Design automation and CAD customization of an EV chassis

Abstract This study focuses on developing an efficient approach to design and customizing electric vehicle (EV) chassis using automation and machine learning techniques. It includes 1) the design of an EV chassis using Python, 2) The implementation of a machine learning model to predict and find the suitable material for the chassis, and 3) CAD Customization of the chassis using Fusion 360 API in Python. 4) Structural Analysis of the chassis in Fusion 360. The mentioned methodology provides faster calculations, reduced manual errors, and a more efficient way of exploring design alternatives. The use of machine learning for material selection ensures a reliable and safe chassis. The study contributes to the advancement of EV chassis design processes by integrating automation and machine learning techniques, leading to faster and more reliable designs, and demonstrating the benefits of CAD customization.