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Multi-horizon MPC and Its Application to the Integrated Power and Thermal Management of Electrified Vehicles

Author

Listed:
  • Qiuhao Hu

    (University of Michigan)

  • Mohammad Reza Amini

    (University of Michigan)

  • Ilya Kolmanovsky

    (University of Michigan)

  • Jing Sun

    (University of Michigan)

Abstract

The chapter provides an overview of several recent applications of model predictive control (MPC) to coordinated power and thermal management in connected and automated electrified vehicles. Such applications of MPC face significant challenges due to the need to accommodate different timescales of faster power and slower thermal dynamics, interactive constraints, and the need to generate and accommodate long-term vehicle speed and traction power forecasts in the optimization. It will be shown that a multi-horizon formulation of MPC consisting of a shorter receding horizon phase and a longer shrinking horizon phase can help address these challenges. Perspectives on creating forecasts and exploiting multi-horizon MPC for energy efficiency optimization based on several case studies are summarized.

Suggested Citation

  • Qiuhao Hu & Mohammad Reza Amini & Ilya Kolmanovsky & Jing Sun, 2025. "Multi-horizon MPC and Its Application to the Integrated Power and Thermal Management of Electrified Vehicles," Dynamic Modeling and Econometrics in Economics and Finance,, Springer.
    • Handle: RePEc:spr:dymchp:978-3-031-85256-5_1
    DOI: 10.1007/978-3-031-85256-5_1
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