TY - GEN
T1 - Research on optimal power allocation strategy based on power demand prediction for electro-mechanical transmission
AU - Zhao, Yulong
AU - Chen, Wenjun
AU - Wang, Weida
AU - Xiang, Changle
AU - Huang, Kun
N1 - Publisher Copyright:
© 2016 TCCT.
PY - 2016/8/26
Y1 - 2016/8/26
N2 - Electro-mechanical transmission (EMT), with power distribution strategy as its core technology, stands for the developing orientation of the heavy vehicles' transmission, which is able to fulfill power, fuel economy and electricity demand of the vehicles. Furthermore, the demand power prediction has significant meaning for the improvement of the control strategy performance. In this paper, the mechanical and electrical power balance equations were established according to the split and convergence characteristics of the power coupling mechanism. The power demand of the EMT is predicted through combination of the fixed-gain prediction algorithms and the input that driver's desired speed during the vehicle driving cycle. Then the optimal power distribution strategy based on power prediction algorithm is achieved. Moreover, the optimal allocation pattern of the engine and motors is proposed. The rationality of control strategy is verified by the forward simulation results, which shows the new strategy based on the demand power prediction has better power performance and fuel economy than the traditional rule-based one.
AB - Electro-mechanical transmission (EMT), with power distribution strategy as its core technology, stands for the developing orientation of the heavy vehicles' transmission, which is able to fulfill power, fuel economy and electricity demand of the vehicles. Furthermore, the demand power prediction has significant meaning for the improvement of the control strategy performance. In this paper, the mechanical and electrical power balance equations were established according to the split and convergence characteristics of the power coupling mechanism. The power demand of the EMT is predicted through combination of the fixed-gain prediction algorithms and the input that driver's desired speed during the vehicle driving cycle. Then the optimal power distribution strategy based on power prediction algorithm is achieved. Moreover, the optimal allocation pattern of the engine and motors is proposed. The rationality of control strategy is verified by the forward simulation results, which shows the new strategy based on the demand power prediction has better power performance and fuel economy than the traditional rule-based one.
KW - EMT
KW - fixed-gain prediction algorithm
KW - optimal control strategy
KW - power distribution
UR - https://www.scopus.com/pages/publications/84987900132
U2 - 10.1109/ChiCC.2016.7554735
DO - 10.1109/ChiCC.2016.7554735
M3 - Conference contribution
AN - SCOPUS:84987900132
T3 - Chinese Control Conference, CCC
SP - 8638
EP - 8643
BT - Proceedings of the 35th Chinese Control Conference, CCC 2016
A2 - Chen, Jie
A2 - Zhao, Qianchuan
A2 - Chen, Jie
PB - IEEE Computer Society
T2 - 35th Chinese Control Conference, CCC 2016
Y2 - 27 July 2016 through 29 July 2016
ER -