Research On Power Battery SOC Estimation And Energy Management Strategy For Plug-in Hybrid Electric Vehicles

In order to alleviate the environmental pollution caused by automobile exhaust emissions,and improve the fuel economy to reduce the energy crisis,plug-in hybrid electric vehicles are getting more and more attention.Different from the traditional hybrid electric vehicle,plug-in hybrid electric vehicle is equipped with a larger capacity battery,and its energy management strategy of power system is more complex.The power battery state of charge(SOC)estimation and energy management strategy for plug-in hybrid electric vehicle is studied in this thesis.Firstly,the effect of different battery model on SOC estimation results is analyzed,and the Thevenin equivalent circuit model is established.Then,recursive least squares with forgetting factor(FFRLS)method is applied to realize the on-line identification of the model parameters.Secondly,combined estimation of power battery SOC and model parameters based on Extended kalman filter(EKF)algorithm and FFRLS algorithm.Considering the the shortcomings of EKF algorithm,BP neural network is used to train the relevant parameters which affect the accuracy of filtering estimation.Through the real-time correction of the estimation error,the joint estimation of BP neural network aided EKF algorithm and parameter online identification is realized.Finally,on the CD-CS strategy basis,the fuzzy control energy management strategy based on torque distribution is designed,which the power battery SOC and the drive torque are regarded as fuzzy inputs and the engine torque is fuzzy output.Then,the fuzzy controller is embedded into the ADVISOR software for secondary development.On the basis of this,the particle swarm optimization algorithm is proposed to optimize the energy management strategy of the fuzzy controller,it realizes the design object to improve the fuel economy and decrease the emissions.The use of the particle swarm algorithm to optimize the fuzzy rules of the fuzzy controller,combined with MATLAB and ADVISOR simulation software,to achieve the global optimal solution.The simulation results show that the SOC estimation method can achieve accurate and stable control,and the energy management strategy can obtain good fuel economy and emission.The thesis provides a promising research value on the SOC estimation and energy management strategy formulation.