Study On The Control Strategy Of Regenerative Braking For HEV

With the rapid growth of vehicle production, vehicle fuel consumption accounts for all oil production sharings is increasing. Regenerative braking is the general technology to recover energy in hybrid electric vehicle, regenerative braking in hybrid vehicles is one of the most important differences to conventional cars. Rccovering a part of energy lost in traditional cars durning braking, thereby greatly enhancing fuel economy and saving energy.This dissertation first compared several common performances of electric vehicles, summaried the advantages of hybrid vehicles, introduced the development of regenerative braking control strategy, analied the principle of regenerative braking, described the excellent evaluation index of braking performances, the mathematical models of vehicle drive systems and batteries were built. This dissertation introduced importantly vehicle-specific simulation software ADVISOR from the view of hybrid electric vehicle simulation technology, described its simulation process and simulation theory. On account of the deficiency of the original share strategy of braking force in HEV simulation software ADVISOR, based on the regenerative braking control model, a new model in which the braking share of every braking force varies on the change of loading was built from the dynamical standpoint. Simulation was done with the use of ADVISOR in HAFEI automobile.At last, aiming at the problems of energy management strategy in HEV, fuzzy control of regenerative braking for HEV based on particle swarm optimization with compressibility factor was proposed. A fuzzy controller of energy management was constructed by using the torque request of the hybrid system and the battery state of charge (SOC) as inputs, and the engine torque as the output based on PSO with compressibility factor, improving the problems such as lower precision and limited adaptive capability in the traditional fuzzy control algorithm, and the robustness and control accuracy were improved. The simulation results in ADVISOR showed the fuzzy control algorithm based on PSO with compressibility factor compared with the traditional fuzzy control algorithm can improve fuel economy and control the change of SOC more effectively, the emission has been improved.