Lyapunov-Based Thermal Fault Diagnosis of Cylindrical Lithium-Ion Batteries

• Published in: IEEE transactions on industrial electronics (1982) Vol. 67; no. 6; pp. 4670 - 4679
• Main Authors: Wei, Jingwen, Dong, Guangzhong, Chen, Zonghai
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Algorithms; Batteries; Battery energy storage; Computational modeling; Computer simulation; Continuous improvement; Diagnostic systems; Energy storage; Fault detection; Fault diagnosis; Heat generation; Integrated circuit modeling; Liapunov direct method; Lithium; Lithium-ion batteries; Lyapunov-based observer; Mathematical model; Rechargeable batteries; Resistance; Storage systems; Temperature measurement; thermal faults; Thermodynamic properties
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2019.2931275

With the continuous improvement of lithium-ion batteries in energy and power density, their safety and reliability concern is becoming increasingly urgent for energy storage systems. Thermal faults are one of the most critical faults in lithium-ion batteries that must be diagnosed in real time, because they can be potentially catastrophic. Motivated by this fact, a diagnostic algorithm is presented in this article to diagnose several thermal faults in cylindrical lithium-ion batteries, including heat generation fault and thermal parameter fault. This diagnostic algorithm is based on an electrothermal-coupled model describing both electrical and thermal dynamic behaviors of batteries. A Lyapunov-based battery internal resistance estimator is proposed to describe the dynamics of the surface and the core temperature of a battery cell, because the heat generation caused by the electrical loss is highly dependent on battery resistance. An observer-based fault detection framework is then established based on surface temperature measurements and resistance estimates, where stability and convergence are guaranteed by Lyapunov direct method. Furthermore, the adaptation law of fault evaluation threshold is designed to suppress modeling and measurement uncertainties. Simulation studies are presented to illustrate the effectiveness of the proposed model and diagnosis algorithm.