TY - GEN
T1 - A Real-Time Predictive Energy Management Strategy for Power-split Plug-in Hybrid Electric Bus
AU - Huang, Ruchen
AU - He, Hongwen
AU - Meng, Xiangfei
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - This paper proposes a real-Time predictive energy management strategy (EMS) for a power-split plug-in hybrid electric bus (PHEB) to improve fuel economy by decreasing the total operation cost of fuel and electricity. Firstly, a two-dimensional (2-D) velocity prediction method is adopted to improve the accuracy of the prediction. Then, an online optimal controller is designed to distribute power flows optimally by tracking the SOC reference trajectory accurately. At last, comprehensive comparative simulations are conducted to validate the effectiveness of the proposed EMS in terms of fuel economy improvement and real-Time application performance. Simulation results indicate that the proposed EMS in this paper can reduce the total cost by 8.65% in comparison with rule-based strategy and the longest prediction horizon can reach 15 s at least for real-Time application.
AB - This paper proposes a real-Time predictive energy management strategy (EMS) for a power-split plug-in hybrid electric bus (PHEB) to improve fuel economy by decreasing the total operation cost of fuel and electricity. Firstly, a two-dimensional (2-D) velocity prediction method is adopted to improve the accuracy of the prediction. Then, an online optimal controller is designed to distribute power flows optimally by tracking the SOC reference trajectory accurately. At last, comprehensive comparative simulations are conducted to validate the effectiveness of the proposed EMS in terms of fuel economy improvement and real-Time application performance. Simulation results indicate that the proposed EMS in this paper can reduce the total cost by 8.65% in comparison with rule-based strategy and the longest prediction horizon can reach 15 s at least for real-Time application.
KW - Plug-in hybrid electric bus
KW - energy management
KW - fuel economy
KW - model predictive control
KW - real-Time application
UR - http://www.scopus.com/inward/record.url?scp=85127516362&partnerID=8YFLogxK
U2 - 10.1109/ICIERA53202.2021.9726733
DO - 10.1109/ICIERA53202.2021.9726733
M3 - Conference contribution
AN - SCOPUS:85127516362
T3 - ICIERA 2021 - 1st International Conference on Industrial Electronics Research and Applications, Proceedings
BT - ICIERA 2021 - 1st International Conference on Industrial Electronics Research and Applications, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st International Conference on Industrial Electronics Research and Applications, ICIERA 2021
Y2 - 22 December 2021 through 24 December 2021
ER -