Real-Time Battery SOC Calculation Using Dynamic Noise Adaptation
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Solution Overview
Problem
Existing methods for calculating the State Of Charge (SOC) of batteries are inaccurate due to unsuitable external error values in various environments, leading to errors in SOC calculation.
Innovation Solution
A real-time SOC calculation method using the Extended Kalman Filter, which measures current, voltage, temperature, and degradation, and sets a noise variable to optimize the external error, allowing for accurate SOC estimation by iteratively adjusting the error values within a predetermined range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If an external error value is arbitrarily set at the beginning for SOC calculation, then the calculation process is simple, but the SOC calculation accuracy deteriorates in various noise environments
Solution Approach 1:
The external error value is changed from a static arbitrarily set value to a dynamic value that is automatically adjusted based on the actual noise level detected during battery operation. The system dynamically adapts the error value to match the current environmental noise conditions, resolving the contradiction between simple initialization and accurate calculation in varying environments.
Solution Approach 2:
The system implements a feedback mechanism where the calculated SOC value is continuously compared with actual measurements, and the external error value is adjusted based on the detected noise level from this comparison. This feedback loop enables the system to automatically optimize the error value for accurate SOC calculation without arbitrary initial setting.
2Productivity
If a fixed external error value is used in Extended Kalman Filter, then the calculation is computationally efficient, but the SOC estimation accuracy deteriorates when noise characteristics change
Solution Approach 1:
The system performs preliminary detection of noise characteristics before executing the main SOC calculation. By detecting the noise level in advance and setting the external error value accordingly, the system prepares the optimal parameters for the Extended Kalman Filter, ensuring both computational efficiency and accurate estimation even when noise characteristics change during operation.
Solution Approach 2:
The external error value parameter in the Extended Kalman Filter is changed from a fixed constant to a variable that adapts to changing noise conditions. The system modifies this parameter based on detected noise characteristics, maintaining computational efficiency while improving reliability across different operating environments.
Data Source
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AI summary
According to an embodiment of the present invention, a method of calculating the SOC of a battery in real time includes a battery parameter measurement operation for measuring current, voltage, temperature, and degradation degree of battery, and a real-time SOC calculation operation for calculating the SOC of the battery in real time based on the measured battery parameter. The real-time SOC calculation operation calculates the SOC of the battery in real time using the Extended Kalman Filter.