TY - JOUR
T1 - Incorporated vehicle lateral control strategy for stability and enhanced energy saving in distributed drive hybrid bus
AU - Li, Lin
AU - Coskun, Serdar
AU - Langari, Reza
AU - Xi, Junqiang
N1 - Publisher Copyright:
© 2021
PY - 2021/11
Y1 - 2021/11
N2 - Vehicle stability and energy efficiency are important considerations in vehicle engineering. In this context, the current paper presents an energy saving strategy for hybrid electric vehicles that incorporates vehicle lateral dynamic control in conjunction with energy efficiency. To this end, we first model the nonlinear vehicle lateral dynamics of a hybrid electric bus via a Takagi–Sugeno approach and combine this model with an H_{\infty } state-feedback controller via parallel distributed compensation. The controller matrices are obtained using linear matrix inequalities through an optimal energy-to-energy performance norm of the nonlinear vehicle model. Second, we propose a reference side-slip angle generating method and a set of tire force distribution rules, which under the premise of ensuring vehicle stability, minimize the overall energy consumption of the vehicle. Finally, we put forward a new speed prediction method based on vehicle lateral dynamics for hybrid electric vehicle energy saving. Human-in-the-loop simulated driving experiments are conducted where the bus performs lane-changing maneuvers with enhanced control properties under various driving conditions, demonstrating the reliability of the proposed energy-saving performance measures.
AB - Vehicle stability and energy efficiency are important considerations in vehicle engineering. In this context, the current paper presents an energy saving strategy for hybrid electric vehicles that incorporates vehicle lateral dynamic control in conjunction with energy efficiency. To this end, we first model the nonlinear vehicle lateral dynamics of a hybrid electric bus via a Takagi–Sugeno approach and combine this model with an H_{\infty } state-feedback controller via parallel distributed compensation. The controller matrices are obtained using linear matrix inequalities through an optimal energy-to-energy performance norm of the nonlinear vehicle model. Second, we propose a reference side-slip angle generating method and a set of tire force distribution rules, which under the premise of ensuring vehicle stability, minimize the overall energy consumption of the vehicle. Finally, we put forward a new speed prediction method based on vehicle lateral dynamics for hybrid electric vehicle energy saving. Human-in-the-loop simulated driving experiments are conducted where the bus performs lane-changing maneuvers with enhanced control properties under various driving conditions, demonstrating the reliability of the proposed energy-saving performance measures.
KW - Distributed driving vehicles
KW - Fuzzy H_{\infty } control
KW - Hybrid electric vehicles
KW - Nonlinear bus model
KW - Speed prediction
KW - Tire force allocation
UR - http://www.scopus.com/inward/record.url?scp=85109505014&partnerID=8YFLogxK
U2 - 10.1016/j.asoc.2021.107617
DO - 10.1016/j.asoc.2021.107617
M3 - Article
AN - SCOPUS:85109505014
SN - 1568-4946
VL - 111
JO - Applied Soft Computing
JF - Applied Soft Computing
M1 - 107617
ER -