Optimal control for Plug-in Hybrid Electric vehicle applications

Stephanie Stockar; Vincenzo Marano; Giorgio Rizzoni; Lino Guzzella

doi:10.1109/acc.2010.5530752

Optimal control for Plug-in Hybrid Electric vehicle applications

Stephanie Stockar, Vincenzo Marano, Giorgio Rizzoni, Lino Guzzella

Institute for Computational and Data Sciences (ICDS)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

63 Scopus citations

Abstract

Plug-In Hybrid Electric Vehicles (PHEVs) are a promising solution to reduce fuel consumption and emissions, due to their capability of storing energy in the battery through direct connection to the grid. In order to achieve the highest benefits from this technology, a suitable energy management strategy that optimizes the vehicle energy efficiency must be defined. The present work proposes a supervisory controller for PHEVs, which explicitly accounts for the on-board electricity consumption during vehicle operations. The approach is based on the formulation of an optimal control problem that is solved by the Pontryagin's minimum principle to produce a solution that can be implemented on-line. Simulation results are presented to illustrate the developed energy management strategy.

Original language	English (US)
Title of host publication	Proceedings of the 2010 American Control Conference, ACC 2010
Publisher	IEEE Computer Society
Pages	5024-5030
Number of pages	7
ISBN (Print)	9781424474264
DOIs	https://doi.org/10.1109/acc.2010.5530752
State	Published - 2010

Publication series

Name	Proceedings of the 2010 American Control Conference, ACC 2010

All Science Journal Classification (ASJC) codes

Control and Systems Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/acc.2010.5530752

Cite this

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title = "Optimal control for Plug-in Hybrid Electric vehicle applications",

abstract = "Plug-In Hybrid Electric Vehicles (PHEVs) are a promising solution to reduce fuel consumption and emissions, due to their capability of storing energy in the battery through direct connection to the grid. In order to achieve the highest benefits from this technology, a suitable energy management strategy that optimizes the vehicle energy efficiency must be defined. The present work proposes a supervisory controller for PHEVs, which explicitly accounts for the on-board electricity consumption during vehicle operations. The approach is based on the formulation of an optimal control problem that is solved by the Pontryagin's minimum principle to produce a solution that can be implemented on-line. Simulation results are presented to illustrate the developed energy management strategy.",

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Optimal control for Plug-in Hybrid Electric vehicle applications. / Stockar, Stephanie; Marano, Vincenzo; Rizzoni, Giorgio et al.

Proceedings of the 2010 American Control Conference, ACC 2010. IEEE Computer Society, 2010. p. 5024-5030 5530752 (Proceedings of the 2010 American Control Conference, ACC 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Guzzella, Lino

PY - 2010

Y1 - 2010

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AB - Plug-In Hybrid Electric Vehicles (PHEVs) are a promising solution to reduce fuel consumption and emissions, due to their capability of storing energy in the battery through direct connection to the grid. In order to achieve the highest benefits from this technology, a suitable energy management strategy that optimizes the vehicle energy efficiency must be defined. The present work proposes a supervisory controller for PHEVs, which explicitly accounts for the on-board electricity consumption during vehicle operations. The approach is based on the formulation of an optimal control problem that is solved by the Pontryagin's minimum principle to produce a solution that can be implemented on-line. Simulation results are presented to illustrate the developed energy management strategy.

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Optimal control for Plug-in Hybrid Electric vehicle applications

Abstract

Publication series

All Science Journal Classification (ASJC) codes

UN SDGs

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