Ferramentas livres para simulação de veículos elétricos: estudo de caso de um kart elétrico

Abstract

In response to the increasing demand for methods to reduce greenhouse gas emissions, electric vehicles have emerged as a global alternative to combustion vehicles, highlighting the importance of study and development technologies in this field. Modeling and simulation of electric vehicles are crucial for cost reduction, safety, and efficiency. However, most simulations are carried out using proprietary tools, such as Matlab, Simulink, and Simcenter Amesim. Therefore, it is worthwhile to explore free, alternative tools for electric vehicle simulation. In this context, an electric go-kart is used as a case study, employing existing open-source Python simulation libraries to perform essential simulations, such as driving cycle and energy efficiency analysis. The main libraries considered are Gym Electric Motor, to simulate motor control under the go-kart’s dynamic loads, and PyBaMM, for battery simulation. For the driving cycle, speed data from a combustion go-kart at a rental kart track was used to generate a speed reference for the electric go-kart. This approach enabled the simulation of the electric machine’s control according to the driving cycle’s speed reference and the system’s battery response for the electric go-kart simulation.