Adaptive Battery SOC Estimation for Drift-Resistant Tracking
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Solution Overview
Problem
Traditional state-of-charge (SOC) estimation methods in energy storage systems, such as coulomb counting and model-based approaches, suffer from long-term drift and inaccuracies due to errors accumulation and model inaccuracies, which affect the reliability of SOC tracking with external physical behavior.
Innovation Solution
A method and device for SOC estimation in energy storage systems that combines current and voltage measurements to generate a model-based estimate, an aggregated estimate, and an adaptive estimate, using adaptation currents to correct for drift and measurement errors, ensuring accurate tracking with external physical behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional coulomb counting is used to estimate SOC, then the estimation can be continuously updated based on current measurements, but errors accumulate over time causing long-term drift
Solution Approach 1:
The patent implements feedback by comparing the model-based SOC estimate with the coulomb counting estimate and using the difference (error) to adaptively adjust the model parameters. This closed-loop feedback mechanism prevents error accumulation by continuously correcting the estimates based on the discrepancy between two methods, thereby maintaining long-term accuracy while preserving continuous updating capability.
Solution Approach 2:
The patent dynamically changes model parameters (such as resistance and capacitance values) based on operating conditions and error feedback. By adapting parameters rather than using fixed values, the system compensates for aging, temperature effects, and other factors that cause drift, thus maintaining measurement precision over time while allowing continuous updates.
2Reliability
If model-based approaches are used to estimate SOC, then the estimation can account for battery physics, but the stochastic nature prevents the SOC from tracking with external physical behavior
Solution Approach 1:
The patent merges two estimation approaches: model-based estimation (which captures physical behavior) and coulomb counting (which tracks external current measurements). By combining these methods and using their difference as feedback for adaptation, the system achieves both physical accuracy and tracking capability, resolving the contradiction between reliability and ease of operation.
Solution Approach 2:
The system performs self-calibration by using the error between model-based and coulomb counting estimates to automatically adjust model parameters. This self-service mechanism enables the model to adapt to actual battery behavior without external intervention, ensuring both physical accuracy and tracking capability are maintained simultaneously.
3Ease of operation
If an incorrect initial state-of-charge value is used in coulomb counting, then the estimation process can start, but the estimates consistently differ from the true value
Solution Approach 1:
The feedback mechanism compares model-based estimates (which are less sensitive to initial conditions) with coulomb counting estimates and uses the difference to correct for incorrect initial values. This continuous feedback allows the system to start with any initial value while progressively eliminating the consistent offset error, maintaining both ease of operation and measurement precision.
Data Source
AI summary
Systems, methods, and devices are provided for estimating a state-of-charge in an energy storage system. The systems, methods, and devices may measure a current and a voltage related to the energy storage system, generate a model-based state-of-charge estimate based thereon, generate an aggregated state-of-charge estimate based on the model-based state-of-charge estimate, generate an adaptation current based on the measured current, aggregated state-of-charge estimate, and the adaptive state-of-charge estimate, and update the adaptive state-of-charge estimate based on the measured current and the adaptation current. The systems, methods, and devices may also provide a tracking indication whether the adaptive state-of-charge estimate is tracking between upper and lower confidence limits.