system selects initial values from pre-stored tables corresponding to different temperature conditions, which compensates for error accumulation and maintains estimation accuracy over extended operation periods.
3Measurement precision
If full charge control signal is transmitted to BMS at intervals to calibrate initial SOC value, then SOC calibration is achieved, but the process is cumbersome and requires frequent full charging
Solution Approach 1:
The patent applies partial action by using only the necessary portion of the full charging process for calibration purposes. Instead of requiring complete full charging cycles, the system performs partial charging followed by OCV measurement and calibration when SOC deviation thresholds are exceeded. This reduces the calibration frequency and duration while maintaining accuracy, eliminating the need for cumbersome periodic full charging.
4Productivity
If SOC estimation relies on initial SOC value in current integration method, then estimation can proceed, but errors occur when initial value is not accurate and accuracy decreases as runtime increases
Solution Approach 1:
The patent applies parameter changes by making the initial SOC value dynamic rather than fixed. The system stores multiple initial SOC values in tables corresponding to different temperature conditions and selects the appropriate initial value based on current temperature. This temperature compensation approach prevents error accumulation and maintains estimation accuracy over extended runtime without sacrificing the ability to continue estimation continuously.
Data Source
AI summary
A battery system includes: a storage that stores, at each predetermined storage period, mapping data that map an SOC and a first open voltage; and a controller that performs: when a number of times of storing the mapping data reaches a predetermined reference number of times so that a calibration period arrives, estimating a first relationship graph between a plurality of SOCs and a plurality of open circuit voltages; calculating a plurality of relationship graphs by reflecting a plurality of preset error values in the first relationship graph; calculating a summed value of distances between each of the plurality of relationship graphs and the mapping data; determining an error value corresponding to a minimum value among a plurality of summed values to be a final error value; and determining whether the final error value falls within a predetermined reference range, to determine whether to calibrate an initial SOC value.