TY - JOUR
T1 - Model predictive control power management strategies for HEVs
T2 - A review
AU - Huang, Yanjun
AU - Wang, Hong
AU - Khajepour, Amir
AU - He, Hongwen
AU - Ji, Jie
N1 - Publisher Copyright:
© 2016
PY - 2017/2/15
Y1 - 2017/2/15
N2 - This paper presents a comprehensive review of power management strategy (PMS) utilized in hybrid electric vehicles (HEVs) with an emphasis on model predictive control (MPC) based strategies for the first time. Research on MPC-based power management systems for HEVs has intensified recently due to its many inherent merits. The categories of the existing PMSs are identified from the latest literature, and a brief study of each type is conducted. Then, the MPC approach is introduced and its advantages are discussed. Based on the acquisition method of driver behavior used for state prediction and the dynamic model used, the MPC is classified and elaborated. Factors that affect the performance of the MPC are put forward, including prediction accuracy, design parameters, and solvers. Finally, several important issues in the application of MPC-based power management strategies and latest developing trends are discussed. This paper not only provides a comprehensive analysis of MPC-based power management strategies for HEVs but also puts forward the future and emphasis of future study, which will promote the development of energy management controller with high performance and low cost for HEVs.
AB - This paper presents a comprehensive review of power management strategy (PMS) utilized in hybrid electric vehicles (HEVs) with an emphasis on model predictive control (MPC) based strategies for the first time. Research on MPC-based power management systems for HEVs has intensified recently due to its many inherent merits. The categories of the existing PMSs are identified from the latest literature, and a brief study of each type is conducted. Then, the MPC approach is introduced and its advantages are discussed. Based on the acquisition method of driver behavior used for state prediction and the dynamic model used, the MPC is classified and elaborated. Factors that affect the performance of the MPC are put forward, including prediction accuracy, design parameters, and solvers. Finally, several important issues in the application of MPC-based power management strategies and latest developing trends are discussed. This paper not only provides a comprehensive analysis of MPC-based power management strategies for HEVs but also puts forward the future and emphasis of future study, which will promote the development of energy management controller with high performance and low cost for HEVs.
KW - Hybrid electric vehicles
KW - Model predictive control
KW - Power management strategy
UR - http://www.scopus.com/inward/record.url?scp=85003935989&partnerID=8YFLogxK
U2 - 10.1016/j.jpowsour.2016.11.106
DO - 10.1016/j.jpowsour.2016.11.106
M3 - Review article
AN - SCOPUS:85003935989
SN - 0378-7753
VL - 341
SP - 91
EP - 106
JO - Journal of Power Sources
JF - Journal of Power Sources
ER -