Research On Autonomous Drifting Obstacle Avoidance Algorithm For Distributed Drive Vehicles

Automobile “low-carbonization,informatization and intelligence” support and empower each other,and are leading the development of global automobile technology innovation.In the process of accelerating the development of power systems to low-carbon development,distributed drive electric vehicles have gradually become one of the important directions for the transformation and upgrading of global automotive power systems by virtue of the advantages of four-wheel independent drive,high power transmission efficiency,and the potential to reduce vehicle energy consumption and improve vehicle stability and safety.Informatization and intelligence point to the higher pursuit of “safety,comfort and efficiency” for future vehicles.Therefore,the automatic driving system of intelligent connected vehicles should continuously improve its ability in driving safety.The research on obstacle avoidance function plays an important role in promoting the improvement of vehicle safety performance by automatic driving technology.The existing obstacle avoidance technology research is usually conservative and cannot adapt to some extreme working conditions.The addition of automatic drift technology can enhance the handling range of vehicles and expand the obstacle avoidance ability of vehicles.In this paper,the drift characteristics are incorporated into the vehicle’s obstacle avoidance research using distributed drive electric vehicles as a carrier.It explores the obstacle avoidance trajectory planning algorithm of the vehicle’s driving ability beyond the typical stability limits and the drifting control algorithm adapted to the vehicle with four-wheel independent drive configuration to expand the controllable area of the vehicle,enhance the ability of autonomous driving technology to deal with extreme obstacle avoidance conditions,and improve the safety performance of autonomous vehicles.The details of the research are as follows.(1)A 3-DOF dynamics model and coupled form of the Fiala tire model were used to accurately describe the dynamic response of the distributed drive vehicle.The steady-state drift operating point of the vehicle is studied by phase portrait and equilibrium analysis,and the influence of front wheel longitudinal force on vehicle drift equilibrium is analyzed.It is found that the distributed drive vehicles have better controllability during operation than the rearwheel-drive vehicles,and the front wheel braking will reduce the stable operating area of the vehicle and the front wheel drive will expand the stable operating area of the vehicle.In addition,the reduction of the front wheel longitudinal force will improve the control of the front wheel cornering on the drifting radius of the vehicle.Finally,the ability of the control system to drive and stabilize the vehicle near the steady-state operating point is explored through tangent space,and the results show that the rear-wheel drive vehicle is an underdriven system with interdependence between state derivatives,while the distributed drive vehicle brings the underdriven system to a fully driven system due to the independent control of the longitudinal forces at the front wheels,which uncouples the state derivatives.Therefore,the velocity,sideslip angle and yaw rate during drifting can be controlled independently.(2)A dynamic drifting avoidance trajectory planning algorithm for vehicles with extreme conditions is proposed.The drift characteristics of the vehicle are incorporated into the obstacle avoidance planning to enhance the active obstacle avoidance capability of the autonomous vehicles,and the dynamic drifting obstacle avoidance trajectory planning algorithm is established based on the NMPC principle.Firstly,based on the 3-DOF model of the distributed drive vehicle,the position information of the vehicle and the actuator outputs together are regarded as the extended states of the vehicle,while the derivatives of the actuator outputs are taken as the inputs of the system,which finally forms a system prediction model with 9 states and 3 inputs.Then the cost function and its constraints are established to form the dynamic drifting obstacle avoidance optimal control problem,and the maximal stability envelop limit of the vehicle is proposed in the constraints to expand the limits of the sideslip angle and the yaw rate of the vehicle.Finally,the optimal control problem established by the obstacle avoidance planning is solved by nonlinear programming methods to obtain the obstacle avoidance trajectory of the vehicle.The algorithm is verified by U-turn path scenario,and the results show that the dynamic drifting obstacle avoidance trajectory planning algorithm realizes the safe driving path planning of the vehicle in the emergency obstacle avoidance condition,and at the same time can fully mobilize the vehicle capabilities and allow the vehicle states to exceed the typical stability limits to avoid the obstacle by drifting maneuvers.(3)A distributed drive vehicle dynamic drifting control algorithm with hierarchical architecture is established.The algorithm is divided into three layers: the first one is the path tracking control layer,which is designed with LQR algorithm to achieve the reference path tracking and desired states generation;the second one is the vehicle motion control layer,which generates the desired front and rear wheel speeds and front wheel side angle by establishing states error relations,distributed drive vehicle dynamics inverse model and tire model inversion;the third one is the actuator regulating layer,which converts the desired wheel speeds and tire slip angle into adjustable actuator outputs,i.e.,steering wheel angle and driving torque of each wheel.The Simulink/Car Sim co-simulation platform is built to simulate and verify the dynamic drifting control algorithm of the distributed drive vehicle,and two fixed-circle steady-state drift conditions are set up,respectively,constant sideslip angle with velocity variation and constant velocity with sideslip angle variation.The results show that the dynamic drifting control algorithm can realize the drift control of the vehicle and verify the characteristics that the velocity,sideslip angle and yaw rate can be controlled independently during the drifting of the distributed drive vehicle.In addition,a dynamic drift experiment of the vehicle is designed,and the results prove that the dynamic drifting control algorithm can realize the integrated control of drifting and typical cornering of the vehicle,which expands the handling range and improves the maneuverability of the vehicle.(4)The S-curve scenario is designed to simulate the emergency obstacle avoidance conditions of the vehicle at high speed,so as to fully verify the effectiveness of the autonomous drifting obstacle avoidance algorithm for distributed drive vehicles proposed in this paper,in which the obstacle avoidance trajectory planning algorithm is tested offline using Matlab,and while verifying its feasibility,the distributed drive vehicle dynamic drifting control algorithm is deployed on the hardware-in-the-loop simulation test bench for verification due to its excellent real-time performance.The results show that the distributed drive vehicles are capable of operating in emergency obstacle avoidance conditions with drifting maneuvers according to the obstacle avoidance requirements,which proves the effectiveness of the drifting obstacle avoidance algorithm in this paper and enhances the active safety performance of the vehicles.