Improvement of the safety and reliability of the Lithium-ion (Li-ion) battery operation is one of the key tasks for advanced Battery Management Systems (BMSs). It is critical for BMSs to be able to diagnose battery electrochemical faults that can potentially lead to catastrophic failures. In this paper, an observer-based fault diagnosis scheme is presented that can detect, isolate and estimate some internal electrochemical faults. The scheme uses a reduced-order electrochemical-thermal model for a Li-ion battery cell. The paper first presents a modeling framework where the electrochemical faults are modeled as parametric faults. Then, multiple sliding mode observers are incorporated in the diagnostic scheme. The design and selection of the observer gains as well as the convergence of the observers are verified theoretically via Lyapunov’s direct method. Finally, the performance of the observer-based diagnostic scheme is illustrated via simulation studies.
- Dynamic Systems and Control Division
A Diagnostic Scheme for Detection, Isolation and Estimation of Electrochemical Faults in Lithium-Ion Cells
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Dey, S, & Ayalew, B. "A Diagnostic Scheme for Detection, Isolation and Estimation of Electrochemical Faults in Lithium-Ion Cells." Proceedings of the ASME 2015 Dynamic Systems and Control Conference. Volume 1: Adaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2: Hybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems. Columbus, Ohio, USA. October 28–30, 2015. V001T13A001. ASME. https://doi.org/10.1115/DSCC2015-9699
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