This book explores how advanced control theories and artificial intelligence can be integrated to enhance the stability adaptability and efficiency of electric vehicles operating under harsh real-world conditions. It bridges classical and modern approaches - from PID and robust H control to neural networks and reinforcement learning - offering a unified framework for handling nonlinearities uncertainties and severe constraints such as aerodynamic drag tire slip and battery degradation while envisioning resilient autonomous and sustainable EV systems connected to smart grids.