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Advanced efficiency solutions for hy...

Concordia University (Canada).

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Advanced efficiency solutions for hybrid electric vehicles (HEVs).

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Advanced efficiency solutions for hybrid electric vehicles (HEVs)./
Author:	Li, Xin.
Description:	88 p.
Notes:	Source: Masters Abstracts International, Volume: 47-04, page: 2317.
Contained By:	Masters Abstracts International47-04.
Subject:	Energy. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR45490
ISBN:	9780494454909

Advanced efficiency solutions for hybrid electric vehicles (HEVs).
Li, Xin.

Advanced efficiency solutions for hybrid electric vehicles (HEVs). - 88 p.

Source: Masters Abstracts International, Volume: 47-04, page: 2317.

Thesis (M.A.Sc.)--Concordia University (Canada), 2008.

As an alternative to conventional vehicles (CVs), hybrid electric vehicles (HEVs) are touted to be a practically attractive measure to create an energy-wise and sustainable society. By employing electric energy as one of the traction energy sources, HEVs are able to reduce costly fuel consumption as well as greenhouse gas (GHG) emissions. There are some commercially available HEVs in the market, employing various drive train configurations; however, their drive trains and control strategies are not optimally designed. In this thesis, parametric and power component stage based efficiency analysis methods are introduced to assess the overall drive train efficiencies for different HEV configurations. Hence, it is possible to find the key parameters that significantly affect the overall drive train efficiency. A mid-sized sport utility vehicle (SUV) is modeled in different hybrid configurations within the Advanced Vehicle Simulator (ADVISOR) software. Simulations are carried out based on the modeled SUV over varied load demands. The thesis also defines regenerative braking efficiency and the term "hybridization factor" for series and parallel HEVs. In addition, a method to analyze and calculate regenerative braking efficiency is also introduced. Finally, the thesis focuses on optimizing system control strategies for series and parallel HEVs, to enhance their regenerative braking efficiency. The optimized fuzzy logic and electric assist control strategies are simulated and tested in ADVISOR, thus providing the data for eventually designing a novel control strategy, to improve the overall drive train efficiency.

ISBN: 9780494454909Subjects--Topical Terms:

876794
Energy.

Advanced efficiency solutions for hybrid electric vehicles (HEVs).
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020 $a 9780494454909
035 $a (UMI)AAIMR45490
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100 1 $a Li, Xin. $3 999627
245 1 0 $a Advanced efficiency solutions for hybrid electric vehicles (HEVs).
300 $a 88 p.
500 $a Source: Masters Abstracts International, Volume: 47-04, page: 2317.
502 $a Thesis (M.A.Sc.)--Concordia University (Canada), 2008.
520 $a As an alternative to conventional vehicles (CVs), hybrid electric vehicles (HEVs) are touted to be a practically attractive measure to create an energy-wise and sustainable society. By employing electric energy as one of the traction energy sources, HEVs are able to reduce costly fuel consumption as well as greenhouse gas (GHG) emissions. There are some commercially available HEVs in the market, employing various drive train configurations; however, their drive trains and control strategies are not optimally designed. In this thesis, parametric and power component stage based efficiency analysis methods are introduced to assess the overall drive train efficiencies for different HEV configurations. Hence, it is possible to find the key parameters that significantly affect the overall drive train efficiency. A mid-sized sport utility vehicle (SUV) is modeled in different hybrid configurations within the Advanced Vehicle Simulator (ADVISOR) software. Simulations are carried out based on the modeled SUV over varied load demands. The thesis also defines regenerative braking efficiency and the term "hybridization factor" for series and parallel HEVs. In addition, a method to analyze and calculate regenerative braking efficiency is also introduced. Finally, the thesis focuses on optimizing system control strategies for series and parallel HEVs, to enhance their regenerative braking efficiency. The optimized fuzzy logic and electric assist control strategies are simulated and tested in ADVISOR, thus providing the data for eventually designing a novel control strategy, to improve the overall drive train efficiency.
590 $a School code: 0228.
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650 4 $a Engineering, Automotive. $3 1018477
650 4 $a Engineering, Electronics and Electrical. $3 626636
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710 2 $a Concordia University (Canada). $3 1018569
773 0 $t Masters Abstracts International $g 47-04.
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792 $a 2008
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