Optimal control of parallel hybrid electric vehicles

In this paper, a model-based strategy for the real-time load control of parallel hybrid vehicles is presented. The aim is to develop a fuel-optimal control which is not relying on the a priori knowledge of the future driving conditions (global optimal control), but only upon the current system operation. The methodology developed is valid for those problem that are characterized by hard constraints on the state-battery state-of-charge (SOC) in this application-and by an arc cost-fuel consumption rate-which is not an explicit function of the state. A suboptimal control is found with a proper definition of a cost function to be minimized at each time instant. The instantaneous cost function includes the fuel energy and the electrical energy, the latter related to the state constraints. In order to weight the two forms of energy, a new definition of the equivalence factors has been derived. The strategy has been applied to the Hyper prototype of DaimlerChrysler, obtained from the hybridization of the Mercedes A-Class. Simulation results illustrate the potential of the proposed control in terms of fuel economy and in keeping the deviations of SOC at a low level.