DIRECT as two-level optimization method for drive train design and control of hybrid electric vehicles

Christiane Bertram; Dominik Buecherl; Tom P. Kohler; Hans Georg Herzog

DIRECT as two-level optimization method for drive train design and control of hybrid electric vehicles

Christiane Bertram, Dominik Buecherl, Tom P. Kohler, Hans Georg Herzog

Associate Professorship of Energy Conversion Technology

Technical University of Munich

Research output: Contribution to conference › Paper › peer-review

4 Scopus citations

Abstract

The present paper deals with the optimization problem of hybrid electric vehicles' power trains. Different optimization algorithms are compared and the chosen algorithm DIviding RECTangles (DIRECT) is described in detail. An optimization method dealing with the strong dependency of the parameters is used to analyze the hybridization factor's influence. The developed method enables further to draw extensive conclusions from the optimization results. The achieved results concerning the optimal hybridization factor with respect to the energy storage's size are presented. Furthermore the influence of different driving cycles and combustion engines on the optimal hybridization factor is analyzed.

Original language	English
State	Published - 2010
Event	25th World Battery, Hybrid and Fuel Cell Electric Vehicle Symposium and Exhibition: Sustainable Mobility Revolution, EVS 2010 - Shenzhen, China Duration: 5 Nov 2010 → 9 Nov 2010

Conference

Conference	25th World Battery, Hybrid and Fuel Cell Electric Vehicle Symposium and Exhibition: Sustainable Mobility Revolution, EVS 2010
Country/Territory	China
City	Shenzhen
Period	5/11/10 → 9/11/10

Keywords

Dividing rectangles DIRECT
Energy storage
Hybrid electric vehicle
Hybridization factor
Optimization

Cite this

@conference{5c47c2e91a5d4dc789a7bcf666eda1ab,

title = "DIRECT as two-level optimization method for drive train design and control of hybrid electric vehicles",

abstract = "The present paper deals with the optimization problem of hybrid electric vehicles' power trains. Different optimization algorithms are compared and the chosen algorithm DIviding RECTangles (DIRECT) is described in detail. An optimization method dealing with the strong dependency of the parameters is used to analyze the hybridization factor's influence. The developed method enables further to draw extensive conclusions from the optimization results. The achieved results concerning the optimal hybridization factor with respect to the energy storage's size are presented. Furthermore the influence of different driving cycles and combustion engines on the optimal hybridization factor is analyzed.",

keywords = "Dividing rectangles DIRECT, Energy storage, Hybrid electric vehicle, Hybridization factor, Optimization",

author = "Christiane Bertram and Dominik Buecherl and Kohler, {Tom P.} and Herzog, {Hans Georg}",

year = "2010",

language = "English",

note = "25th World Battery, Hybrid and Fuel Cell Electric Vehicle Symposium and Exhibition: Sustainable Mobility Revolution, EVS 2010 ; Conference date: 05-11-2010 Through 09-11-2010",

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DIRECT as two-level optimization method for drive train design and control of hybrid electric vehicles. / Bertram, Christiane; Buecherl, Dominik; Kohler, Tom P. et al.
2010. Paper presented at 25th World Battery, Hybrid and Fuel Cell Electric Vehicle Symposium and Exhibition: Sustainable Mobility Revolution, EVS 2010, Shenzhen, China.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

T1 - DIRECT as two-level optimization method for drive train design and control of hybrid electric vehicles

AU - Bertram, Christiane

AU - Buecherl, Dominik

AU - Kohler, Tom P.

AU - Herzog, Hans Georg

PY - 2010

Y1 - 2010

N2 - The present paper deals with the optimization problem of hybrid electric vehicles' power trains. Different optimization algorithms are compared and the chosen algorithm DIviding RECTangles (DIRECT) is described in detail. An optimization method dealing with the strong dependency of the parameters is used to analyze the hybridization factor's influence. The developed method enables further to draw extensive conclusions from the optimization results. The achieved results concerning the optimal hybridization factor with respect to the energy storage's size are presented. Furthermore the influence of different driving cycles and combustion engines on the optimal hybridization factor is analyzed.

AB - The present paper deals with the optimization problem of hybrid electric vehicles' power trains. Different optimization algorithms are compared and the chosen algorithm DIviding RECTangles (DIRECT) is described in detail. An optimization method dealing with the strong dependency of the parameters is used to analyze the hybridization factor's influence. The developed method enables further to draw extensive conclusions from the optimization results. The achieved results concerning the optimal hybridization factor with respect to the energy storage's size are presented. Furthermore the influence of different driving cycles and combustion engines on the optimal hybridization factor is analyzed.

KW - Dividing rectangles DIRECT

KW - Energy storage

KW - Hybrid electric vehicle

KW - Hybridization factor

KW - Optimization

UR - http://www.scopus.com/inward/record.url?scp=84907401269&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:84907401269

T2 - 25th World Battery, Hybrid and Fuel Cell Electric Vehicle Symposium and Exhibition: Sustainable Mobility Revolution, EVS 2010

Y2 - 5 November 2010 through 9 November 2010

ER -

DIRECT as two-level optimization method for drive train design and control of hybrid electric vehicles

Abstract

Conference

Keywords

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