System identification of a spark ignition engine for natural gas injection rate control (Record no. 117244)

MARC details
000 -LEADER
fixed length control field 03827nam a2200457 a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260818223752.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140619s2011 th ad ||| 000 0 eng d
035 ## - SYSTEM CONTROL NUMBER
System control number .b12133772
099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Classification number AIT Thesis no.ISE-11-09
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Suradech Doungpummet
245 10 - TITLE STATEMENT
Title System identification of a spark ignition engine for natural gas injection rate control
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Pathum Thani :
Name of publisher, distributor, etc. Asian Institute of Technology,
Date of publication, distribution, etc. 2011
300 ## - PHYSICAL DESCRIPTION
Extent 34 p. :
Other physical details ill. (some col.), charts
490 1# - SERIES STATEMENT
Series statement Thesis ;
Volume/sequential designation no. ISE-11-09
502 ## - DISSERTATION NOTE
Dissertation note Thesis (M. Eng.) - Asian Institute of Technology, 2011
500 ## - GENERAL NOTE
General note A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Mechatronics, School of Engineering and Technology
520 ## - SUMMARY, ETC.
Summary, etc. Neural networks for identification and control of a spark ignition engine using natural gas can be improved its dynamic. Basically, converted engines result in a significant power loss. The fuel quality variation and low volumetric efficiency of natural gas require numerous modification and calibration efforts, but the optimum operations can not be guaranteed. The vehicle was op~rated on both a test bench and practical driving cycles. The parameters such as throttle position and fuel injection duration were excited, while an oxygen concentration was observed over the whole operating range. The neural network has capability to identify the relation between natural gas injection duration and the engine states. According to these experiments, the correctness of neural network is between 91.2% to 93.4%.Therefore, the injection duration for each operating point was calculated from the neural network model. A interpolated look-up table is suitable for a fuel injection control. In this case, a test vehicle is Toyota Altis 1.6 1, fourcylinder engine equipped with compressed natural gas components. In additional, I adopt an ARM 32-bit microcontroller as a rapid prototype. The embedded controller contained the look-up table that used during a transient period. For steady-state responses, the system was combined with a PI controller. Thus, the experimental results can be confirmed the effectiveness of vehicle responses and also reduction of the calibration efforts. Finally, this similar methodology can be applied to other kinds of engines or fuels and allow inexpensive adjustments.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Spark ignition engines
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Gas as fuel
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element System identification
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Manukid Parnichkun,
Relator term Chairperson
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Afzulpurkar, Nitin V.,
Relator term Examination Committee
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Dailey, Mathew N.,
Relator term Examination Committee
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element National Science and Technology Development Agency (NSTDA), Thailand,
Relator term Scholarship donor
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Royal Thai Government Fellowship,
Relator term Scholarship donor
810 2# - SERIES ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Asian Institute of Technology.
Title of a work Thesis ;
Volume/sequential designation no. ISE-11-09
856 ## - ELECTRONIC LOCATION AND ACCESS
Materials specified Full-Text
Uniform Resource Identifier <a href="http://203.159.5.9/ait-thesis/detail.php?q=B11722">http://203.159.5.9/ait-thesis/detail.php?q=B11722</a>
907 ## - LOCAL DATA ELEMENT G, LDG (RLIN)
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b mnait
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902 ## - LOCAL DATA ELEMENT B, LDB (RLIN)
a 240404
998 ## - LOCAL CONTROL INFORMATION (RLIN)
Operator's initials, OID (RLIN) 0
Cataloger's initials, CIN (RLIN) 140619
First date, FD (RLIN) m
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-- 000:001:PDF:b1213377:001533:0:0:0:0:0:0
-- Abstract--AIT Thesis no.ISE-11-09
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945 ## - LOCAL PROCESSING INFORMATION (OCLC)
l mnait
945 ## - LOCAL PROCESSING INFORMATION (OCLC)
l mnait
945 ## - LOCAL PROCESSING INFORMATION (OCLC)
l mnarc
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type 20-AIT Publication
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type 40-Archives
909 ## - LOCAL ITEMS USED
Barcode Barcode : 30050120845820
CREATED CREATED : 2014-06-19
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CREATED CREATED : 2014-06-19
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Barcode Barcode : 30050160029798
CREATED CREATED : 2016-03-16
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Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Shelving location Date acquired Cost, normal purchase price Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library AIT Publications 18/08/2026 50.00   AIT Thesis no.ISE-11-09 30050120845820 18/08/2026 1 18/08/2026 20-AIT Publication
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library AIT Publications 18/08/2026 50.00   AIT Thesis no.ISE-11-09 30050120845812 18/08/2026 2 18/08/2026 20-AIT Publication
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library Archives 18/08/2026     AIT Thesis no.ISE-11-09 30050160029798 18/08/2026 1 18/08/2026 40-Archives
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