Drive cycle generation for stochastic optimization of energy management controller for hybrid vehicles

A methodology to generate drive cycles based on probabilistic driving profiles is presented in this paper. The described approach can be utilized for the stochastic optimization of an energy management controller (EMC) for hybrid electric vehicles (HEVs). It enables for an optimal design towards a probabilistic driving portfolio such as individual driving characteristics of the vehicle operator, location, traffic conditions, topography and environment. Hence, maximum fuel efficiency for the individual driver can be achieved. The introduced method is implemented in a drive cycle generation tool. The approach is validated using a model of a parallel HEV powered by fuel cells. Simulation results are presented and the advantage of the proposed method over conventional approaches is proven.