Dynamic SOC Estimation Algorithm Switching for Battery Accuracy
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Solution Overview
Problem
Existing battery management systems face inaccuracies in estimating the state of charge (SOC) due to errors in current measurement and voltage variations during charging and discharging, which affect the accuracy of SOC estimation.
Innovation Solution
An apparatus and method that analyze the input/output power pattern of a battery over a predetermined time to determine its current application status, using either the Extended Kalman Filter (EKF) SOC estimation algorithm for high depth of discharge or the Smart SOC Moving Estimation (SSME) algorithm when the depth of discharge is low, and includes a current sensor checking unit to switch to SSME if the current sensor is absent or malfunctioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If current accumulation method is used to estimate SOC, then the method is simple to implement, but measurement errors are continuously accumulated reducing accuracy over time
Solution Approach 1:
The system dynamically switches between different SOC estimation algorithms (current accumulation method and voltage-based method) based on real-time operating conditions such as charging/discharging states and load conditions, rather than using a single static method. This dynamic adaptation resolves the contradiction by using the simple current accumulation method when appropriate while switching to more accurate voltage-based methods when errors would accumulate.
Solution Approach 2:
The system changes the estimation parameter from current-based accumulation to voltage-based estimation (OCV mapping) depending on the battery's operational state. By monitoring parameters like current magnitude, voltage stability, and charging/discharging status, the system selects the most appropriate parameter for accurate SOC estimation in each specific condition, preventing error accumulation while maintaining implementation feasibility.
2Measurement precision
If voltage measurement method is used to estimate SOC, then the method avoids current measurement errors, but voltage varies significantly during charging/discharging reducing accuracy
Solution Approach 1:
The system dynamically determines the appropriate estimation method based on real-time voltage characteristics. When voltage is stable (indicating the battery is not under heavy load or rapid charging/discharging), the system uses voltage-based SOC estimation. When voltage fluctuates significantly, the system switches to current accumulation or other methods, thus resolving the contradiction between voltage method's potential accuracy and its reliability under varying conditions.
Solution Approach 2:
The system performs preliminary assessment of voltage stability and operating conditions before selecting the estimation method. By evaluating whether the battery is in a steady state suitable for voltage-based estimation, the system proactively chooses the appropriate method, preventing accuracy degradation from using voltage measurement during unsuitable conditions while still benefiting from voltage-based estimation when reliable.
3Ease of operation
If a single SOC estimation algorithm is used, then the system is simple to operate, but accuracy decreases under varying battery conditions
Solution Approach 1:
The system implements dynamic algorithm selection that automatically adapts to varying battery conditions such as charging state, discharge rate, temperature, and load characteristics. The controller monitors multiple parameters and switches between current accumulation method, voltage-based OCV mapping, and hybrid methods based on real-time conditions, maintaining high accuracy across diverse operating scenarios while presenting a unified simple interface to users.
Solution Approach 2:
The SOC estimation system is designed with multi-functionality, incorporating multiple estimation algorithms (current accumulation, voltage-based estimation, and their combinations) within a single unified system. This universal approach allows the system to handle various battery conditions, charging/discharging rates, and operational states using the most appropriate algorithm for each situation, achieving both operational simplicity and high accuracy under varying conditions.
Data Source
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AI summary
Provided are battery SOC estimating apparatus and method. The battery SOC estimating apparatus according to the present invention includes an input/output power pattern analyzing unit which analyzes an input/output power of a battery during a predetermined time to obtain an input/output power pattern of the battery; an application status determining unit which analyzes the input/output power pattern of the battery to determine a current application status of the battery; and an SOC calculating unit which calculates an SOC of the battery using a state of charging (SOC) estimation algorithm corresponding to the current application status of the battery.