An Energy Management Strategy and Parameter Optimization of Fuel Cell Electric Vehicles

Abstract

This study involved a detailed analysis of an energy distribution strategy and the parameters of key components of fuel cell electric vehicles (FCEVs). In order to better utilize the advantages of multiple energy sources, the wavelet-fuzzy energy management method was used to adjust the demand power allocation among multiple energy sources, and particle swarm optimization (PSO) was used to solve highly nonlinear optimization problems under multi-dimensional and multi-condition constraints. The multi-objective optimization problem of predefined driving cycle powertrain parameters about fuel economy and system durability was studied. The parameters of the key components of the system were optimized, including the size parameters of the air com-pressor and the number of batteries and ultra-capacitors. Furthermore, the driving state under specific working conditions was analyzed, and a nonlinear model with system durability and fuel economy as the optimization objectives were established, which greatly reduced the costs, reduced the fuel consumption rate and extended the battery life. The simulation results showed that for a UDDS cycle, the FCS’s maximal net output power of 83 kW was optimal for the fuel economy and system durability of a fuel cell city bus.