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Dual-layered Multi-Objective Genetic Algorithms (D-MOGA) : = A Robust Solution for Modern Engine Development and Calibrations.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Dual-layered Multi-Objective Genetic Algorithms (D-MOGA) :/
Reminder of title:	A Robust Solution for Modern Engine Development and Calibrations.
Author:	Padmavathy, Pragalath Thiruvengadam.
Description:	1 online resource (131 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
Contained By:	Dissertation Abstracts International78-10B(E).
Subject:	Mechanical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9781369765984

Dual-layered Multi-Objective Genetic Algorithms (D-MOGA) : = A Robust Solution for Modern Engine Development and Calibrations.
Padmavathy, Pragalath Thiruvengadam.

Dual-layered Multi-Objective Genetic Algorithms (D-MOGA) :A Robust Solution for Modern Engine Development and Calibrations. - 1 online resource (131 pages)

Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

Heavy-duty (HD) diesel engines are the primary propulsion systems used within the freight transportation sector and are subjected to stringent emissions regulations. The primary objective of this study is to develop a robust calibration technique for HD engine optimization in order to meet current and future regulated emissions standards during certification cycles and off-cycle vocation activities. Recently, California - Air Resources Board (C-ARB) has also shown interests in controlling off-cycle emissions from vehicles operating in California by funding projects such as the Ultra-Low NOx study by Sharp et. al [1]. Moreover, there is a major push for the complex real-world driving emissions testing protocol as the confirmatory and certification testing procedure in Europe and Asia through the United Nations - Economic Commission for Europe (UN-ECE) and International Organization for Standardization (ISO). This calls for more advanced and innovative approaches to optimize engine operation to meet the regulated certification levels.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369765984Subjects--Topical Terms:

557493
Mechanical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Dual-layered Multi-Objective Genetic Algorithms (D-MOGA) : = A Robust Solution for Modern Engine Development and Calibrations.
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245 1 0 $a Dual-layered Multi-Objective Genetic Algorithms (D-MOGA) : $b A Robust Solution for Modern Engine Development and Calibrations.
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300 $a 1 online resource (131 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
500 $a Adviser: Mridul Gautam.
502 $a Thesis (Ph.D.) $c West Virginia University $d 2017.
504 $a Includes bibliographical references
520 $a Heavy-duty (HD) diesel engines are the primary propulsion systems used within the freight transportation sector and are subjected to stringent emissions regulations. The primary objective of this study is to develop a robust calibration technique for HD engine optimization in order to meet current and future regulated emissions standards during certification cycles and off-cycle vocation activities. Recently, California - Air Resources Board (C-ARB) has also shown interests in controlling off-cycle emissions from vehicles operating in California by funding projects such as the Ultra-Low NOx study by Sharp et. al [1]. Moreover, there is a major push for the complex real-world driving emissions testing protocol as the confirmatory and certification testing procedure in Europe and Asia through the United Nations - Economic Commission for Europe (UN-ECE) and International Organization for Standardization (ISO). This calls for more advanced and innovative approaches to optimize engine operation to meet the regulated certification levels.
520 $a A robust engine calibration technique was developed using dual-layered multi-objective genetic algorithms (D-MOGA) to determine necessary engine control parameter settings. The study focused on reducing fuel consumption and lowering oxides of nitrogen (NOx) emissions, while simultaneously increasing exhaust temperatures for thermal management of exhaust after-treatment system. The study also focused on using D-MOGA to develop a calibration routine that simultaneously calibrates engine control parameters for transient certification cycles and vocational drayage operation. Several objective functions and alternate selection techniques for D-MOGA were analyzed to improve the optimality of the D-MOGA results.
520 $a The Low-NOx calibration for the Federal Test Procedure (FTP) which was obtained using the simple desirability approach was validated in the engine dynamometer test cell over the FTP and near-dock test cycles. In addition, the 2010 emissions compliant calibration was baselined for performance and emissions over the FTP and custom developed low-load Near-Dock engine dynamometer test cycles. Performance and emissions of the baseline calibrations showed a 63% increase in engine-out brake-specific NOx emissions and a proportionate 77% decrease in engine-out soot emissions over the Near-Dock cycle as compared to the FTP cycle. Engine dynamometer validation results of the Low-NOx FTP cycle calibration developed using D-MOGA, showed a 17% increase brake-specific NOx emissions over the FTP cycle, compared to the baseline calibrations. However, a 50% decrease in engine-out soot emissions and substantial increase in exhaust temperature were observed with no penalties on fuel consumption.
520 $a The tools developed in this study can play a role in meeting current and future regulations as well as bridging the gap between emissions during certification and real-world engine operations and eventually could play a vital role in meeting the National Ambient Air Quality Standards (NAAQS) in areas such as the port of Los Angeles, California in the South Coast Air Basin.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Mechanical engineering. $3 557493
655 7 $a Electronic books. $2 local $3 554714
690 $a 0548
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a West Virginia University. $b Mechanical and Aerospace Engineering. $3 1182910
773 0 $t Dissertation Abstracts International $g 78-10B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10275143 $z click for full text (PQDT)