TY - JOUR
T1 - 混合动力电动汽车能量管理技术研究综述
AU - He, Hongwen
AU - Meng, Xiangfei
N1 - Publisher Copyright:
© 2022 Beijing Institute of Technology. All rights reserved.
PY - 2022/8
Y1 - 2022/8
N2 - Energy management strategy (EMS) is critical to improving the fuel economy, protecting the health status, and reducing the greenhouse gas emissions of hybrid electric vehicles (HEVs). However, due to the complex nonlinear structure of the power system and the real-time requirements of online applications, it is still a challenge task to develop an efficient EMS. Therefore, the evolution of energy management technology was summarized completely in this paper. Firstly, the electro-mechanical coupled systems used widely in HEVs and their topological structures and functional features were surveyed. Secondly, the research progress and development trend of EMS were analyzed synthetically. In addition, the technical advantages and disadvantages of various methods were evaluated based on fundamental technical indicators such as optimality and real-time performance, providing a reference for further engineering applications. Finally, the future research trend of EMS was prospected, hoping to provide a reference for the development of EMS under the intelligent connected environment.
AB - Energy management strategy (EMS) is critical to improving the fuel economy, protecting the health status, and reducing the greenhouse gas emissions of hybrid electric vehicles (HEVs). However, due to the complex nonlinear structure of the power system and the real-time requirements of online applications, it is still a challenge task to develop an efficient EMS. Therefore, the evolution of energy management technology was summarized completely in this paper. Firstly, the electro-mechanical coupled systems used widely in HEVs and their topological structures and functional features were surveyed. Secondly, the research progress and development trend of EMS were analyzed synthetically. In addition, the technical advantages and disadvantages of various methods were evaluated based on fundamental technical indicators such as optimality and real-time performance, providing a reference for further engineering applications. Finally, the future research trend of EMS was prospected, hoping to provide a reference for the development of EMS under the intelligent connected environment.
KW - energy management
KW - energy management strategy (EMS)
KW - hybrid electric vehicle
KW - machine learning
KW - model predictive control
UR - http://www.scopus.com/inward/record.url?scp=85138273705&partnerID=8YFLogxK
U2 - 10.15918/j.tbit1001-0645.2022.161
DO - 10.15918/j.tbit1001-0645.2022.161
M3 - 文章
AN - SCOPUS:85138273705
SN - 1001-0645
VL - 42
SP - 773
EP - 783
JO - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
JF - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
IS - 8
ER -