Optimization of equivalent fuel consumption minimization strategy based on firefly algorithm
1. School of Automotive Engineering， Wuhan University of Technology, Wuhan， Hubei 430070， China； 2. Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan University of Technology, Wuhan， Hubei 430070， China
Abstract：To improve the fuel economy of hybrid electric vehicles（HEVs）, an optimization of equivalent fuel consumption minimization strategy (EFCMS) was proposed based on firefly algorithm (FA). Taking the parallel hybrid electric vehicle as research object, the equivalent factor of EFCMS and the battery state of charge (SOC) were optimized by FA to realize the equivalent control. A whole vehicle model was established in Matlab/Simulink for simulation. The results show that
compared with that before optimization, the fuel saving rates under three working conditions of urban dynamometer driving schedule（UDDS）， new European driving cycle（NEDC）and highway fuel economy test（HWFET） can respectively reach 286%, 255% and 169%. Compared with the traditional algorithms, the fuel consumption of the proposed EFCMS based on FA is effectively decreased, and the battery SOC can be well maintained near the target value.
