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A Mathematical Model for Dynamic Electric Vehicles: Analysis and Optimization

Author

Listed:
  • Khalid Khan

    (Department of Mathematics, University of Malakand, Chakdara Dir(L) 18000, Khyber Pakhtunkhwa, Pakistan)

  • Inna Samuilik

    (Institute of Life Sciences and Technologies, Daugavpils University, 13 Vienibas Street, LV-5401 Daugavpils, Latvia
    Institute of Applied Mathematics, Riga Technical University, LV-1048 Riga, Latvia)

  • Amir Ali

    (Department of Mathematics, University of Malakand, Chakdara Dir(L) 18000, Khyber Pakhtunkhwa, Pakistan)

Abstract

In this article, we introduce a flexible and reliable technique to simulate and optimize the characteristics of a Dynamic Electrical Vehicle (DEV). The DEV model is a discrete event-based modeling technique used in electrical vehicle research to improve the effectiveness and performance of various electrical vehicles (EVs) components. Here, the DEVS model is applied to EV research in several ways, including battery management optimization, evaluation of power train design and control strategy, and driver behavior analysis. The essential power train elements, including the battery, motor, generator, internal combustion engine, and power electronics are included in the mathematical model for the dynamic electric vehicle. The model is derived using the conservation of energy principle. The model includes mathematical equations for the electrical power output, battery charge level, motor torque, motor power output, generator power output, internal combustion engine torque, mechanical power delivered to the generator, and the efficiencies of the power electronics, motor, generator, and engine. The model is examined by using a numerical method called the Runge–Kutta Method of order 4 for dynamic electric vehicle’s performance under various driving states for maximum effectiveness and performance. It is revealed that the DEV model provides a systematic method to simulate and optimize the behavior of complex EV systems.

Suggested Citation

  • Khalid Khan & Inna Samuilik & Amir Ali, 2024. "A Mathematical Model for Dynamic Electric Vehicles: Analysis and Optimization," Mathematics, MDPI, vol. 12(2), pages 1-19, January.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:2:p:224-:d:1316215
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    References listed on IDEAS

    as
    1. Nikita V. Martyushev & Boris V. Malozyomov & Svetlana N. Sorokova & Egor A. Efremenkov & Mengxu Qi, 2023. "Mathematical Modeling the Performance of an Electric Vehicle Considering Various Driving Cycles," Mathematics, MDPI, vol. 11(11), pages 1-26, June.
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