TY - JOUR
T1 - Handling and Stability Integrated Control of AFS and DYC for Distributed Drive Electric Vehicles Based on Risk Assessment and Prediction
AU - Liu, Hui
AU - Liu, Cong
AU - Han, Lijin
AU - Xiang, Changle
N1 - Publisher Copyright:
© 2000-2011 IEEE.
PY - 2022/12/1
Y1 - 2022/12/1
N2 - How to improve the trajectory following ability and lateral stability under extreme conditions is an important research problem for distributed drive electric vehicles (DDEVs). This paper proposes a novel integrated control architecture of active front steering control (AFS) system and direct yaw moment control (DYC) system for DDEVs. First, to deal with the future instability problem caused by driver's misoperation or delayed control, online risk assessment and prediction models, including self-regulating phase plane stability judgment and future driving state prediction of vehicles, is designed to provide decision commands for actuators in advance under extreme conditions. Then, on the basis of comprehensive consideration of system chattering, robustness and control constraint index requirements, an integrated control method based on robust sliding mode predictive control (SMPC) to put forward to solve the multi-objective and multi-constraint optimization problem for multi-subsystem integration. Finally, the simulation and experimental results show that the proposed control architecture can effectively assist drivers improve the trajectory following ability and handling stability of DDEVs, as to ensure the maneuverability and safety of emergency obstacle avoidance under extreme conditions.
AB - How to improve the trajectory following ability and lateral stability under extreme conditions is an important research problem for distributed drive electric vehicles (DDEVs). This paper proposes a novel integrated control architecture of active front steering control (AFS) system and direct yaw moment control (DYC) system for DDEVs. First, to deal with the future instability problem caused by driver's misoperation or delayed control, online risk assessment and prediction models, including self-regulating phase plane stability judgment and future driving state prediction of vehicles, is designed to provide decision commands for actuators in advance under extreme conditions. Then, on the basis of comprehensive consideration of system chattering, robustness and control constraint index requirements, an integrated control method based on robust sliding mode predictive control (SMPC) to put forward to solve the multi-objective and multi-constraint optimization problem for multi-subsystem integration. Finally, the simulation and experimental results show that the proposed control architecture can effectively assist drivers improve the trajectory following ability and handling stability of DDEVs, as to ensure the maneuverability and safety of emergency obstacle avoidance under extreme conditions.
KW - Distributed drive electric vehicles
KW - handling stability
KW - integrated control
KW - risk assessment and prediction
KW - sliding mode predictive control
UR - http://www.scopus.com/inward/record.url?scp=85135760195&partnerID=8YFLogxK
U2 - 10.1109/TITS.2022.3193891
DO - 10.1109/TITS.2022.3193891
M3 - Article
AN - SCOPUS:85135760195
SN - 1524-9050
VL - 23
SP - 23148
EP - 23163
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 12
ER -