A Neural Network Based Soft Sensor For Air Fuel Ratio Dynamics In SI Engines

Yujia Zhai; Ka Lok Man; Sanghyuk Lee; Fei Xue

A Neural Network Based Soft Sensor For Air Fuel Ratio Dynamics In SI Engines

Yujia Zhai, Ka Lok Man, Sanghyuk Lee, Fei Xue

Xi'an Jiaotong-Liverpool University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

1 Citation (Scopus)

Abstract

Soft sensors have been widely used in control algorithms of engineering application to enhance the control performance and system robustness. This paper proposes a neural network (NN) based soft sensor scheme for air/fuel ratio sensor in spark-ignition engines. The modeling results show that satisfactory modeling performance can be obtained with moderate computational load.

Original language	English
Title of host publication	Proceedings of the International MultiConference of Engineers and Computer Scientists 2017, IMECS 2017
Editors	A. M. Korsunsky, S. I. Ao, Oscar Castillo, Craig Douglas, David Dagan Feng
Publisher	Newswood Limited
Pages	719-722
Number of pages	4
ISBN (Electronic)	9789881404770
Publication status	Published - 2017
Event	2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017 - Hong Kong, Hong Kong Duration: 15 Mar 2017 → 17 Mar 2017

Publication series

Name	Lecture Notes in Engineering and Computer Science
Volume	2228
ISSN (Print)	2078-0958

Conference

Conference	2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017
Country/Territory	Hong Kong
City	Hong Kong
Period	15/03/17 → 17/03/17

Keywords

Engine dynamics
Neural network
Soft sensor
System identification

Cite this

Zhai, Y., Man, K. L., Lee, S., & Xue, F. (2017). A Neural Network Based Soft Sensor For Air Fuel Ratio Dynamics In SI Engines. In A. M. Korsunsky, S. I. Ao, O. Castillo, C. Douglas, & D. D. Feng (Eds.), Proceedings of the International MultiConference of Engineers and Computer Scientists 2017, IMECS 2017 (pp. 719-722). (Lecture Notes in Engineering and Computer Science; Vol. 2228). Newswood Limited.

Zhai, Yujia ; Man, Ka Lok ; Lee, Sanghyuk et al. / A Neural Network Based Soft Sensor For Air Fuel Ratio Dynamics In SI Engines. Proceedings of the International MultiConference of Engineers and Computer Scientists 2017, IMECS 2017. editor / A. M. Korsunsky ; S. I. Ao ; Oscar Castillo ; Craig Douglas ; David Dagan Feng. Newswood Limited, 2017. pp. 719-722 (Lecture Notes in Engineering and Computer Science).

@inproceedings{b6623948396c4a7b958a691fe359744d,

title = "A Neural Network Based Soft Sensor For Air Fuel Ratio Dynamics In SI Engines",

abstract = "Soft sensors have been widely used in control algorithms of engineering application to enhance the control performance and system robustness. This paper proposes a neural network (NN) based soft sensor scheme for air/fuel ratio sensor in spark-ignition engines. The modeling results show that satisfactory modeling performance can be obtained with moderate computational load.",

keywords = "Engine dynamics, Neural network, Soft sensor, System identification",

author = "Yujia Zhai and Man, {Ka Lok} and Sanghyuk Lee and Fei Xue",

note = "Funding Information: This work was supported in part by the Centre for Smart Grid and Information Convergence (CeSGIC) at Xian Jiaotong-Liverpool University. This research was financially supported by the Centre for Smart Grid and Information Convergence (CeSGIC) at Xian Jiaotong-Liverpool University. The authors would like to thank all the parties concerned.; 2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017 ; Conference date: 15-03-2017 Through 17-03-2017",

year = "2017",

language = "English",

series = "Lecture Notes in Engineering and Computer Science",

publisher = "Newswood Limited",

pages = "719--722",

editor = "Korsunsky, {A. M.} and Ao, {S. I.} and Oscar Castillo and Craig Douglas and Feng, {David Dagan}",

booktitle = "Proceedings of the International MultiConference of Engineers and Computer Scientists 2017, IMECS 2017",

}

Zhai, Y, Man, KL, Lee, S & Xue, F 2017, A Neural Network Based Soft Sensor For Air Fuel Ratio Dynamics In SI Engines. in AM Korsunsky, SI Ao, O Castillo, C Douglas & DD Feng (eds), Proceedings of the International MultiConference of Engineers and Computer Scientists 2017, IMECS 2017. Lecture Notes in Engineering and Computer Science, vol. 2228, Newswood Limited, pp. 719-722, 2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017, Hong Kong, Hong Kong, 15/03/17.

A Neural Network Based Soft Sensor For Air Fuel Ratio Dynamics In SI Engines. / Zhai, Yujia; Man, Ka Lok; Lee, Sanghyuk et al.
Proceedings of the International MultiConference of Engineers and Computer Scientists 2017, IMECS 2017. ed. / A. M. Korsunsky; S. I. Ao; Oscar Castillo; Craig Douglas; David Dagan Feng. Newswood Limited, 2017. p. 719-722 (Lecture Notes in Engineering and Computer Science; Vol. 2228).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

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AU - Zhai, Yujia

AU - Man, Ka Lok

AU - Lee, Sanghyuk

AU - Xue, Fei

N1 - Funding Information: This work was supported in part by the Centre for Smart Grid and Information Convergence (CeSGIC) at Xian Jiaotong-Liverpool University. This research was financially supported by the Centre for Smart Grid and Information Convergence (CeSGIC) at Xian Jiaotong-Liverpool University. The authors would like to thank all the parties concerned.

PY - 2017

Y1 - 2017

N2 - Soft sensors have been widely used in control algorithms of engineering application to enhance the control performance and system robustness. This paper proposes a neural network (NN) based soft sensor scheme for air/fuel ratio sensor in spark-ignition engines. The modeling results show that satisfactory modeling performance can be obtained with moderate computational load.

AB - Soft sensors have been widely used in control algorithms of engineering application to enhance the control performance and system robustness. This paper proposes a neural network (NN) based soft sensor scheme for air/fuel ratio sensor in spark-ignition engines. The modeling results show that satisfactory modeling performance can be obtained with moderate computational load.

KW - Engine dynamics

KW - Neural network

KW - Soft sensor

KW - System identification

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M3 - Conference Proceeding

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T3 - Lecture Notes in Engineering and Computer Science

SP - 719

EP - 722

BT - Proceedings of the International MultiConference of Engineers and Computer Scientists 2017, IMECS 2017

A2 - Korsunsky, A. M.

A2 - Ao, S. I.

A2 - Castillo, Oscar

A2 - Douglas, Craig

A2 - Feng, David Dagan

PB - Newswood Limited

T2 - 2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017

Y2 - 15 March 2017 through 17 March 2017

ER -

A Neural Network Based Soft Sensor For Air Fuel Ratio Dynamics In SI Engines

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Publication series

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Keywords

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