公开(公告)号：US12091114B2

公开(公告)日：2024-09-17

申请号：US18395716

申请日：2023-12-25

Applicant: Zhengzhou University of Light Industry

Inventor： Zhijun Fu ,  Yaohua Guo ,  Dengfeng Zhao ,  Jinquan Ding ,  Chaohui Liu ,  Wenbin He ,  Wenchao Yang ,  Lei Yao ,  Fang Zhou ,  Hui Wang ,  Wuyi Ming

IPC: B62D7/15

CPC classification number: B62D7/159

Abstract: The present disclosure provides a self-learning collaborative control method for active steering and yaw moment for a motor vehicle, including a first step of constructing fundamental formulas which are stored in a vehicle ECU, and a second step of calculating an active steering angle δC and a yaw moment Mc on line by the vehicle ECU according to following sub-steps during a driving process of the motor vehicle, and controlling a driving state of the motor vehicle according to δC and Mc. The second step includes a first sub-step of collecting raw real-time parameter values, a second sub-step of performing calculation by the identifier and the control target reference model, a third sub-step of calculating δC and Mc. The present disclosure can realize the self-learning collaborative control of active steering and yaw moment without requiring a system control model and correct a driver's steering operation.

公开(公告)号：US20240132152A1

公开(公告)日：2024-04-25

申请号：US18395716

申请日：2023-12-25

Applicant: Zhengzhou University of Light Industry

Inventor： Zhijun Fu ,  Yaohua Guo ,  Dengfeng Zhao ,  Jinquan Ding ,  Chaohui Liu ,  Wenbin He ,  Wenchao Yang ,  Lei Yao ,  Fang Zhou ,  Hui Wang ,  Wuyi Ming

IPC: B62D7/15

CPC classification number: B62D7/159

Abstract: The present disclosure provides a self-learning collaborative control method for active steering and yaw moment for a motor vehicle, including a first step of constructing fundamental formulas which are stored in a vehicle ECU, and a second step of calculating an active steering angle δC and a yaw moment Mc on line by the vehicle ECU according to following sub-steps during a driving process of the motor vehicle, and controlling a driving state of the motor vehicle according to δC and Mc. The second step includes a first sub-step of collecting raw real-time parameter values, a second sub-step of performing calculation by the identifier and the control target reference model, a third sub-step of calculating δC and Mc. The present disclosure can realize the self-learning collaborative control of active steering and yaw moment without requiring a system control model and correct a driver's steering operation.