Real-Time Battery SOC Correction via Voltage Feedback
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Solution Overview
Problem
Existing battery management systems face challenges in accurately estimating state-of-charge (SOC) and state-of-health (SOH) of lithium-ion batteries due to increased errors in Coulomb counting methods, especially with biased current measurements and instability at realistic drive cycles, and lack real-time correction mechanisms for ion concentration and SOC.
Innovation Solution
A method that estimates the average concentration of ions in battery electrodes using an unscented Kalman filter (UKF) to correct ion concentration based on differences in predicted and measured cell voltages, and adjusts Coulomb counting SOC accordingly, integrating real-time correction for improved accuracy during charging and discharging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If Coulomb counting method is used to estimate SOC, then the SOC estimation can be obtained in real time, but the estimation accuracy deteriorates over integration time due to biased current measurements and discretization errors
Solution Approach 1:
The patent implements a feedback mechanism where the estimated SOC from Coulomb counting is continuously corrected using voltage measurements. The open-circuit voltage (OCV) is measured and compared with the predicted voltage from the equivalent circuit model, and the SOC estimate is adjusted based on this voltage error feedback, thereby maintaining accuracy over time
Solution Approach 2:
The patent introduces an equivalent circuit model as an intermediary between the Coulomb counting method and the final SOC estimate. This model uses voltage measurements to provide corrective feedback, acting as a mediator that compensates for the accumulating errors in the direct Coulomb counting approach
2Device complexity
If simple Coulomb counting method is used for SOC prediction, then the system complexity is reduced, but the method becomes unstable at realistic drive cycles and lacks fault detection capability
Solution Approach 1:
The equivalent circuit model serves as an intermediary layer that adds minimal complexity while significantly improving reliability. It enables fault detection by comparing predicted and actual voltages, and provides stability correction without requiring complex computational resources
Solution Approach 2:
The patent replaces the purely electrical measurement approach with a hybrid method that incorporates electrochemical model-based voltage prediction. This substitution enables fault detection and stability improvement while maintaining computational efficiency
3Use of energy by moving object
If ion concentration estimation is performed without real-time correction, then the computational load is reduced, but the SOC estimation accuracy deteriorates due to model uncertainty and sensor errors
Solution Approach 1:
The patent implements a lightweight feedback mechanism using voltage measurements to correct ion concentration estimates. The OCV measurement provides feedback that is processed through the equivalent circuit model to adjust the SOC estimate, achieving accuracy improvement with minimal additional computational energy
Solution Approach 2:
The patent changes the approach from continuous complex state estimation to periodic voltage-based correction. By using OCV measurements at appropriate intervals and processing them through the equivalent circuit model, the system achieves accurate SOC estimation with reduced computational energy consumption
Data Source
AI summary
A method includes estimating an average concentration of ions in electrodes of a battery and estimating a state-of-charge (SOC) of the battery by Coulomb counting, correcting the ion concentration based on a difference in predicted and measured cell voltages, and correcting the Coulomb counting SOC based on a relation between SOC estimated by Coulomb counting and the average concentration, and the difference in the predicted and measured cell voltages.