Research On Driving Control Strategy Of Pure Electric Vehicle Based On Driving Intention Recognition

Because of the characteristics of energy saving and non-polluting,pure electric vehicles have attracted extensive attention for research,development and application.With the increasing of oil crisis and environmental pollution,pure electric vehicles have become an important trend in the development of automotive industry.The focus of the vehicle development project is the vehicles control strategy,which affects the performance of the entire vehicle directly.The driving intention identification and drive control strategy influence the dynamic and economical performance of pure electric vehicles greatly.So it is of great important significance that the research of identification and driving control strategies.With the development of electric vehicles,it has become a research focus.This article takes a certain pure electric vehicle model of the cooperation project with China FAW Technology Center for research object to research on driving intention identification and driving control strategies.The main research contents for:Firstly,analysing the key components of the power electric vehicle powertrain system,and the actual selected parameters of the power motor and power battery are theoretically verified according to the performance index requirements.Secondly,Taking accelerator pedal opening and pedal opening change rate with a identification parameter,a support vector machine classification model was used to identify the driving intention.An adaptive particle swarm optimization algorithm was proposed to optimize the parameters of support vector machine and compared with the conventional particle swarm optimization algorithm.Simulation experiments show that the classification model obtained by this adaptive particle swarm optimization support vector machine has higher classification accuracy and higher prediction and identification.Thirdly,developing the drive control strategy of the pure electric vehicle,and completing the driver’s demand torque calculation.First,the basic torque MAP table is established based on the accelerator pedal opening and the vehicle speed.Then the required torque correction factor is determined by applying the fuzzy algorithm based on the acceleration intention recognition result and the current vehicle speed,which determined the final driver demand torque.Finally,using Cruise software to build the vehicle model and set parameters andconnect the various components of the vehicle.Using MATLAB to model the drive control strategy,then make the joint simulation of MATLAB/Simulink and Cruise.Comparing the simulation results of the complete vehicle model with driving control strategy and non-drive control strategy through computational tasks under different driving conditions.the performance of the electric vehicle is validated by driving control strategy based on driving intention recognition.