TY - GEN
T1 - Model Predictive Control Considering Engine On/Off and Mode Switch for Dual-mode Hybrid Electric Vehicle
AU - Guo, Xinghua
AU - Yang, Chao
AU - Wang, Weida
AU - Zha, Mingjun
N1 - Publisher Copyright:
© 2021 The Society of Instrument and Control Engineers-SICE.
PY - 2021/9/8
Y1 - 2021/9/8
N2 - For dual-mode hybrid electric vehicle (HEV), the design of switch strategy and energy management strategy (EMS) are always independent. However, due to the complex and changeable driving condition hybrid electric vehicle encountering, the vehicle performance, including fuel economy and battery lifetime, will be affected by the inconsistency between the two strategies. It's still open to study how to combine switch strategy with EMS. Aiming at this problem, this paper proposes a model predictive control (MPC) considering engine on/off and mode switch for dual-mode hybrid electric vehicle. Firstly, in order to get the precise input sequence, Back Propagation Neural Network is used to forecast future velocity. Secondly, a cost function, considering engine on/off and mode switch, which is solved with Pontryagin's minimum principle (PMP), is put forward. To avoid frequently mode switch and engine on/off during the process of velocity fluctuation, a smooth method is applied in the prediction domain of MPC. Finally, the proposed EMS is verified in simulation. Simulation results show that this strategy can achieve the desired goals.
AB - For dual-mode hybrid electric vehicle (HEV), the design of switch strategy and energy management strategy (EMS) are always independent. However, due to the complex and changeable driving condition hybrid electric vehicle encountering, the vehicle performance, including fuel economy and battery lifetime, will be affected by the inconsistency between the two strategies. It's still open to study how to combine switch strategy with EMS. Aiming at this problem, this paper proposes a model predictive control (MPC) considering engine on/off and mode switch for dual-mode hybrid electric vehicle. Firstly, in order to get the precise input sequence, Back Propagation Neural Network is used to forecast future velocity. Secondly, a cost function, considering engine on/off and mode switch, which is solved with Pontryagin's minimum principle (PMP), is put forward. To avoid frequently mode switch and engine on/off during the process of velocity fluctuation, a smooth method is applied in the prediction domain of MPC. Finally, the proposed EMS is verified in simulation. Simulation results show that this strategy can achieve the desired goals.
KW - Dual-mode hybrid electric vehicle
KW - Energy management strategy
KW - Engine on/off and mode switch
KW - model predictive control
UR - http://www.scopus.com/inward/record.url?scp=85117685530&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85117685530
T3 - 2021 60th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2021
SP - 714
EP - 719
BT - 2021 60th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 60th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2021
Y2 - 8 September 2021 through 10 September 2021
ER -