AI Optimized Induction Motor Controller For EVs

Abstract

Electric vehicles (EVs) emerge as an eco-friendly alternative to gasoline engines, addressing environmental concerns and mitigating the impact of carbon emissions on the ecosystem. The soaring fuel prices further necessitate affordable commuting solutions. Traditional EVs employ DC motors, notably BLDC motors, posing challenges like high costs, dependency on scarce permanent magnets, and limited lifespan. This project endeavors to develop a controller facilitating the operation of electric cars utilizing an Induction motor. Despite its inherent complexities in control, the control of the Induction motor presents a cost-efficient, highly efficient, and dependable solution. The implementation focuses on leveraging the voltage-hertz method, ensuring consistent torque delivery across variable speeds. By optimizing the control mechanism of the induction motor, this endeavor seeks to pave the way for a more accessible, eco-conscious, and economically viable means of electric vehicle propulsion. The integration of AI in refining motor control strategies holds the promise of achieving optimal performance and efficiency in real-world driving scenarios. In essence, this project endeavors to establish an efficient and reliable framework for utilizing induction motors in electric vehicles, contributing to the advancement of sustainable transportation solutions while emphasizing affordability and environmental preservation.