Intelligent Energy Management Based on the Driving Cycle Sensitivity Identification Using SVM

Hybrid Electric Vehicles (HEV) offer the ability to significantly reduce fuel consumptions and emission. Management of energy is one of essential elements in the implementation of hybrid electric vehicles. Engine and motor should satisfy the driver´s demand in different driving environment. This paper defines a driving cycle sensitivity parameter, which is used to create different driving cycles to substitute a kind of the on-road driving conditions. The parameters of control strategy are optimized by genetic agency on these different cycles. In this paper support vector machines (SVM) is used to identify the driving cycle sensitivity parameter. And an intelligent energy management is crated, which could change the parameters in control strategy to the genetic optimized results. Simulation work is carried out for the validation of proposed intelligent management, and the results show it´s great in improving fuel economy and reducing emissions.