In this paper, first a simplified electrochemical model that includes internal faulty modes (capacity, power and rate capability fade) is developed for a lithium-ion battery. It is derived from the so-called equivalent hydraulic model for the battery electrodes, but it also includes the electrolyte dynamics as well as the thermal effects. Next this model is exploited to design a diagnosis system able to detect and isolate both internal faults and sensor faults. This system relies on a dual unscented Kalman filter for residual generation, as well as tracking of the parameters and the states of the model. The simulation results demonstrate that a set of fault indicators that allow fault discrimination can be obtained with the proposed approach.
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Couto et al. (2018) studied this question.
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