An energy management strategy based on genetic algorithm for fuel cell hybrid yard truck

Energy management is one of the key issues for hybrid electric vehicle (HEV) to improve energy efficiency and prolong fuel cell life, especially for the HEV in port logistic characterized by low speed and heavy load. However, there is a serious lack of investigation on the energy management strategy of hydrogen-fueled yard truck (YT) for port applications. In order to reduce the hydrogen fuel consumption of YT configured by a fuel cell and a power battery, an energy management strategy based on genetic algorithm (GA) is proposed in this paper. According to the power flow and efficiency characteristics of key components of HEV hybrid powertrain, the equivalent hydrogen consumption objective is considered in the GA. In the proposed real-coded GA, uniform mutation and two-point crossover operators are used to involve solutions, and the elitist strategy is adopted to improve the quality of solutions and facilitate fast convergence. Moreover, the penalty method is adopted to maintain the right range of battery SOC. The simulation results show that solutions obtained by GA under two typical operations are better than those obtained by existing rule-based strategy.