TY - JOUR
T1 - An Economic Driving Energy Management Strategy for the Fuel Cell Bus
AU - Guo, Jinquan
AU - He, Hongwen
AU - Wei, Zhongbao
AU - Li, Jianwei
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2023/12/1
Y1 - 2023/12/1
N2 - Compared with passenger cars, the fuel cell bus (FCB) driving cycles have obvious periodicity. Therefore, based on the driving cycles' periodicity characteristics and the traditional velocity prediction energy management strategy (EMS), this article proposes an economic driving EMS (EDEMS) for the FCB. In EDEMS, two scenarios are designed for the bus line condition: when there is no front bus in the bus lane (main scenario), the FCB can follow a trapezoidal programming curve (TPC)-based speed planning from the bus station out/in, which reduce the intersection stop condition, and the speed planning as the input applied to the model predictive control (MPC)-based EMS; otherwise, traditional velocity prediction is used in the MPC-based EMS (backup scenario). Moreover, the busload change at the bus station is added for the EDEMS cost function, which can accurately calculate the energy consumption and optimal energy allocation. The results show that the main scenario can reduce the intersection stop driving condition and the energy efficiency can improve by approximately 6.70% compared with the backup EMS. Overall, the EDMES can be applied to any bus route in the network environment and to further improve the comprehensive performance of FCB.
AB - Compared with passenger cars, the fuel cell bus (FCB) driving cycles have obvious periodicity. Therefore, based on the driving cycles' periodicity characteristics and the traditional velocity prediction energy management strategy (EMS), this article proposes an economic driving EMS (EDEMS) for the FCB. In EDEMS, two scenarios are designed for the bus line condition: when there is no front bus in the bus lane (main scenario), the FCB can follow a trapezoidal programming curve (TPC)-based speed planning from the bus station out/in, which reduce the intersection stop condition, and the speed planning as the input applied to the model predictive control (MPC)-based EMS; otherwise, traditional velocity prediction is used in the MPC-based EMS (backup scenario). Moreover, the busload change at the bus station is added for the EDEMS cost function, which can accurately calculate the energy consumption and optimal energy allocation. The results show that the main scenario can reduce the intersection stop driving condition and the energy efficiency can improve by approximately 6.70% compared with the backup EMS. Overall, the EDMES can be applied to any bus route in the network environment and to further improve the comprehensive performance of FCB.
KW - Energy management strategy (EMS)
KW - fuel cell bus (FCB)
KW - model predictive control (MPC)
KW - speed planning
KW - trapezoidal programming curve (TPC)
UR - http://www.scopus.com/inward/record.url?scp=85133722192&partnerID=8YFLogxK
U2 - 10.1109/TTE.2022.3185215
DO - 10.1109/TTE.2022.3185215
M3 - Article
AN - SCOPUS:85133722192
SN - 2332-7782
VL - 9
SP - 5074
EP - 5084
JO - IEEE Transactions on Transportation Electrification
JF - IEEE Transactions on Transportation Electrification
IS - 4
ER -