Study On Energy Management Strategy Of Plug-in Hybrid Electric Vehicles Based On The Influences Of Driving Conditions

Plug-in Hybrid Electric Vehicle(PHEV)energy management strategy is the key to affect the performance of hybrid power system.In order to fully improve the fuel economy of PHEVs,it is necessary to comprehensively consider the impact of road conditions(such as driving cycles,road grade,etc.).However,there is still rarely systematic research on the influences of road conditions on the performance and optimal control of PHEVs.Therefore,it is difficult to rationally optimize energy management strategies according to the impact of road condition information.This paper takes a parallel PHEV as research object and conducts a PHEV energy management strategy study that considers the influences of road conditions information.The main research contents are as follows:(1)Energy management strategy based on dynamic programming.Mathematical models of the hybrid power system are established combining experimental data with theoretical analysis.According to the dynamic characteristics of the hybrid system,the objective function,state variables and control variables of the dynamic programming algorithm are designed,and the dynamic programming problem of PHEV is constructed.The reasonable setting of dynamic programming algorithm simulation parameters and control variables are obtained by analyzing the impact of parameters such as the scaling of the length of driving cycles and control variables on the optimization results.(2)Study on the influence mechanism of driving conditions on PHEV performance and optimal control.K-means clustering algorithm based on simulated annealing is used to cluster a large number of driving cycle data into four types.Combining the SOC with the driving distance,a new parameter equivalent distance coefficient is proposed to characterize the driving distance.The mathematical models for energy consumption of hybrid system are established and the energy consumption characteristics of PHEV under different driving patterns are analyzed using the CD-CS control strategy.The results show that the deficiency of the traditional control strategy is the low energy efficiency in the CS mode.The key measure to improve the fuel economy is to take full use of electric energy to drive the vehicle,that is,to reasonably control the engine startup.Dynamic programming algorithm is used to obtain optimal control under the four types of driving cycles,and the optimal control strategies under the influence of different driving patterns and driving distances are extracted.The influence law of the driving cycle on the optimal engine starting power,shift schedule and engine torque distribution ratio is obtained.(3)Study on the influence mechanism of road grade on PHEV performance and optimal control.Mean road grade,standard deviation of road grade,single slope length and total length of slope are taken as characteristic parameters of slope.A mathematical model of slope is established by using Gauss random process.The comparison between global optimal energy management strategy based on minimum principle and dynamic programming is conducted.The impact mechanism of uphill road,hilly road with same altitude and downhill road on fuel economy improvement of PHEV is analyzed.Based on the research result of the influence mechanism in the previous chapter,the influence of road grade on the optimal engine starting power,shift schedule and engine torque distribution ratio is analyzed.Finally,the influence mechanism of road conditions including driving cycles and road grade on the optimal control of PHEV is obtained.(4)Develop a real-time energy management strategy based on the influence mechanism of driving conditions on the PHEV optimal control.The K mean clustering algorithm is used to recognize the driving pattern,and the other driving condition information are obtained by the road grade and the pure electric mileage information provided by the GPS/GIS system.Considering the influence mechanism of road condition information on PHEV optimal control,the engine starting power control strategy based on road condition information is formulated by three interpolation fitting and genetic algorithm.The controllers of shift schedule and engine torque distribution ratio are developed by BP neural network based on driving condition.Finally,real-time energy management strategy based on driving condition is realized.The effectiveness of the proposed energy management strategy is verified by simulation based on MATLAB/Simulink.