The Multi-objective Optimization of Cost, Energy Consumption and Battery Degradation for Fuel Cell-Battery Hybrid Electric Vehicle

As one of the promising solutions to air pollution and energy crisis caused by the transportation sector, fuel cell hybrid electric vehicles (FC HEVs) attract great attention around the world. Given the under power of the fuel cell to meet the requirements of daily driving, a power supplement system, generally battery, is essential to make up a multi-power hybrid powertrain. In this paper, the power matching strategies are optimized, considering the system cost, energy efficiency, and battery degradation, by particle swarm optimization (PSO) algorithm. Based on the change of the degree of hybridization (DOH), two hybrid systems are proposed, and the corresponding optimal hybridization degrees of the hybrid powertrain are found under four groups of weighting factors. Based on multi-objective optimization, the optimal hybridization degrees of the hybrid powertrain are proposed to extend battery life, improve energy consumption, and reduce powertrain cost according to individual requirements.