GA-Based Fuzzy Energy Management System for FC/SC-Powered HEV Considering H2 Consumption and Load Variation

The combination of the fuel cell (FC) and supercapacitor for a hybrid electric vehicle (HEV) has the benefit of compensating for the slow dynamic response and avoiding reactant starvation of FC. Energy management system (EMS) is critical to HEV and a fuzzy controller plus low-pass filter is proposed to prolong the FC lifetime and decrease the hydrogen consumption. The constrained biobjective optimization problem for fuzzy EMS is then solved by an improved genetic algorithm (GA), where the decimal and rule base encoding, constraint handling, the pruning and maintain operator are designed to optimize both the fuzzy rule base and the parameters of the membership functions. Simulation results of highway fuel economy certification test, urban dynamometer driving schedule, and new European drive cycle illustrate that the proposed approach can smooth the output of FC with robustness and be implemented in real time, which decreases 19% current variation with about 10% increase of H
₂
consumption.