**5. Conclusions**

In the current research paper, the following most relevant contributions of the authors can be highlighted:


Based on six statistical criteria values for all three SOC estimators, as a behavior response to an FTP-75 driving cycle profile test, it was possible to choose, from all three competitors, the most suitable SOC estimator. The result of the overall performance analysis indicates that the AEKF SOC estimator performs better than the other two competing SOC estimators.

In future work, our investigations will continue to improve the design and implementation approach by using fuzzy logic, neural networks and learning machine methods from artificial intelligence field.

**Author Contributions:** R.-E.T. has contributed for, algorithm conceptualization, software, original draft preparation and writing it. N.T. has contributed for battery models investigation and validation, performed MATLAB simulations and formal analysis of the results. M.Z. has contributed for project administration, supervision, and results visualization. S.-M.R. has contributed for methodology, data curation and supervision. All authors have read and agreed to the published version of the manuscript.

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

**Acknowledgments:** In Research funding (discovery grant) for this project from the Natural Sciences and Engineering Research Council of Canada (NSERC) is gratefully acknowledged.

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