Simulation Research On Energy-efficient Control System Of Electric Vehicles Based On Intelligent Connection

The popularity of automobiles has brought enormous pressure to energy and the environment.Energy conservation,emission reduction and carbon reduction have become the focus of the development of the automobile industry,and electric vehicles have become an important direction of automobile development.The energy-efficient control of electric vehicles based on intelligent connection can reduce the driving energy consumption of electric vehicles and improve the cruising range,which has important research value.This dissertation studies the energy-efficient control of electric vehicles under smooth road conditions and the energy-efficient control of intelligent connected electric vehicles considering traffic lights,aiming to optimize the driving energy consumption of electric vehicles.Firstly,based on reading a large amount of literatures to make a summary of the current research status of energy-efficient control of intelligent connected vehicles,electric vehicles are selected as the research object,and the energy-efficient control problem of optimizing vehicles driving energy consumption through velocity profile planning is studied.The electric vehicle controlled object model is established in the simulation software AMESim,and the AMESim and MATLAB/Simulink co-simulation platform is established for the subsequent control effect verification of the controller.Secondly,for the energy-efficient control of electric vehicles under smooth road conditions,a vehicle velocity profile planning method based on variable prediction time domain model predictive control is proposed.Based on the analysis of the optimization problem,a linear longitudinal dynamics model of electric vehicles for controller design is established,and the prediction equation is derived based on the model.The objective function of the optimization problem is constructed from the perspective of reducing the working loss of the motor,the road velocity limit and actuator limit were transformed into optimization problem constraints,and the relationship between motor loss power,motor speed and motor torque was fitted into a polynomial form based on motor loss power MAP.In order to solve the optimization problem,a model predictive control method with variable prediction time domain is proposed,and the terminal velocity constraint and terminal distance constraint of the optimization problem are transformed into the terminal penalty term of the objective function.The simulation conditions are designed,and the controller effect is verified on the co-simulation platform of MATLAB/Simulink and AMESim.The simulation results show that the electric vehicle can achieve a 29.08%energy saving effect compared to the driver’s driving with the velocity profile planning result,which shows that the designed controller has a good effect and proves the effectiveness of the proposed method.Finally,based on the study of energy-efficient control of electric vehicles under smooth road conditions and considering the influence of traffic signals on vehicle driving,a vehicle driving velocity profile planning method incorporating traffic signal information based on variable step model predictive control is proposed.Based on V2X（Vehicle to Everything）technology,the vehicle can be informed of the traffic signal change information at the intersection ahead of driving in advance,and the learned traffic signal change information will be used to guide the vehicle’s driving velocity profile planning.Based on the analysis of the optimization problem,a nonlinear longitudinal dynamics model for controller design is established,and the prediction equation is derived based on the model.When constructing the description of the optimization problem,the objective function is established from the perspective of reducing the motor working losses,and the traffic light change information is transformed into part of the objective function and constraints.In order to make the velocity profile planning results easy to satisfy the terminal constraints of the optimization problem,a variable step model predictive control method for the solution of the optimization problem is proposed,and the controller sampling time is designed to be related to the velocity of the vehicle.When designing driving tasks,define driving task parameters with reference to the driver’s driving results,and the velocity profile planning is carried out by means of section planning.Simulation results show that whether in a single traffic light driving scenario or in a multiple traffic lights driving scenario,electric vehicles driving with velocity profile planning results achieve better energy savings relative to driver driving and reduce waiting time for red lights,proving the effectiveness of the proposed method.