Research On Optimization Of Energy Management Strategy Of Plug-in Hybrid Electric Vehicle

It’s going to be more serious with the continuous education of the community,with the environmental and energy problems,people demand energy saving and emission reduction.In order to purify the air and reduce energy problems,Hybrid Electric Vehicle in the automotive industry stands out between traditional fuel vehicles and pure electric vehicles due to its low energy consumption,low pollution and high efficiency,and have attracted people’s attention.The energy management strategy is the key to the operation of hybrid electric vehicles and directly affects vehicle properties control.This paper takes a coaxial parallel plug-in hybrid electric vehicle as the research object,with the goal of optimizing vehicle energy distribution and improving vehicle fuel economy,and carries out the design and automatically optimise energy management strategies.Referring to the mentioned national models and according to the characteristics of the vehicle,the vehicle models and parts of the vehicle are surrounded by the MATLAB/Simulation simulation,including engine model,engine model,battery model,transmission model,vehicle dynamics model etc.Subsequently,analyzing the various of operation modes and switching conditions of the vehicle,a logic threshold-based control strategy for whole-vehicle energy management was developed.According to the handling features of the vehicle engine and motor,a series of logic threshold parameters are set for the vehicle mode switching and torque distribution to achieve control.Finally,the logic threshold strategy model is built in the MATLAB/Simulink simulation platform and its control effect is verified by simulation experiments.Based on the energy control strategy of the whole vehicle based on the logic threshold value,in response to the complex and ever-changing driving environment of vehicles and the general control effect of the threshold constraint value,a fuzzy controller is added to its driving charging and hybrid drive mode to optimize and adjust the vehicle energy distribution.An energy management control strategy based on a dual fuzzy controller is established and its torque distribution is divided,The simulation results show that the fuel economy of the vehicle has been improved.Finally,the setting of membership function parameters in fuzzy rules tends to be subjective,in order to further improve the optimization effect of vehicle fuel consumption.From the perspective of global optimization,the dynamic programming algorithm is used to find the optimal solution of fuel consumption.The simulation results show that the dynamic programming control strategy is better than the optimal control strategy based on double fuzzy controllers,and significantly improves the fuel economy of the vehicle.In view of the weak real-time control of dynamic programming algorithm,train and learn the optimal engine output torque control variable dataset using BP neural network.On the basis of realizing real-time control,the simulation results show that the optimization control strategy based on BP neural network has a good optimization effect.