In diesel engines, variable geometry turbocharger (VGT) and exhaust gas recirculation (EGR) systems are used to increase engine specific power and reduce NOx emissions, respectively. Because the dynamics of both the VGT and EGR are highly nonlinear and coupled to each other, better performance may be attained by substituting nonlinear multiple input, multiple output (MIMO) controllers for the existing conventional lookup table-based linear controllers. This paper presents a coordinated VGT/EGR control system for common-rail direct injection diesel engines. The objective of the control system is to track target mass air flow and target intake manifold pressure by adjusting the EGR and VGT actuator positions. We designed a nonlinear MIMO control system using a neural control scheme that adopts an indirect adaptive control approach. The neural control system is comprised of a neural network identifier, which mimics the target air system, and a neural network controller, which calculates the actuator positions. The proposed control system has been validated with engine experiments under transient operating conditions. It was demonstrated from experimental results that the proposed control system shows improved target value tracking performance over conventional VGT/EGR control system.
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e-mail: msunwoo@hanyang.ac.kr
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January 2013
Research-Article
VGT and EGR Control of Common-Rail Diesel Engines Using an Artificial Neural Network
Byounggul Oh,
Byounggul Oh
Advanced Combustion & Engine
Technology Team
,Institute of Technology
,Doosan Infracore Co., Ltd.
,39-3, Sungbok-Dong
,Suji-Gu, Yongin-Si
,Gyeonggi-Do 448-795
, Korea
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Jeongwon Sohn,
Jeongwon Sohn
Department of Automotive Engineering
,Hanyang University
,222 Wangsimni-ro, Seongdong-gu
,Seoul 133-791
, Korea
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Jongseob Won,
Jongseob Won
Department of Mechanical and
Automotive Engineering
,Jeonju University
,303 Cheonjam-ro, Wansan-gu
,Jeonju 560-759
, Korea
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Myoungho Sunwoo
e-mail: msunwoo@hanyang.ac.kr
Myoungho Sunwoo
1
Department of Automotive Engineering
,Hanyang University
,222 Wangsimni-ro, Seongdong-gu
,Seoul 133-791
, Korea
e-mail: msunwoo@hanyang.ac.kr
1Corresponding author.
Search for other works by this author on:
Byounggul Oh
Advanced Combustion & Engine
Technology Team
,Institute of Technology
,Doosan Infracore Co., Ltd.
,39-3, Sungbok-Dong
,Suji-Gu, Yongin-Si
,Gyeonggi-Do 448-795
, Korea
Jeongwon Sohn
Department of Automotive Engineering
,Hanyang University
,222 Wangsimni-ro, Seongdong-gu
,Seoul 133-791
, Korea
Jongseob Won
Department of Mechanical and
Automotive Engineering
,Jeonju University
,303 Cheonjam-ro, Wansan-gu
,Jeonju 560-759
, Korea
Myoungho Sunwoo
Department of Automotive Engineering
,Hanyang University
,222 Wangsimni-ro, Seongdong-gu
,Seoul 133-791
, Korea
e-mail: msunwoo@hanyang.ac.kr
1Corresponding author.
Contributed by the IC Engine Division of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received February 29, 2012; final manuscript received August 6, 2012; published online November 21, 2012. Assoc. Editor: Christopher J. Rutland.
J. Eng. Gas Turbines Power. Jan 2013, 135(1): 012801 (9 pages)
Published Online: November 21, 2012
Article history
Received:
February 29, 2012
Revision Received:
August 6, 2012
Citation
Oh, B., Lee, M., Park, Y., Sohn, J., Won, J., and Sunwoo, M. (November 21, 2012). "VGT and EGR Control of Common-Rail Diesel Engines Using an Artificial Neural Network." ASME. J. Eng. Gas Turbines Power. January 2013; 135(1): 012801. https://doi.org/10.1115/1.4007541
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