Energy Control Strategy For Plug-in Hybrid Electric Vehicle Based On Speed Prediction

Because the fuel economy of PHEV is very well,it has become an important development direction.Since PHEV has two power sources(motor and engine),it is necessary to develop a reasonable energy control strategy in order to achieve the best fuel economy.Based on the analysis of domestic and foreign hybrid vehicle energy control strategies,this paper focuses on the PHEV energy control strategy based on short-term traffic speed prediction.In this paper,the traffic speed prediction model is used to predict the traffic speed in the future.In order to achieve improve the fuel economy of the vehicle,the predicted traffic speed is used into the energy control strategy.Firstly,this paper analyzes the advantages and disadvantages of control strategy based on rules,real-time optimization control strategy and global optimization control strategy.Then,the five working modes of PHEV are introduced,and the vehicle model of PHEV is built by ADVISOR simulation platform.Secondly,the influence of traffic speed on the economy of PHEV fuel is analysed.The GPS system of 400 taxis in Foshan City is used to get traffic information.The traffic speed of the six sections of Fenjiang Road is collected and studied.The short-term traffic velocity prediction model(SVM model)is established and this model is compared with the moving average model,historical data model,ANN model,k-NN model and ARIMA model.Then,the prediction accuracy of each model is studied.Finally,the predicted traffic speed is used into the energy control strategy.The results show that the higher the accuracy of traffic speed prediction model,the better the fuel economy of PHEV.In addition,the short-term traffic speed prediction model(SVM model)has the highest prediction accuracy,and the corresponding PHEV energy control strategy achieves the best fuel economy.