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IEEE Transactions on Vehicular Technology
Article . 2020 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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A New Energy Management Strategy for Multimode Power-Split Hybrid Electric Vehicles

Authors: Giuseppe Buccoliero; Pier Giuseppe Anselma; Saeed Amirfarhangi Bonab; Giovanni Belingardi; Ali Emadi;

A New Energy Management Strategy for Multimode Power-Split Hybrid Electric Vehicles

Abstract

Among the hybrid electric vehicle categories, the multimode power-split allows to fully exploit the advantages related to the powertrain electrification. However, together with the increased flexibility, it comes with greater difficulty in defining an effective control strategy, both in terms of predicted fuel consumption and computational cost. To overcome the limits of the most diffused energy management strategies, slope-weighted energy-based rapid control analysis (SERCA) has been recently proposed. Nevertheless, so far, the algorithm has been applied to powertrains characterized by two operative modes solely. In this paper, we first present the inconsistency of SERCA applied to the whole set of multimode power-split arrangements. Subsequently, after correlating this divergence to the mode selection process, to overcome this draft, we introduce a novel strategy called SERCA+. This algorithm is proven to be robust and to achieve results close to the optimum benchmark with an insignificant increase in computational cost. Therefore, SERCA+ could potentially find application in design methodologies for multimode power-split HEVs to accelerate the overall vehicle design process.

Country
Italy
Keywords

Electric vehicles, energy management, fast analysis, hybrid, multimode, optimal control, power-split powertrain

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    40
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
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    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
40
Top 1%
Top 10%
Top 1%
Green