**6. Conclusions**

This paper presented a model-based sensor FDI scheme for a Li-ion cell used in EVs with cell degradation consideration. The scheme uses the RLS algorithm to estimate the ECM parameters in real time, and the WMA filter coupled with CUSUM control chart to detect faults. Experiments and simulations were conducted on an LFP cell in a controlled environment, to verify that ECM parameters are a ffected by degradation and faults to di fferent degrees; the latter having a more significant e ffect. It was also found that certain parameters respond faster to specific types of fault, enabling the isolation of faults. Finally, the UDDS driving cycles were used to validate the performance of the proposed FDI scheme. Various injection times, fault sizes, fault types, and cell capacities were considered. The validation results showed that the proposed scheme could detect and isolate voltage sensor faults and current sensor faults for an LFP cell within a reasonable time, with no false or missed detection.

**Author Contributions:** Conceptualization, M.-K.T. and M.F.; methodology, M.-K.T.; software, M.-K.T.; validation, M.-K.T.; formal analysis, M.-K.T.; investigation, M.-K.T.; resources, M.F.; data curation, M.-K.T.; writing—original draft preparation, M.-K.T.; writing—review and editing, M.-K.T. and M.F.; visualization, M.-K.T.; supervision, M.F.; project administration, M.-K.T.; funding acquisition, M.F. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Acknowledgments:** This work was supported by equipment and manpower from the Department of Chemical Engineering at the University of Waterloo.

**Conflicts of Interest:** The authors declare no conflict of interest.
