Optimization of the Mathematical Model of the Dynamics of Electric Vehicles

Abstract

In this paper, we present a flexible and reliable technique for electric vehicle dynamic performance simulation (DXS) and optimization. The DXS model is a discrete event-based modeling technique used in electric vehicle research to improve the efficiency and performance of various electric vehicle (ETV) components. Here, the DXS model is applied to ETV research in several ways, including battery management optimization, power train design and control strategy evaluation, and driver behavior analysis. The main power train elements, including the battery, motor, generator, internal combustion engine and power electronics, are included in the mathematical model of the dynamic electric vehicle. The model was created based on the principle of energy conservation. Model electrical power output, battery charge level, motor torque, engine output, generator power, internal combustion engine torque, mechanical power delivered to the generator and power electronics, motor, generator, and engine. The model is verified using a numerical method called the Runge-Kutta Level 4 method for dynamic electric vehicle performance under various driving conditions for maximum efficiency and performance. It was found that the DXS model provides a systematic method for simulating and optimizing the behavior of complex ETV systems.