Research On Adaptive Optimization Energy Management Strategy For Four-wheel Drive PHEV Based On Driving Condition Perception

Nowadays,plug-in hybrid electric vehicle(PHEV),as a multi-power source new energy vehicle,has a complex energy coupling relationship.Reasonable design of energy management strategy can give full play to the energy-saving potential of the vehicle and become an effective solution to alleviate the global energy crisis.Compared with two-power source single-bridge drive PHEV,multi-power sources and multipower components in four-wheel drive PHEV(4WD PHEV)form a more complex energy coupling relationship.However,in the 4WD PHEV energy management system,the coupled output relationships between power sources and between the front and rear motors exhibit a high degree of nonlinearity.Developing a reasonable energy management strategy can optimize and manage the energy system and maximize the energy-saving potential of the 4WD PHEV,which has become a thorny challenge to be solved.In order to give full play to the energy-saving potential of the 4WD PHEV,the dual adaptive ECMS(DA-ECMS)was established based on the theoretical basis of ECMS and combined with the two-layer energy management and control architecture.The multi-energy flow collaborative output optimization management of the 4WD PHEV was realized,and the energy-saving potential of the 4WD PHEV was fully brought into play.In the application of DA-ECMS,the multi-dimensional equivalent factor introduced can realize the optimization management of the multi-power source oil-electric system(the system composed of engine,generator,and power battery)of the front axle on the premise of satisfying the power performance and complete the energy flow optimization of the front and rear axle electronic control system.In order to improve the applicability of DA-ECMS driving conditions,the combination of offline and online methods is used to realize the division and identification of driving conditions,and the adaptive adjustment of multi-dimensional equivalent factor value is completed.The method of multi-algorithm fusion is used to complete the classification of driving conditions offline and the optimization of multi-dimensional equivalent factors and realize the matching of driving conditions identification and equivalent factors online.Therefore,the DA-ECMS takes into account the driving condition information,powertrain system,and vehicle states and weighs the relationship between economy,real-time,and driving condition adaptation.The simulation results verify the feasibility that the DA-ECMS proposed in this paper can give full play to the energysaving potential of the 4WD PHEV.This paper relies on a key science and technology research project in Jilin Province,which focuses on an in-depth study of energy management for a 4WD PHEV.This paper focuses on the development of strategies for 4WD PHEV energy management to achieve the optimal economy under different driving conditions.The main research contents of this paper are as follows.(1)The topology of the studied 4WD PHEV powertrain is introduced and the parameters of the key components are given.The model of the 4WD PHEV is built by MATLAB/Simulink simulation platform,including driver model,vehicle dynamics model,engine model,generator model,front motor model,rear motor model,and battery model.(2)A rule-based energy management strategy for the 4WD PHEV is analyzed,and the switching thresholds between different modes of the 4WD PHEV and the energy flow between components in different modes are analyzed in depth.(3)A dual ECMS applicable to 4WD PHEV is proposed using the ECMS basic theory to realize the energy distribution between power sources and energy distribution between power components,giving full play to the energy saving potential of 4WD PHEV.(4)In order to further optimize the values of the equivalent factors in the dual ECMS,improve the adaptability and robustness of the dual ECMS in terms of driving conditions,and further improve the economy of the 4WD PHEV,this paper proposes a dual adaptive ECMS(DA-ECMS)under a two-layer energy management control architecture,which combines the a priori information of the driving conditions of the4 WD PHEV with the dual ECMS.(5)The overall vehicle economy under six different energy management strategies is analyzed and compared,and the SOC,equivalent fuel consumption,and fuel consumption are analyzed in depth.In addition,in order to further analyze and compare the operating characteristics of 4WD PHEV components under six different energy management strategies,the operating point and output torque of the engine,front motor and rear motor are analyzed and compared respectively,which fully proves that the DAECMS proposed in this paper can achieve the best energy saving potential of the 4WD PHEV.Through hardware-in-the-loop experiments,the DA-ECMS is verified to have superior potential for application in a real-time environment.