Optimization of Electric Vehicle Battery Size and Reduction Ratio Using Genetic Algorithm

A battery electric vehicle (BEV), known as a pure electric vehicle, exclusively uses chemical energy stored in rechargeable battery units (BUs), with no secondary source of propulsion. In this study a genetic algorithm (GA) based optimization study has been performed in order to find the optimum battery size or capacity and the final drive ratio (FDR) for the given driving profiles of an electric vehicle to find maximum range and minimum acceleration time for a BEV. Numerous startups and conventional automotive companies offer a variety of electric vehicles to customers from small electric motorcycles to full-size passenger vehicles. Battery sizing is very critical as it is the main factor for driving range. However excessive battery allocation will increase vehicle cost and weight significantly. Optimized input parameters of FDR and battery capacity were calculated to obtain maximum value of composite objective function which requires maximization of range and minimization of acceleration time of the vehicle at the same time, in the given interval of input parameters.