A direct yaw moment control frame through model predictive control considering vehicle trajectory tracking performance and handling stability for autonomous driving
Lisheng Jin, Heping Zhou, Xianyi Xie, Baicang Guo, Xiangsheng Ma
{"title":"A direct yaw moment control frame through model predictive control considering vehicle trajectory tracking performance and handling stability for autonomous driving","authors":"Lisheng Jin, Heping Zhou, Xianyi Xie, Baicang Guo, Xiangsheng Ma","doi":"10.1016/j.conengprac.2024.105947","DOIUrl":null,"url":null,"abstract":"<div><p>This paper considers the problem of optimal coordination of trajectory tracking performance and handling stability for autonomous equipped with distributed drive electric vehicle. Therefore, a hierarchical frame for multi-mode chassis dynamics torque vector allocation strategy is proposed, which aimed to solve the contradictory issues between vehicles’ trajectory tracking accuracy and handling stability under extreme working conditions. Firstly, in a hierarchical architecture, the upper-level trajectory tracking controller is designed by using model predictive control theory, which is used to solve the front wheel angle and the additional yaw moment of the vehicle. Secondly, the lower-level multimode torque distribution controller severs the sum of tire force utilization in every wheel as the objective function, and designs three distribution modes of chassis dynamic torque vectors based on the response of the longitudinal force and yaw moment obtained from the upper-level controller. Thirdly, the switching mechanism between the three chassis torque vector distribution modes is set according to the road adhesion condition and the requirements of the upper-level controller. Then, an analysis is conducted on the computational time complexity and robustness of the algorithm, confirming the potential for real-world application of the algorithm. Finally, Simulink/CarSim co-simulation test and hardware-in-the-loop test platform are carried out. And a vehicle trajectory tracking controller with single-mode torque vectors distribution by MPC is used as the baseline algorithm. The test results show that the proposed method show better trajectory tracking performance and handling stability than the baseline algorithm under the conditions of low adhesion surfaces and split-friction surfaces. Therefore, this study provides a solution for the safe driving of autonomous vehicles under extreme working conditions.</p></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":null,"pages":null},"PeriodicalIF":5.4000,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Control Engineering Practice","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0967066124001072","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper considers the problem of optimal coordination of trajectory tracking performance and handling stability for autonomous equipped with distributed drive electric vehicle. Therefore, a hierarchical frame for multi-mode chassis dynamics torque vector allocation strategy is proposed, which aimed to solve the contradictory issues between vehicles’ trajectory tracking accuracy and handling stability under extreme working conditions. Firstly, in a hierarchical architecture, the upper-level trajectory tracking controller is designed by using model predictive control theory, which is used to solve the front wheel angle and the additional yaw moment of the vehicle. Secondly, the lower-level multimode torque distribution controller severs the sum of tire force utilization in every wheel as the objective function, and designs three distribution modes of chassis dynamic torque vectors based on the response of the longitudinal force and yaw moment obtained from the upper-level controller. Thirdly, the switching mechanism between the three chassis torque vector distribution modes is set according to the road adhesion condition and the requirements of the upper-level controller. Then, an analysis is conducted on the computational time complexity and robustness of the algorithm, confirming the potential for real-world application of the algorithm. Finally, Simulink/CarSim co-simulation test and hardware-in-the-loop test platform are carried out. And a vehicle trajectory tracking controller with single-mode torque vectors distribution by MPC is used as the baseline algorithm. The test results show that the proposed method show better trajectory tracking performance and handling stability than the baseline algorithm under the conditions of low adhesion surfaces and split-friction surfaces. Therefore, this study provides a solution for the safe driving of autonomous vehicles under extreme working conditions.
期刊介绍:
Control Engineering Practice strives to meet the needs of industrial practitioners and industrially related academics and researchers. It publishes papers which illustrate the direct application of control theory and its supporting tools in all possible areas of automation. As a result, the journal only contains papers which can be considered to have made significant contributions to the application of advanced control techniques. It is normally expected that practical results should be included, but where simulation only studies are available, it is necessary to demonstrate that the simulation model is representative of a genuine application. Strictly theoretical papers will find a more appropriate home in Control Engineering Practice''s sister publication, Automatica. It is also expected that papers are innovative with respect to the state of the art and are sufficiently detailed for a reader to be able to duplicate the main results of the paper (supplementary material, including datasets, tables, code and any relevant interactive material can be made available and downloaded from the website). The benefits of the presented methods must be made very clear and the new techniques must be compared and contrasted with results obtained using existing methods. Moreover, a thorough analysis of failures that may happen in the design process and implementation can also be part of the paper.
The scope of Control Engineering Practice matches the activities of IFAC.
Papers demonstrating the contribution of automation and control in improving the performance, quality, productivity, sustainability, resource and energy efficiency, and the manageability of systems and processes for the benefit of mankind and are relevant to industrial practitioners are most welcome.