**3. Proposed Fault Diagnosis Scheme**

In other industrial applications, parameter estimation is a common fault diagnosis method, due to its ability to be implemented online. The method involves the online estimation of the parameters, and the results are compared with a reference model [16]. For real-time identification of ECM parameters, the RLS method is selected because it has low computational demand, fast convergence speed, and can easily be implemented in an embedded system [14]. In this particular case, this method can estimate the model parameters, while adapting to their changes with the degradation and operational conditions of the battery [17]. The resulting estimations are in the form of a time series, for which a change point detection method can be used to diagnose faults [18]. The change point detection method proposed in this paper consists of a WMA filter and a CUSUM control chart.
