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Adaptive Optimal Supervisory Control Methods

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Hybrid Electric Vehicles

Part of the book series: SpringerBriefs in Electrical and Computer Engineering ((BRIEFSCONTROL))

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Abstract

The problem of designing a real-time implementable strategy to solve the energy management problem in hybrid electric vehicles and achieve a close-to-optimal solution has been the subject of extensive research over the last decade.

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Notes

  1. 1.

    In virtue of the equivalence between the two strategies shown in Chap. 6, in the rest of the chapter, we do not distinguish between ECMS and PMP, and we conduct the study of adaptive methods with reference to the PMP—but the same considerations apply to ECMS.

  2. 2.

    In some cases [1], PMP is used to indicate the offline implementation of the minimum principle with the optimal co-state, and ECMS for its online implementation based on adaptation of \(\lambda \).

  3. 3.

    Extensions have been proposed for plug-in HEVs, where the reference SOC is varied during the cycle to allow battery discharge [1, 18, 19].

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Author information

Authors and Affiliations

  1. Automotive Engineering Department, Clemson University, Greenville, SC, USA

    Simona Onori

  2. Dana Mechatronics Technology Center, Dana Holding Corporation, Rovereto, Italy

    Lorenzo Serrao

  3. Department of Mechanical and Aerospace Engineering and Center for Automotive Research, The Ohio State University, Columbus, OH, USA

    Giorgio Rizzoni

Authors
  1. Simona Onori
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  2. Lorenzo Serrao
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  3. Giorgio Rizzoni
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Correspondence to Simona Onori .

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Onori, S., Serrao, L., Rizzoni, G. (2016). Adaptive Optimal Supervisory Control Methods. In: Hybrid Electric Vehicles. SpringerBriefs in Electrical and Computer Engineering(). Springer, London. https://doi.org/10.1007/978-1-4471-6781-5_7

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  • DOI: https://doi.org/10.1007/978-1-4471-6781-5_7

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