Receding horizon real-time energy management strategy for hybrid vehicles

Bram Jager, de; T.A.C. Keulen, van

doi:10.1115/IMECE2013-64699

Receding horizon real-time energy management strategy for hybrid vehicles

Bram Jager, de, T.A.C. Keulen, van

Control Systems Technology

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

1 Citaat (Scopus)

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Indirect optimal control and dynamic programming are combined in a receding horizon controller to obtain an energy management strategy for hybrid vehicles. This combination permits the use of inaccurate predictions of the future, instead of requiring exact knowledge, and allows the use of mixed state-control constraints, like voltage constraints for batteries. The controller can run in real-time on commodity hardware and, using a prediction of the future based on geographic information only, obtains a fuel use within 0.2% of the optimal fuel use computed with the exact speed and power trajectory of the vehicle known in advance. All this for a planned distance of more than 500 [km].

Originele taal-2	Engels
Titel	ASME 2013 International Mechanical Engineering Congress and Exposition (IMECEB 2013), San Diego, California, USA, November 15–21, 2013
Subtitel	Volume 4A: Dynamics, Vibration and Control
Uitgeverij	American Society of Mechanical Engineers
ISBN van geprinte versie	978-0-7918-5624-6
DOI's	https://doi.org/10.1115/IMECE2013-64699
Status	Gepubliceerd - 2013

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10.1115/IMECE2013-64699

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Jager, de, B., & Keulen, van, T. A. C. (2013). Receding horizon real-time energy management strategy for hybrid vehicles. In ASME 2013 International Mechanical Engineering Congress and Exposition (IMECEB 2013), San Diego, California, USA, November 15–21, 2013: Volume 4A: Dynamics, Vibration and Control American Society of Mechanical Engineers. https://doi.org/10.1115/IMECE2013-64699

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title = "Receding horizon real-time energy management strategy for hybrid vehicles",

abstract = "Indirect optimal control and dynamic programming are combined in a receding horizon controller to obtain an energy management strategy for hybrid vehicles. This combination permits the use of inaccurate predictions of the future, instead of requiring exact knowledge, and allows the use of mixed state-control constraints, like voltage constraints for batteries. The controller can run in real-time on commodity hardware and, using a prediction of the future based on geographic information only, obtains a fuel use within 0.2% of the optimal fuel use computed with the exact speed and power trajectory of the vehicle known in advance. All this for a planned distance of more than 500 [km].",

author = "{Jager, de}, Bram and {Keulen, van}, T.A.C.",

year = "2013",

doi = "10.1115/IMECE2013-64699",

language = "English",

isbn = "978-0-7918-5624-6",

booktitle = "ASME 2013 International Mechanical Engineering Congress and Exposition (IMECEB 2013), San Diego, California, USA, November 15–21, 2013",

publisher = "American Society of Mechanical Engineers",

address = "United States",

}

Jager, de, B & Keulen, van, TAC 2013, Receding horizon real-time energy management strategy for hybrid vehicles. in ASME 2013 International Mechanical Engineering Congress and Exposition (IMECEB 2013), San Diego, California, USA, November 15–21, 2013: Volume 4A: Dynamics, Vibration and Control. American Society of Mechanical Engineers. https://doi.org/10.1115/IMECE2013-64699

Receding horizon real-time energy management strategy for hybrid vehicles. / Jager, de, Bram; Keulen, van, T.A.C.
ASME 2013 International Mechanical Engineering Congress and Exposition (IMECEB 2013), San Diego, California, USA, November 15–21, 2013: Volume 4A: Dynamics, Vibration and Control. American Society of Mechanical Engineers, 2013.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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AU - Keulen, van, T.A.C.

PY - 2013

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N2 - Indirect optimal control and dynamic programming are combined in a receding horizon controller to obtain an energy management strategy for hybrid vehicles. This combination permits the use of inaccurate predictions of the future, instead of requiring exact knowledge, and allows the use of mixed state-control constraints, like voltage constraints for batteries. The controller can run in real-time on commodity hardware and, using a prediction of the future based on geographic information only, obtains a fuel use within 0.2% of the optimal fuel use computed with the exact speed and power trajectory of the vehicle known in advance. All this for a planned distance of more than 500 [km].

AB - Indirect optimal control and dynamic programming are combined in a receding horizon controller to obtain an energy management strategy for hybrid vehicles. This combination permits the use of inaccurate predictions of the future, instead of requiring exact knowledge, and allows the use of mixed state-control constraints, like voltage constraints for batteries. The controller can run in real-time on commodity hardware and, using a prediction of the future based on geographic information only, obtains a fuel use within 0.2% of the optimal fuel use computed with the exact speed and power trajectory of the vehicle known in advance. All this for a planned distance of more than 500 [km].

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DO - 10.1115/IMECE2013-64699

M3 - Conference contribution

SN - 978-0-7918-5624-6

BT - ASME 2013 International Mechanical Engineering Congress and Exposition (IMECEB 2013), San Diego, California, USA, November 15–21, 2013

PB - American Society of Mechanical Engineers

ER -

Receding horizon real-time energy management strategy for hybrid vehicles

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