Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/132394
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Type: Journal article
Title: Fuzzy model based control for energy management and optimization in fuel cell vehicles
Author: Shen, D.
Lim, C.C.
Shi, P.
Citation: IEEE Transactions on Vehicular Technology, 2020; 69(12):14674-14688
Publisher: Institute of Electrical and Electronics Engineers
Issue Date: 2020
ISSN: 0018-9545
1939-9359
Statement of
Responsibility: 
Di Shen, Cheng-Chew Lim, Peng Shi
Abstract: Energy management system is vital to fuel cell vehicles in fuel economy and system durability. In this paper, we investigate the problem of controlling energy flow in charge- sustaining fuel cell vehicles by considering system stability, optimality and fuel cell durability. The energy management problem is transformed to a nonlinear optimization problem with multi-objectives in order to improve fuel economy, maintain battery state of charge, and reduce the incidence of factors affecting the fuel cell performance degradation. A robust model- predictive-based fuzzy control method is employed to design the nonlinear control law. The energy management system is capable of coordinating with a fuel cell stack state of health estimator and an energy storage system scheduler to achieve the optimization objectives in the presence of uncertainty of the driver’s power demand. The effectiveness of the new design technique developed is demonstrated by conducting studies on control performance over typical urban/highway driving scenarios.
Keywords: Energy management; fuel cell; fuzzy control; model predictive control; Kalman filter
Rights: © 2020 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
DOI: 10.1109/TVT.2020.3034454
Grant ID: http://purl.org/au-research/grants/arc/DP170102644
Published version: http://dx.doi.org/10.1109/tvt.2020.3034454
Appears in Collections:Aurora harvest 8
Electrical and Electronic Engineering publications

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