Research On Autonomous Tracking Control Of Intelligent Full Drive-by-Wire Electric Vehicles

The intelligent full drive-by-wire electric vehicle is a new type of pure electric vehicle,employing the X-by-wire technology to control independently driving,braking and steering movement of each wheel.There are many advantages compared with the traditional vehicles.With the increasingly intelligent,electrified,wire-controlled and networked vehicles,autonomous driving technology has received extensive attention.Flexible vehicles with full drive-by-wire control provide a good application platform for autonomous driving technology.The chassis integrated control and path tracking control strategy is the key to realize the intelligent full drive-by-wire electric vehicle.This research relies on the National Natural Science Foundation funded project “Distributed Full-line Control Electric Vehicle Reconfigurable Integrated Control Strategy Research”(No.51505178).Research on the autonomous tracking control strategy of intelligent full drive-by-wire electric vehicle has been conducted.Firstly,the state of the electric vehicle is judged by phase plane analysis,and full drive-by-wire electric vehicle economy is mainly considered in normal working conditions;the stability is mainly done on the extreme conditions.Different optimization objectives and constraints are selected to establish the chassis comprehensive control strategy under full conditions,then the path planning and tracking control are studied to take advantage of distributed full drive-by-wire electric vehicles,the specific research has following aspects:(1)Using the hierarchical control structure to realize the intelligent integrated control of the full drive-by-wire electric vehicles chassis: design the sliding mode control algorithm(SMC)in the motion control layer to obtain the total target force and total torque of the vehicle;in the distribution optimization layer,based on the energy efficiency of the motor map,the four hub motor torques are optimally allocated to reduce the motor power loss and obtain the recovered energy of the regenerative braking,and the wheel lateral force is reduced by the corner distribution to reduce the tire wear.At the same time,according to the phase plane analysis of the centroid side angle,it is judged whether the vehicle is close to the limit condition,and the vehicle stability margin is maximized under the extreme conditions.This part of the research group has carried out relevant research and made some progress,therefore it has not been discussed in detail.(2)Considering the characteristics of each actuator,the co-simulation vehicle model is built based on CarSim/Simulink/AmeSim software.Firstly,based on the measured motor map,a simplified motor model is established for the hub motor.A control model based on three closed loops is established for the steering motor,and a hydraulic system model based on fuzzy control is established.Considering the insufficient braking torque of the motor during large deceleration,the electro-hydraulic hybrid braking(EHB)control strategy is adopted,and the fuzzy logic method is applied to the ABS control with higher braking intensity.Cosimulation with CarSim/ Simulink/AMEsim shows that the proposed strategy can improve vehicle stability,reflect the characteristics of each actuator and reduce the energy consumption caused by motor and tire side slip.(3)Research on the path planning of the full drive-by-wire electric vehicles has been conducted,firstly summarizing the path planning algorithms and analyzing the advantages and disadvantages,then selecting the artificial potential field method for path planning through comprehensive comparison,the repulsive function and the repulsive force has been presented to improve the potential unreachable and local optimal problems existing in the tranditional potential field method;for the high maneuverability of the full drive-by-wire electric vehicles,comprehensively consider the relevant kinematics and dynamic constraints,and integrate into the vehicle speed planning.In order to verify the validity and feasibility of the proposed planning method,different obstacle scenes are set up in a specified range for simulation verification.The results show that the proposed planning method can obtain a reasonable driving path and carry out the generated path points.Interpolation and piecewise fitting provide achievable position information for tracking control.(4)According to the research of tracking control of full drive-by-wire electric vehicles,based on fuzzy control theory,a forward-looking behavior model of driver with variable preview distance is designed.The vehicle lateral dynamics model and kinematic model are established,and the curvature calculation is proposed;for the shortcoming of tracking control algorithm based on curvature calculation,the model predictive control algorithm is adopted,comprehensively considering the vehicle constraints,real-time prediction and feedback optimization of vehicle state.By setting different simulation conditions comparison and analysis,it shows that the tracking accuracy obtained by the two control methods is not much different under low speed conditions;with the increase of speed,the control accuracy based on curvature calculation will be reduced,especially into the curvature.The curve needs to reduce the speed to a very low level,and the model prediction path tracking control method can be adjusted according to the vehicle state,showing better control effect.Therefore,the two control algorithms have their own advantages and disadvantages,and it is necessary to comprehensively consider all aspects to select the appropriate control algorithm.