Research On Minimum Energy Management Strategy For Equivalent Fuel Consumption Of Hybrid Electric Vehicles

Under the background of the shortage of oil resources,the aggravation of environmental pollution and the increasing greenhouse effect,the promotion of energy-saving cars has become the trend of automobile development.Hybrid electric vehicle,which combines the advantages of pure electric vehicle and traditional internal combustion engine vehicle,has become the research hotspot of energy-saving vehicle at present.Due to the multiple power sources of hybrid electric vehicles,efficient energy management strategies are needed to accurately distribute energy,so that all power sources can achieve a good cooperative working state,and finally improve the fuel economy of the vehicle.Aiming at the energy management system of a hybrid passenger vehicle,this paper studies the minimum energy management strategy of equivalent fuel consumption.The specific contents include:(1)The forward vehicle simulation platform including driver model,power component model,battery model,longitudinal dynamics model and control strategy model was built by using Matlab/simulink software,and the rationality of the simulation model was verified by using real vehicle data.(2)By deducing Pontriagin’s principle,this paper expounds the basis of establishing the mathematical model of minimum strategy of equivalent fuel consumption,and analyzes the influence of equivalent factor on vehicle fuel consumption and battery power.Then,in order to solve the problem that there are two conflicting optimization objectives in off-line optimization of the equivalent factor,a two-layer energy management strategy is proposed,which uses the dual-objective gray Wolf algorithm to optimize the equivalent factor in the outer layer and uses the characteristics of the strategy of least equivalent fuel consumption to achieve instantaneous optimal distribution of demand torque in the inner layer.(3)In order to optimize the equivalent factor in real time online,an adaptive equivalent fuel consumption minimum energy management strategy based on battery power feedback regulation was established.On this basis,after predicting the future vehicle speed by using the nonlinear autoregressive neural network algorithm with external input,the equivalent fuel consumption minimum energy management strategy based on vehicle speed prediction was further established.By comparing the simulation results of various strategies,it is found that all the strategies proposed in this paper can improve vehicle fuel economy and maintain battery power balance,and the strategy based on vehicle speed prediction has the best performance.