Optimization algorithm applied to extended range fuel cell hybrid vehicles. Contribution to road transport decarbonization

Progressive decarbonization of road transport is underway to reduce greenhouse gas (GHG) emissions and their harmful effects. Although different options have already been considered, hydrogen-electric hybridization seems to be an interesting option to reduce emissions by offering vehicles with sufficient range and competitive performance compared to fossil fuel vehicles. The development of energy management systems (EMS) that achieve efficient use of energy is crucial to extend the vehicles range. In this paper we propose two energy management systems applied to two hydrogen hybrid vehicles: a Plug-in Hybrid Electric Vehicle (PHEV) and a Range-Extended Fuel Cell Hybrid Vehicle (FC-EREV). The proposed EMSs are based on single and multi-level approaches, that consider the amount of hydrogen in the tank to implement a rule-based strategy (RBS) that distributes the current demanded by the motor between the fuel cell and the battery. The EMS parameters for both approaches were selected using a particle swarm optimization (PSO) algorithm in order to find the optimized set of values for both EMS. The proposals have been tested for different driving cycles, showing improvements up to 9% and 12% in range, for the single and multi-level approaches, respectively, when compared to previous works.