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Development of system analysis metho...

Baglione, Melody L.

Development of system analysis methodologies and tools for modeling and optimizing vehicle system efficiency.

レコード種別:	コンピュータ・メディア : 単行資料
タイトル / 著者:	Development of system analysis methodologies and tools for modeling and optimizing vehicle system efficiency./
著者:	Baglione, Melody L.
記述:	193 p.
注記:	Source: Dissertation Abstracts International, Volume: 68-10, Section: B, page: 6904.
含まれています:	Dissertation Abstracts International68-10B.
主題:	Engineering, Automotive. -
電子資源:	Download PDF (下載PDF全文)
国際標準図書番号 (ISBN):	9780549304050

Development of system analysis methodologies and tools for modeling and optimizing vehicle system efficiency.
Baglione, Melody L.

Development of system analysis methodologies and tools for modeling and optimizing vehicle system efficiency. - 193 p.

Source: Dissertation Abstracts International, Volume: 68-10, Section: B, page: 6904.

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

Optimizing the vehicle system is essential for achieving higher fuel efficiency. This dissertation addresses the need to better understand energy demand from a vehicle subsystem standpoint and tackles the challenge of optimal hardware and control system design.

ISBN: 9780549304050Subjects--Topical Terms:

1000006179
Engineering, Automotive.

Development of system analysis methodologies and tools for modeling and optimizing vehicle system efficiency.
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245 1 0 $a Development of system analysis methodologies and tools for modeling and optimizing vehicle system efficiency.
300 $a 193 p.
500 $a Source: Dissertation Abstracts International, Volume: 68-10, Section: B, page: 6904.
500 $a Advisers: Dionissios N. Assanis; Jun Ni.
502 $a Thesis (Ph.D.)--University of Michigan, 2007.
520 $a Optimizing the vehicle system is essential for achieving higher fuel efficiency. This dissertation addresses the need to better understand energy demand from a vehicle subsystem standpoint and tackles the challenge of optimal hardware and control system design.
520 $a An energy analysis methodology and MatlabRTM/Simulink RTM based tool are developed to account for where the fuel energy supplied to a vehicle system is demanded. A hybrid semi-empirical and analytical approach that combines first principles with detailed component speed and load data is proposed. The methodology and tool are applied to account for the instantaneous and accumulated vehicle subsystem energy usage over a given drive cycle. A comparison of the prevailing fuel economy factors for city and highway driving are presented. Incremental vehicle subsystem changes that account for a fraction of the total energy demand are analyzed to determine individual effects on overall fuel economy.
520 $a A reverse dynamic optimization methodology is proposed for optimal powertrain integration and control design. A reverse tractive road load demand model developed in MatlabRTM/SimulinkRTM propagates the required wheel torque and speed derived from vehicle speed and road grade through the powertrain system to determine the required fuel flow for all possible states within the hardware constraints. The control strategy is treated as a multi-stage, multi-dimension decision process, where dynamic programming is applied to find an optimal control policy that minimizes the accumulated fuel flow over a drive cycle.
520 $a The reverse dynamic optimization methodology and tool are used to assess and develop transmission gear shift, torque converter lock-up clutch, and pedal control strategies that are catered to specific vehicle applications. The reverse model and dynamic optimization technique are extended to virtually optimize variable displacement engine operation taking gear and clutch control interaction effects into account. The reverse model is used for establishing design criteria, such as minimum engine part throttle torque requirements, by determining the required speeds and loads to traverse drive cycles. The advantages of the reverse dynamic optimization approach are demonstrated by performing powertrain matching analyses (i.e., vehicle attribute sensitivity analysis; optimal engine, transmission and axle selection; and variable displacement effects) and key system integration concepts are revealed.
590 $a School code: 0127.
650 4 $a Engineering, Automotive. $3 1000006179
650 4 $a Engineering, Mechanical. $3 170925
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710 2 $a University of Michigan. $3 1000005611
773 0 $t Dissertation Abstracts International $g 68-10B.
790 1 0 $a Assanis, Dionissios N., $e advisor
790 1 0 $a Ni, Jun, $e advisor
790 $a 0127
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3287449 $z Download PDF (下載PDF全文)

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