TY - JOUR
T1 - Adaptive equivalent consumption minimisation strategy and dynamic control allocation-based optimal power management strategy for four-wheel drive hybrid electric vehicles
AU - Liu, Hui
AU - Li, Xunming
AU - Wang, Weida
AU - Han, Lijin
AU - Xin, Huibin
AU - Xiang, Changle
N1 - Publisher Copyright:
© IMechE 2018.
PY - 2019/10/1
Y1 - 2019/10/1
N2 - An adaptive equivalent consumption minimisation strategy and dynamic control allocation-based optimal power management strategy for a four-wheel drive plug-in hybrid electric vehicle is proposed in this paper. The equivalent factors of adaptive equivalent consumption minimisation strategy are optimised offline based on ISIGHT software over several typical driving cycles, which is integrated with AVL CRUISE and MATLAB/Simulink. To update the equivalent factor adaptively according to the predictive velocity, a neural network-based optimal equivalent factor prediction model is built, which can be used online. The torque distribution strategy considering axle load based on energy management strategy optimisation results and the vehicle dynamics control distribution is proposed: this includes two-wheel drive torque distribution, four-wheel drive torque distribution and brake torque distribution. The proposed energy management strategy is verified in New European Driving Cycle and Worldwide harmonised Light Vehicle Test Cycle driving patterns, and the simulation results show that the fuel economy of adaptive equivalent consumption minimisation strategy and dynamic control allocation-based optimal power management strategy is improved by 8.84% and 7.52% in New European Driving Cycle and Worldwide harmonised Light Vehicle Test Cycle, respectively, compared with the benchmark algorithm-based strategy.
AB - An adaptive equivalent consumption minimisation strategy and dynamic control allocation-based optimal power management strategy for a four-wheel drive plug-in hybrid electric vehicle is proposed in this paper. The equivalent factors of adaptive equivalent consumption minimisation strategy are optimised offline based on ISIGHT software over several typical driving cycles, which is integrated with AVL CRUISE and MATLAB/Simulink. To update the equivalent factor adaptively according to the predictive velocity, a neural network-based optimal equivalent factor prediction model is built, which can be used online. The torque distribution strategy considering axle load based on energy management strategy optimisation results and the vehicle dynamics control distribution is proposed: this includes two-wheel drive torque distribution, four-wheel drive torque distribution and brake torque distribution. The proposed energy management strategy is verified in New European Driving Cycle and Worldwide harmonised Light Vehicle Test Cycle driving patterns, and the simulation results show that the fuel economy of adaptive equivalent consumption minimisation strategy and dynamic control allocation-based optimal power management strategy is improved by 8.84% and 7.52% in New European Driving Cycle and Worldwide harmonised Light Vehicle Test Cycle, respectively, compared with the benchmark algorithm-based strategy.
KW - CRUISE
KW - ISIGHT
KW - Plug-in hybrid electric vehicle
KW - energy management strategy
KW - equivalent consumption minimisation strategy
KW - four-wheel drive
UR - http://www.scopus.com/inward/record.url?scp=85061044181&partnerID=8YFLogxK
U2 - 10.1177/0954407018816564
DO - 10.1177/0954407018816564
M3 - Article
AN - SCOPUS:85061044181
SN - 0954-4070
VL - 233
SP - 3125
EP - 3146
JO - Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
JF - Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
IS - 12
ER -