Model-based thermal fault detection in Li-ion batteries using a set-based approach∗

Li-ion batteries suffer from reliability issues due to thermal instability. For this reason, it is important to design suitable Battery Management Systems (BMSs) able to enhance safety and guarantee high battery performance. In this paper we address the problem of detection of thermal faults within a Li-ion cell using a set-based fault detection scheme where unknown but bounded uncertainties are considered. In particular, an equivalent circuit model (ECM) is used for state estimation taking into account bounded parametric uncertainties and measurement noise. The proposed method relies on constrained zonotopes (CZ), a set representation useful for performing standard operations with a lower computational effort with respect to polytopes. Numerical simulations highlight the effectiveness of the proposed approach in detecting thermal faults at an early stage and show the benefits when compared to an interval based method relying on inclusion functions and constraint propagation.