Technology Optimization Process for Heavy Hybrid Electric Vehicle Systems Using Computational Models

Michael O'Keefe

Technology Optimization Process for Heavy Hybrid Electric Vehicle Systems Using Computational Models

Michael O'Keefe

Center for Integrated Mobility Sciences

Research output: Contribution to conference › Paper

Abstract

We have developed a computer-based technology optimization process to define vehicle systems that meet specified goals and constraints using a minimum amount of resources. In this paper, we describe the technology optimization process, with a focus on technical target setting, and illustrate its use with a simple example.

Original language	American English
Number of pages	12
State	Published - 2005
Event	18th International Conference on Systems Engineering (ISCEng'05) - Las Vegas, Nevada Duration: 16 Aug 2005 → 18 Aug 2005

Conference

Conference	18th International Conference on Systems Engineering (ISCEng'05)
City	Las Vegas, Nevada
Period	16/08/05 → 18/08/05

NREL Publication Number

NREL/CP-540-38148

Keywords

advanced heavy hybrid propulsion system (ahhps)
computational models
computer-based technology optimization process
heavy hybrid electric vehicle
technical target
U.S. Department of Energy

Cite this

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abstract = "We have developed a computer-based technology optimization process to define vehicle systems that meet specified goals and constraints using a minimum amount of resources. In this paper, we describe the technology optimization process, with a focus on technical target setting, and illustrate its use with a simple example.",

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KW - advanced heavy hybrid propulsion system (ahhps)

KW - computational models

KW - computer-based technology optimization process

KW - heavy hybrid electric vehicle

KW - technical target

KW - U.S. Department of Energy

M3 - Paper

T2 - 18th International Conference on Systems Engineering (ISCEng'05)

Y2 - 16 August 2005 through 18 August 2005

ER -

Technology Optimization Process for Heavy Hybrid Electric Vehicle Systems Using Computational Models

Abstract

Conference

NREL Publication Number

Keywords

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Cite this