Auto-Adaptive Filtering-Based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles

Jamila Snoussi, Seifeddine Ben Elghali, Mohamed Benbouzid and Mohamed Faouzi Mimouni
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Jamila Snoussi: National Engineering School of Monastir (ENIM), Monastir University, Monastir 5000, Tunisia
Seifeddine Ben Elghali: Laboratory of Information and Systems (UMR CNRS 7020 LIS), Aix-Marseille University, Marseille 13397, France
Mohamed Benbouzid: Institut de Recherche Dupuy de Lôme (UMR CNRS 6027 IRDL), University of Brest, Brest 29238, France and with the Shanghai Maritime University, Shanghai 201306, China
Mohamed Faouzi Mimouni: National Engineering School of Monastir (ENIM), Monastir University, Monastir 5000, Tunisia

Energies, 2018, vol. 11, issue 8, 1-20

Abstract: The global need to solve pollution problems has conducted automotive engineers to promote the development and the use of electric vehicle technologies. This paper focuses on the fuel cell hybrid electric vehicle which uses a proton exchange membrane fuel cell as a main source associated to hybrid storage device: lithium ion battery and ultracapacitors. A common interest in such technology is to spread out the energy flow between its different sources in order to satisfy the power demand for any requested mission. However, the challenging task stills the optimization of this split to reduce hydrogen consumption and respect, at the same time, the system limitations such as admissible limits of storage system capacities and battery current variation. An adaptive filtering-based energy management strategy is proposed in this paper to ensure an optimum distribution of the energy between the sources taking into account dynamic and energetic constraints of each device. For more performance, a fuzzy logic system is used to adapt the frequency of separation with the system state evolution. A sliding mode control is applied to control electric characteristics (voltage and currents) in the considered hybrid power supply. Simulation results, obtained under MATLAB ® /SimPowerSystems ® for four driving cycles are presented. The proposed strategy achieved good performances by respecting the ultracapacitors state of charge while preserving the battery lifetime under various driving missions.

Keywords: fuel cell hybrid electric vehicle; Lithium ion battery; ultracapacitors; frequency energy management; sliding mode control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

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