東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Modeling, configuration and control ...

Liu, Jinming.

Linked to FindBook

Google Book

Amazon

博客來

Modeling, configuration and control optimization of power-split hybrid vehicles.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Modeling, configuration and control optimization of power-split hybrid vehicles./
Author:	Liu, Jinming.
Description:	164 p.
Notes:	Adviser: Huei Peng.
Contained By:	Dissertation Abstracts International68-11B.
Subject:	Engineering, Automotive. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3287571
ISBN:	9780549305125

Modeling, configuration and control optimization of power-split hybrid vehicles.
Liu, Jinming.

Modeling, configuration and control optimization of power-split hybrid vehicles. - 164 p.

Adviser: Huei Peng.

Thesis (Ph.D.)--University of Michigan, 2007.

Hybrid electric vehicles (HEV) represent one of the most promising fuel-saving technologies in the short-term for improving fuel economy of ground vehicles. Their viability has been amply demonstrated in a few successful commercial models. Among the common configurations, the power-split (i.e., combined parallel/series) configuration offers superior design and control flexibility and achieves highest overall efficiency. Therefore, most of the full-hybrid vehicles planned for the near future from Toyota, Lexus, GM, Chrysler, and Ford are all split hybrids. In this dissertation, a model-based configuration and control optimization analysis of power-split HEV is presented.

ISBN: 9780549305125Subjects--Topical Terms:

1018477
Engineering, Automotive.

Modeling, configuration and control optimization of power-split hybrid vehicles.
LDR:03390nam 2200325 a 45 001 949033
005 20110525
008 110525s2007 ||||||||||||||||| ||eng d
020 $a 9780549305125
035 $a (UMI)AAI3287571
035 $a AAI3287571
040 $a UMI $c UMI
100 1 $a Liu, Jinming. $3 1272411
245 1 0 $a Modeling, configuration and control optimization of power-split hybrid vehicles.
300 $a 164 p.
500 $a Adviser: Huei Peng.
500 $a Source: Dissertation Abstracts International, Volume: 68-11, Section: B, page: 7623.
502 $a Thesis (Ph.D.)--University of Michigan, 2007.
520 $a Hybrid electric vehicles (HEV) represent one of the most promising fuel-saving technologies in the short-term for improving fuel economy of ground vehicles. Their viability has been amply demonstrated in a few successful commercial models. Among the common configurations, the power-split (i.e., combined parallel/series) configuration offers superior design and control flexibility and achieves highest overall efficiency. Therefore, most of the full-hybrid vehicles planned for the near future from Toyota, Lexus, GM, Chrysler, and Ford are all split hybrids. In this dissertation, a model-based configuration and control optimization analysis of power-split HEV is presented.
520 $a An integrated dynamic model was first developed for power-split HEV powertrain systems. From this simulation model, a math-based universal model format is generalized. It presents different designs of power-split powertrains regardless of the various connections between gear nodes and power sources. Based on this universal format, a methodology that automatically generates dynamic models is developed. It not only enables rapid generation of powertrain models, but also allows the process of automatically exploring possible configuration designs.
520 $a We next introduce a design screening process and a combined configuration and control optimization strategy. In the design screening process, various design requirements including transmission efficiency, drivability, power source component sizing are utilized to evaluate possible configurations and select valid design candidates. In the combined configuration and control optimization strategy, a control design procedure based on deterministic dynamic programming (DDP) was employed to find the optimal operation of the vehicle system and achieve the performance benchmarks for different configuration candidates. The optimal design solution is then achieved by comparing these benchmarks. This methodology allows design engineers to study powertrain configurations more scientifically and efficiently.
520 $a Finally, with the DDP suggesting the potential performance benchmark of the selected powertrain configuration, two alternative control strategies, stochastic dynamic programming and equivalent consumption minimization strategy, are developed to approach this performance benchmark. Both of these two control designs can be implemented in real-time and show close agreement with the DDP results in the simulation.
590 $a School code: 0127.
650 4 $a Engineering, Automotive. $3 1018477
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Engineering, Mechanical. $3 783786
690 $a 0540
690 $a 0544
690 $a 0548
710 2 $a University of Michigan. $3 777416
773 0 $t Dissertation Abstracts International $g 68-11B.
790 $a 0127
790 1 0 $a Peng, Huei, $e advisor
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3287571