Trajectory Tracking Control Research On Full X-by-wire Electric Vehicle Based On Different Maneuvering Modes

In today's increasingly complex traffic environment,the requirements for vehicle chassis flexibility are becoming higher and higher.In response to the needs of social development,with the rapid improvement of electronic control system technology,full X-by-wire electric vehicles based on distributed chassis will become a solution to the problem of complex traffic environment.X-by-wire electric vehicles have a unique structure of four-wheel independent driving/braking/steering,combing with control methods,it can achieve more flexible and efficient trajectory tracking,which brings many new possibilities for the development of intelligent driving technology.At present,most researches on trajectory tracking and control of full X-by-wire electric vehicles regard it as the basic platform for the realization of desired motion,which combined traditional chassis vehicle control ideas to realize the design of its trajectory tracking control method,it is difficult to give full play to the advantages of full X-by-wire electric vehicles.Therefore,this paper is supported by the National Natural Science Foundation of China,‘Research on Reconfigurable Integrated Control Strategy for Distributed Full-line Controlled Electric Vehicles'(No.51505178)and the Science and Technology Project of the Education Department of Jilin Province during the 13 th Five-Year Plan Period ‘Distributed Electric Vehicle Power Based on Wire Control Chassis dynamic Modeling and Cooperative Control'(No.JJKH20200963KJ),starting from the flexible maneuvering characteristics of the full X-by-wire electric vehicle,considering its dynamic characteristics,the trajectory tracking control method of the full X-by-wire electric vehicle in different driving modes is studied as following parts:1)Research on the estimation method of the full X-by-wire electric vehicle motion state: Aiming at the inaccurate observation of the vehicle motion state caused by the sudden change of the torque of the drive system in-wheel motors and the uncertainty of the vehicle model,a dual-structure strong tracking filter is proposed(Double Strong Tracking Filter,DSTF)motion state observer.The strong tracking filter(Strong Tracking Filter,STF)method is used to observe the state of the in-wheel motor-based drive system and the vehicle motion state,according to the data sharing between the two filters and take advantage of the robustness for model uncertain of the strong tracking filter method strong tracking ability of signal changes can quickly,the vehicle motion status information can be accurately obtain.Through simulation comparison,it is verified that the designed DSTF observer for full X-by-wire electric vehicles can accurately obtain the vehicle motion state without signal mutation;when the driving system in-wheel motor state signal changes suddenly,the proposed observation still has fast and accurate signal processing and estimation capabilities.Compared with the existing full X-by-wire electric vehicle motion state observer,it has improved the ability to observe the vehicle motion state.2)Aiming at emergency conditions,in order to meet the strict trajectory tracking accuracy requirements to ensure the safety of unmanned driving,take advantage of the flexible characteristics of full X-by-wire electric vehicles,a trajectory tracking control method that integrates different driving modes is proposed.Firstly,the trajectory tracking controller of the four-wheel independent drive/brake/steering chassis is designed based on the layered integrated control architecture combined with Model Predictive Control(MPC)method,which combines the artificial potential field method in the MPC trajectory tracking control.The obstacle avoidance potential field function is introduced into the optimization objective to realize the dynamic obstacle avoidance function.Secondly,based on the linearized friction circle constraint combined with the quadratic programming method,the generalized force/moment of the desired vehicle is distributed,combined with the actuator execution layer possessed the inverse tire model,the desired trajectory tracking motion can be realized.On the basis of the above,abandoning the traditional method of manually selecting and rigorously switching between different steering modes by the driver in low-speed conditions,first,the vehicle driving mode is divided into traditional and non-traditional driving modes based on the posture of the vehicle tracking trajectory.And design a full X-by-wire electric vehicle trajectory tracking control method that automatically integrates different driving modes,in which a variable optimization control target is introduced into the MPC trajectory tracker,and a variable weight adjuster is designed to combine the constraint ability of the MPC framework on vehicle dynamics.By controlling the fusion of traditional and non-traditional driving modes to different degrees,more flexible and accurate trajectory tracking control is achieved.The simulation results show that the proposed fusion trajectory tracking control method for full X-by-wire electric vehicles with different driving modes can effectively improve the trajectory tracking accuracy.3)In the working conditions with low trajectory tracking accuracy requirements,in order to adapt to the long-term driving habits formed based on the traditional architecture chassis and improve the ride comfortability,for the traditional driving mode of the full X-by-wire lectric vehicle,the adaptive MPC trajectory tracking control methodis studied,which can satisfy different dynamic stability requirements.First,combine the traditional driving mode to reorganize the control architecture for improving the real-time performance of predictive control,and use the(center of mass side slip angle-center of mass side slip angle velocity,?-(?))phase plane to characterize vehicle stability to judge the dynamic stability And combined with the stability quantification index and the given threshold,according to the influence of the prediction domain in the MPC controller on the dynamic stability of the full X-by-wire electric vehicle,it is adjusted online;for the mathematical problems in the adaptive MPC trajectory tracking control,Introducing a decreasing exponential weight into the objective function to solve the disturbance problem in the switching process of the prediction domain caused by the "ill-conditioned" system,and at the same time reduce the sensitivity of the control system to disturbance;setting a long control horizon is effective for vehicles in dynamic stable conditions The trajectory and yaw tracking capabilities are optimized.The Laguerre function sequence is introduced to fit the control sequence in the control horizon,and the optimization variables are converted from multiple control increments to a small number of fitting parameters,so that the optimization calculation is not complicated.The tracking accuracy of the reference trajectory and expected yaw is improved without increasing computed burden.The simulation results show that the proposed adaptive MPC trajectory tracking control method has a significant improvement in tracking accuracy compared with the traditional MPC trajectory tracking control method for the traditional driving mode of the full X-by-wire electric vehicle,which conforms to the traditional driving and riding custom.And through optimization,the trajectory tracking accuracy in stable conditions is further improved,and the effectiveness of the proposed method is verified.4)Test and verification for the method proposed in this paper.First,the full X-by-wire electric vehicle is used to collect and synthesize the experimental data,which simulates the in-wheel motor failure and test noise to verify the proposed DSTF motion state observer;based on the driving simulator,build a full X-by-wire electric vehicle trajectory tracking controller that integrates multiple driving modes and the adaptive MPC trajectory tracking controller under the traditional driving mode,and the real-time ability of the corresponding method optimized the actuator delay is introduced in the medium and high speed working conditions,and the proposed method is verified in the loop.The test results show that the trajectory tracking control methods for different working conditions can obtain good trajectory tracking control effects,which verifies the effectiveness of the method.