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A driven approach to proper vehicle ...
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Memorial University of Newfoundland (Canada).
A driven approach to proper vehicle modeling and model validation .
Record Type:
Language materials, printed : Monograph/item
Title/Author:
A driven approach to proper vehicle modeling and model validation ./
Author:
Browne, Greg.
Description:
122 p.
Notes:
Source: Masters Abstracts International, Volume: 50-02, page: 1129.
Contained By:
Masters Abstracts International50-02.
Subject:
Engineering, Automotive. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR80796
ISBN:
9780494807965
A driven approach to proper vehicle modeling and model validation .
Browne, Greg.
A driven approach to proper vehicle modeling and model validation .
- 122 p.
Source: Masters Abstracts International, Volume: 50-02, page: 1129.
Thesis (M.Eng.)--Memorial University of Newfoundland (Canada), 2011.
As the use of model-based design in the automotive industry accelerates, so must the efficiency of modeling techniques and the thoroughness of model validation.
ISBN: 9780494807965Subjects--Topical Terms:
845411
Engineering, Automotive.
A driven approach to proper vehicle modeling and model validation .
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A driven approach to proper vehicle modeling and model validation .
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122 p.
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Source: Masters Abstracts International, Volume: 50-02, page: 1129.
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Thesis (M.Eng.)--Memorial University of Newfoundland (Canada), 2011.
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As the use of model-based design in the automotive industry accelerates, so must the efficiency of modeling techniques and the thoroughness of model validation.
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The research presented constructs an energy-based (bond graph) proper vehicle model. This model includes all significant system dynamics generated from pressing on the gas pedal to the resulting vehicle translation.
520
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The Model Order Reduction Algorithm provides a mechanism to quantitatively rank each element in the model and determine its contribution. The complete model, containing 65 elements, is reduced to 22 elements, provides simulation results of adequate agreement, and still contains over 98% of the original system energy. This proper model reduces the number of calculations by 86% and the simulation time by 92%.
520
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By using GPS and OBD-II technologies, the model is exercised by logging on-road real-world vehicle data. By comparing the logged data to the predictions of the model, it is shown that R2 > 0.9 can be achieved across different vehicles (compact sedan versus sport utility vehicle) and geographical routes.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR80796
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