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Article Dans Une Revue IEEE Transactions on Energy Conversion Année : 2021

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

Résumé

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.
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Dates et versions

hal-03705651 , version 1 (27-06-2022)

Identifiants

  • HAL Id : hal-03705651 , version 1

Citer

Mehdi Sellali, Achour Bekta, Abdesslem Djerdir, Yongheng Yang, Imen Bahri, et al.. A Novel Energy Management Strategy in Electric Vehicle Based on H∞ Self-Gain Scheduled for Linear Parameter Varying Systems. IEEE Transactions on Energy Conversion, 2021, 36 (2), pp.767 - 778. ⟨hal-03705651⟩
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