A Novel Energy Management Strategy in Electric Vehicle Based on H∞ Self-gain Scheduled for Linear Parameter Varying Systems

Mehdi Sellali, Achour Betka, Abdesslem Djerdir, Y. Yang, Imene Bahri, Said Drid

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

The present paper exhibits a real time assessment of a robust Energy Management Strategy (EMS) for battery-super capacitor (SC) Hybrid Energy Storage System (HESS). The proposed algorithm, dedicated to an electric vehicular application, is based on a self-gain scheduled controller, which guarantees the H∞ performance for a class of linear parameter varying (LPV) systems. Assuming that the duty cycle of the involved DC-DC converters are considered as the variable parameters, that can be captured in real time, and forwarded to the controller to ensure both; the performance and robustness of the closed-loop system. The subsequent controller is therefore time-varying and it is automatically scheduled according to each parameter variation. This algorithm has been validated through experimental results provided by a tailor-made test bench including both the HESS and the vehicle traction emulation system. The experimental results demonstrate the overall stability of the system, where the proposed LPV supervisor successfully accomplishes a power frequency splitting in an adequate way, respecting the dynamic of the sources. The proposed solution provides significant performances for different speed levels.
Original languageEnglish
JournalIEEE Transactions on Energy Conversion
VolumePP
Issue number99
Pages (from-to)1-13
Number of pages13
ISSN0885-8969
DOIs
Publication statusAccepted/In press - Aug 2020

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