Design And Optimization Of Energy Management Strategy Based On Plug-in Hybrid Electric Vehicle

In the context of energy shortage and increasingly serious environmental pollution,governments around the world have launched new energy vehicle development policies.Plug-in hybrid electric vehicle is an important direction of the development of new energy vehicles.It has the dual advantages of traditional fuel vehicles and pure electric vehicles,and is currently a research hotspot in the industry.Plug-in hybrid electric vehicle has two power sources,engine and battery.Excellent energy management strategy is the key to play the performance of plug-in hybrid electric power system.This paper mainly focuses on the design and optimization of energy management strategies for single-axle parallel plug-in hybrid electric vehicles.First of all,a plug-in hybrid electric vehicle was selected.Through analysis,P2 configuration of the uniaxial parallel hybrid system was selected,and the maximum speed,maximum acceleration and maximum climbing slope of the vehicle were taken as the dynamic indexes to select the components of the hybrid system and match the parameters.The mathematical model of the dynamics of each part and the vehicle was established.The physical model of each part was established in CRUISE using the results of selection and matching.The control strategy of each part was designed in Simulink to verify the validity of the physical model of each part.Secondly,the working mode of P2 configuration plug-in hybrid electric vehicle is analyzed,and the energy management strategy based on CD-CS rules is designed and implemented.The simulation results show that the designed energy management strategy meets the initial requirements,which lays a foundation for the optimization of energy management strategy.Then,an energy management strategy based on ECMS was established,and the influence of equivalent factor on ECMS was analyzed.Considering the fuel economy and the sustainability of battery charging and discharging,an energy management strategy based on adaptive A-ECMS was established on the basis of ECMS,and the optimization results of A-ECMS were analyzed.Based on A-ECMS,a fuzzy adaptive algorithm Fuzzy A-ECMS and an offline particle swarm optimization adaptive algorithm PSO A-ECMS are proposed to optimize the equivalent factors of ECMS,and the simulation results are analyzed.Finally,in WLTC and NEDC cycles,from two aspects of fuel economy and sustainability of charge and discharge of power battery,the simulation results based on engine optimization curve,ECMS,A-ECMS,Fuzzy A-ECMS and offline PSO A-ECMS are compared and analyzed,as well as the optimization effect of Fuzzy A-ECMS and offline PSO A-ECMS on the energy management strategy based on CD-CS rules.The results show that Fuzzy A-ECMS and off-line PSO A-ECMS have better fuel economy and better performance of maintaining SOC balance.Under WLTC cycle condition,the equivalent fuel consumption of 100 km in Fuzzy A-ECMS is reduced by 4.5%,and the range of SOC is reduced by 26.3%.Compared with Fuzzy A-ECMS,the 100 km equivalent fuel consumption of PSO A-ECMS is reduced by 0.82%,and the range of SOC is reduced by 4.8%.Under NEDC cycle condition,the equivalent fuel consumption of 100 km by Fuzzy A-ECMS is reduced by 1.67%,and the range of SOC is reduced by 70.3%.Compared with Fuzzy A-ECMS,the equivalent fuel consumption of PSO A-ECMS is reduced by 2.8% and the range of SOC is reduced by 21.73%.The energy management strategy based on Fuzzy A-ECMS reduces the equivalent fuel consumption of 100 km by 2.5% compared with that based on CD-CS rules,and the energy management strategy based on PSO A-ECMS reduces the equivalent fuel consumption of 100 km by 2.86% compared with Fuzzy A-ECMS.