Abstract:
Growing concerns regarding toxic COx and NOx emissions caused by the vehicles and the scarcity of over-exploited non-renewable resources that led the automobile industry to look out for a more energy efficient energy consumption is the main reason behind the development of Hybrid Electric Vehicles (HEVs). This paper comprises of artificial intelligence techniques employed to achieve smooth speed tracking performance in nonlinear HEVs. Techniques like fuzzy logic, neural network and genetic algorithm have been applied to tune and optimize the parameters of Proportional-Integral-Derivative (PID) controller.
