**8. Conclusions**

This research proposes an advanced metaheuristic MPA optimization approach used in a "small electric vehicle system", which operates on a "solar-powered BLDC motor" system. An MPA optimization approach is implemented to retain "Maximum Power Point" tracking from partial shadow condition as well as constant irradiation in the PV cell in this case. The traditional "MPPT algorithms", especially "WOA" and "GWO", depending on the results of MPPT, were examined, and the proposed algorithm was compared to them. To charge the battery, PV energy is used, and it is also used to supply power to the BLDC motor. The proposed system is created by using MATLAB software. Through the use of torque and change in speed accelerating and decelerating, in addition to the PID controller, the BLDC motor's initial, dynamic, and steady-state behaviors were evaluated. According to the simulation result, the MPA optimization technique improves the performance of the motor and charges the battery well. Consequently, due to continuous solar charging throughout the daytime, the battery is used to operate the BLDC motor for more distance than any electric vehicle.

**Author Contributions:** Data curation: R.K.G.R. and P.K.B.; Writing original draft: R.K.G.R.; Supervision: T.S., P.K.B. and U.M.; Project administration: P.K.B., U.M. and T.S.; Conceptualization: U.M. and A.M.M.S.; Methodology: P.K.B. and R.K.G.R.; Validation: A.M.M.S. and U.M.; Visualization: U.M. and A.M.M.S.; Resources: T.S. and P.K.B.; Review & Editing: T.S., P.K.B. and R.K.G.R.; Funding acquisition: T.S. All authors have read and agreed to the published version of the manuscript.

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

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

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