TY - JOUR
T1 - Online Energy Management Strategy of Fuel Cell Hybrid Electric Vehicles
T2 - A Fractional-Order Extremum Seeking Method
AU - Zhou, Daming
AU - Al-Durra, Ahmed
AU - Matraji, Imad
AU - Ravey, Alexandre
AU - Gao, Fei
N1 - Funding Information:
Manuscript received March 30, 2017; revised December 13, 2017 and January 19, 2018; accepted January 21, 2018. Date of publication February 8, 2018; date of current version April 2, 2018. This work was supported by the European Commission H2020 grant ESPESA (H2020-TWINN-2015) EU Grant agreement No: 692224. (Corresponding author: Daming Zhou.) D. Zhou is with the FEMTO-ST (UMR CNRS 6174), Department of Energy, and FCLAB (FR CNRS 3539), University of Bourgogne Franche-Comte, University of Technology of Belfort-Montbeliard, Belfort F-90010, France, and also with the School of Astronautics, Northwestern Polytechnical University, Xi’an 710072, China (e-mail: [email protected]).
Publisher Copyright:
© 1982-2012 IEEE.
PY - 2018/8
Y1 - 2018/8
N2 - In this paper, an online energy management control strategy is proposed based on a novel fractional-order extremum seeking (ES) method. The proposed method is an online adaptive optimization algorithm, which can be effectively used in the applications of fuel cell hybrid electric vehicles. Compared with the traditional integer-order ES method, the presented method uses Oustaloup approximation based fractional-order calculus in order to achieve faster convergence speed and higher robustness. A detailed mathematical analysis of the proposed method is presented to give a stability proof and shows how the fractional-order calculus improves the integer-order ES method. In order to support the stability analysis results and demonstrate the effectiveness and robustness of the proposed method, a hardware-in-the-loop test bench is developed to provide two experimental case studies. Experimental results show that, by using the presented fractional-order ES approach, the operation points of a proton exchange membrane fuel cell stack system can be effectively controlled in its maximum efficiency area. In addition, the fuel cell system durability can be improved.
AB - In this paper, an online energy management control strategy is proposed based on a novel fractional-order extremum seeking (ES) method. The proposed method is an online adaptive optimization algorithm, which can be effectively used in the applications of fuel cell hybrid electric vehicles. Compared with the traditional integer-order ES method, the presented method uses Oustaloup approximation based fractional-order calculus in order to achieve faster convergence speed and higher robustness. A detailed mathematical analysis of the proposed method is presented to give a stability proof and shows how the fractional-order calculus improves the integer-order ES method. In order to support the stability analysis results and demonstrate the effectiveness and robustness of the proposed method, a hardware-in-the-loop test bench is developed to provide two experimental case studies. Experimental results show that, by using the presented fractional-order ES approach, the operation points of a proton exchange membrane fuel cell stack system can be effectively controlled in its maximum efficiency area. In addition, the fuel cell system durability can be improved.
KW - Extremum seeking (ES) method
KW - fractional-order calculus
KW - fuel cell hybrid electric vehicle (FCHEV)
KW - online energy management strategy
UR - http://www.scopus.com/inward/record.url?scp=85041543274&partnerID=8YFLogxK
U2 - 10.1109/TIE.2018.2803723
DO - 10.1109/TIE.2018.2803723
M3 - Article
AN - SCOPUS:85041543274
SN - 0278-0046
VL - 65
SP - 6787
EP - 6799
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
IS - 8
ER -
