A novel power control strategy of series hybrid electric vehicle

Because of the inherent advantages of increased fuel economy, reduced harmful emissions and better vehicle performance, hybrid electric vehicles (HEV) powered by internal combustion engine (ICE) and energy storage, are being given more and more attention. In this paper, we present a novel approach to the problem of power control strategy for series hybrid electric vehicles (SHEVs). We define 3 different SHEV operation modes and a cost function. After the support vector machine (SVM) training process, we generate a classifier to determine which operation mode should be chosen during driving cycles based on the road situation data, battery state of charge (SOC) data and vehicle speed data. The approach does not need models of SHEV devices, costs less computationally and is more efficient. These distinguished advantages make the approach more practicable in real-time operation. Simulation study proves the feasibility of the approach.