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Optimization and Optimal Control in Automotive Systems pp 199–218Cite as

Model-Based Optimal Energy Management Strategies for Hybrid Electric Vehicles

Part of the Lecture Notes in Control and Information Sciences book series (LNCIS,volume 455)

Abstract

Methods from optimal control theory have been used since the past decade to design model-based energy management strategies for hybrid electric vehicles (HEVs). These strategies are usually designed as solutions to a finite-time horizon, constrained optimal control problem that guarantees optimality upon perfect knowledge of the driving cycle. Properly adapted these strategies can be used for real-time implementation (without knowledge of the future driving mission) at the cost of either high (sometime prohibitive) computational burden or high memory requirement to store high-dimensional off-line generated look-up tables. These issues have motivated the research reported in this chapter. We propose to address the optimal energy management problem over an infinite time horizon by formulating the problem as a nonlinear, nonquadratic optimization problem. An analytical supervisory controller is designed that ensures stability, optimality with respect to fuel consumption, ease of implementation in real-time application, fast execution and low control parameter sensitivity. The approach generates a drive cycle independent control law without requiring discounted cost or shortest path stochastic dynamic programming introduced in the prior literature.

Keywords

  • Optimal Control Problem
  • Energy Management
  • Driving Cycle
  • Drive Cycle
  • Battery Energy

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

  1. 1.

    Results from [13] and [14] prove the uniqueness of the solution of the optimal control problem under the satisfied assumption of constant battery efficiency over the \(SOC\) range of operation.

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Acknowledgments

The author would like to deeply thank Roberto Mura for taking this research a step forward, Lorenzo Serrao for the enjoyable and productive discussions, Yann Guezennec, Giorgio Rizzoni, and Stephen Yuorkovich for the productive iterations.

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Authors and Affiliations

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

    Simona Onori

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  1. Simona Onori
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Correspondence to Simona Onori .

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Editors and Affiliations

  1. Institute for Design and Control of Mechatronical Systems, Johannes Kepler, University Linz, Linz, Austria

    Harald Waschl

  2. Department of Aerospace Engineering, University of Michigan, Ann Arbor, Michigan, USA

    Ilya Kolmanovsky

  3. Department of Mechanical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands

    Maarten Steinbuch

  4. Institute for Design and Control of Mechatronical Systems, Johannes Kepler University Linz, Linz, Austria

    Luigi del Re

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Onori, S. (2014). Model-Based Optimal Energy Management Strategies for Hybrid Electric Vehicles. In: Waschl, H., Kolmanovsky, I., Steinbuch, M., del Re, L. (eds) Optimization and Optimal Control in Automotive Systems. Lecture Notes in Control and Information Sciences, vol 455. Springer, Cham. https://doi.org/10.1007/978-3-319-05371-4_12

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  • DOI: https://doi.org/10.1007/978-3-319-05371-4_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05370-7

  • Online ISBN: 978-3-319-05371-4

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