Electric vehicle power drive train optimization techniques and its analysis based on multiple cycles

Electric vehicles (EVs) are increasingly recognized as a viable means to reduce greenhouse gas emissions and decrease reliance on traditional fossil fuels within the transportation industry. The powertrain system of an EV is pivotal in influencing the vehicle's overall effectiveness and efficiency. The improvement of EV powertrains encompasses efforts to boost energy conversion efficiency, optimize power output, and extend the vehicle's operational range. The proposed article discusses several key optimization techniques such as motor control algorithms, battery management systems, regenerative braking, and power electronics optimization. The objective of this article is to enhance the distance traveled by a vehicle by determining the optimal drivetrain configuration. This setup is designed to reduce battery discharges while maintaining optimal vehicle performance throughout a varied driving cycle. The genetic algorithm optimization technique is used in this article to determine the best drive configuration. The obtained simulation results validate the determination of the best configuration.