TY - GEN
T1 - Steering Reference Acceleration Generation Strategy for a Multi-axis Distributed Drive Electric Vehicle
AU - Yang, Sen
AU - Li, Junqiu
AU - Yang, Shengjun
AU - Qiu, Lulu
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - Distributed drive electric vehicles enable more precise and faster power control. A vehicle steering reference acceleration generation strategy is studied in this paper to improve the steering stability of distributed drive vehicles. The strategy is explored on the basis of a four-axle in-wheel motor driven vehicle and is integrated into a hierarchical vehicle dynamic control system. The proposed strategy is implemented by an adaptive reference acceleration model. Based on linear 2 degree-of-freedom (2DOF) vehicle model, the adaptive model can correct the reference acceleration generated by 2DOF vehicle model in a nonlinear region where the vehicle total force demand exceeds the road surface adhesion limit. In linear region, the adaptive model produces a reference acceleration that is consistent with 2DOF vehicle model. Results of hardware-in-the-loop (HIL) simulation show that the proposed adaptive reference acceleration generation model has better steering stability than 2DOF linear reference model under extreme operating conditions.
AB - Distributed drive electric vehicles enable more precise and faster power control. A vehicle steering reference acceleration generation strategy is studied in this paper to improve the steering stability of distributed drive vehicles. The strategy is explored on the basis of a four-axle in-wheel motor driven vehicle and is integrated into a hierarchical vehicle dynamic control system. The proposed strategy is implemented by an adaptive reference acceleration model. Based on linear 2 degree-of-freedom (2DOF) vehicle model, the adaptive model can correct the reference acceleration generated by 2DOF vehicle model in a nonlinear region where the vehicle total force demand exceeds the road surface adhesion limit. In linear region, the adaptive model produces a reference acceleration that is consistent with 2DOF vehicle model. Results of hardware-in-the-loop (HIL) simulation show that the proposed adaptive reference acceleration generation model has better steering stability than 2DOF linear reference model under extreme operating conditions.
KW - adaptive reference model
KW - distributed drive electric vehicle
KW - reference acceleration
KW - steering stability control
UR - http://www.scopus.com/inward/record.url?scp=85072301654&partnerID=8YFLogxK
U2 - 10.1109/ICCAR.2019.8813708
DO - 10.1109/ICCAR.2019.8813708
M3 - Conference contribution
AN - SCOPUS:85072301654
T3 - 2019 5th International Conference on Control, Automation and Robotics, ICCAR 2019
SP - 683
EP - 688
BT - 2019 5th International Conference on Control, Automation and Robotics, ICCAR 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Control, Automation and Robotics, ICCAR 2019
Y2 - 19 April 2019 through 22 April 2019
ER -