Research On Energy Management Strategy Of Hybrid Electric Vehicle Based On Compound Structure Double-rotor Motor

In recent years,the pressure of energy and environmental issues has made the development of new energy vehicles the mainstream of the automotive industry.Due to the limitations of battery technology and the prevalence of charging piles,there are still some restrictions on the development of pure electric vehicles.Hybrid electric vehicle(HEV),as a transition between fuel vehicles and pure electric vehicles,have been favored and valued by major automobile manufacturers around the world.And HEVs of various topologies have been continuously introduced to the market.In the development process of HEVs,its energy management strategy is the key to determine the success of the development of this model.A good energy management strategy can improve the vehicle's dynamic performance and fuel economy.As a power distribution device with a new energy transmission topology,the compound structure double-rotor motor(CSDM)is very suitable for a HEV with a complicated working mode and various power transmission modes.In this paper,the CSDM-HEV is taken as the research object.On the basis of introducing its working principle and operation mode,the optimization problem of energy management strategy of this HEV is studied.Firstly,based on the working characteristics of CSDM-HEV and "expert experience",this paper develops a rule-based optimization control strategy,and studies the advantages and disadvantages of the strategy.Secondly,in order to pursue the optimal fuel economy of the vehicle,this paper proposes an equivalent consumption minimum strategy(ECMS)to optimize the fuel consumption of the HEV,and considers the impact of the change in the state of charge(SOC)value of the battery on the fuel economy of the vehicle.After that,a battery SOC control strategy module based on the penalty function is added to the control model.Based on the theoretical analysis,this paper establishes a joint simulation model based on AVL/Cruise and MATLAB/Simulink,and carries out simulation on ECMS strategy.The results show that the fuel consumption of the vehicle is relative to the application under the condition of NEDC.The rule-based control strategy saves 8.97%,which verifies the validity and correctness of the ECMS developed in this paper.After that,this paper focuses on the problem of slow calculation speed when ECMS works.Elman neural network algorithm used to optimize ECMS,and ECMS-based Elman neural network control algorithm is designed.The simulation results of the algorithm show that the ECMS control model optimized by Elman neural network algorithm has faster calculation speed,which improved by 92.2% under NEDC conditions than before.The simulation results greatly enhances the practicality of ECMS.Finally,the experiment of ECMS based Elman neural network control algorithm carried out on the test bench with CSDM.The experimental results show that the algorithm is feasible.