Journal
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 69, Issue 12, Pages 14674-14688Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2020.3034454
Keywords
Energy management; fuel cell; fuzzy control; model predictive control; Kalman filter
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Funding
- Australian Research Council [DP170102644]
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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.
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