Nonlinear Fault Detection and Isolation for a Lithium-Ion Battery Management System

Lithium-ion batteries are a growing source for electric power, but must be maintained within acceptable operating conditions to ensure efficiency and reliability. Therefore, a robust fault detection and isolation scheme is required that is sensitive enough to determine when sensor or actuator faults present a threat to the health of the battery. A scheme suitable for a hybrid electric vehicle battery application is presented in this work. The diagnostic problem is formulated as a nonlinear parity equation approach, but is modified for the considered application. Sliding mode observers are designed for input estimation, while the output voltage estimation is performed using an open loop model. The selection of optimal thresholds given a maximum allowable probability of error is also considered. An assessment of the design using real-world driving-cycle data leads to the conclusion that the estimation error of the observers determines a lower bound on the minimum detectable fault magnitude.