• N. Bhargavi
• Dr. D. KIRAN KUMAR

The transition to a sustainable transport sector has established electric vehicles as a key to minimising fuel consumption and pollution of the environment. There are many parameters in design that influence the vehicle range, acceleration, efficiency and cost, among others; battery size and final drive ratio are among them. This paper aims to maximise these two parameters in order to enhance the overall performance of the EV. A Genetic Algorithm, which is based on natural evolution, is applied to seek the optimal combination of battery capacity and gear ratio. This work strikes a balance between both driving and acceleration time, unlike the traditional methods, which focus on one of the performance aspects. MATLAB/Simulink develops the model of the single-mass vehicle in order to demonstrate the real driving conditions. Various changes in the parameters are experimented with to learn how they change the behaviour of vehicles. The decision-making of optimisation also makes sure that design constraints like weight and cost are taken into consideration. The findings indicate that the suggested solution is effective in enhancing efficiency without sacrificing size and cost, without any needless changes. In general, the paper shows that a smarter and more realistic design of electric vehicles can be supported by evolutionary optimisation techniques.

Battery Electric Vehicles, Genetic Algorithm Optimisation, Battery Sizing, Final Drive Ratio, Vehicle Dynamics Modelling, Energy Efficiency

"OPTIMIZATION OF ELECTRIC VEHICLE BATTERY SIZE AND DRIVE RATIO BY USING EVOLUTIONARY TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 2, page no.b423-b431, February-2026, Available :http://www.jetir.org/papers/JETIR2602156.pdf

"OPTIMIZATION OF ELECTRIC VEHICLE BATTERY SIZE AND DRIVE RATIO BY USING EVOLUTIONARY TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 2, page no. ppb423-b431, February-2026, Available at : http://www.jetir.org/papers/JETIR2602156.pdf