Model-Based Stochastic Adaptive Air-Fuel Ratio Control of Direct Injection Biogas-Fuelled Engines

Model-Based Stochastic Adaptive Air-Fuel Ratio Control of Direct Injection Biogas-Fuelled Engines

The problem of stochastic adaptive air-fuel ratio control by the dynamic model of biogas-fuelled engines is investigated in this paper. An adaptive law is employed to estimate the theoretical air-fuel ratio, which is undetermined due to the uncertainty of the methane concentration in the biogas. A s...

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Main Authors: Jun Yang, Yanxiao Li, Jian Wang, Fangyuan Li
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2020/8891046
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spelling doaj-c51ee8809ee145c8988131254f77a9ac2020-11-30T09:11:28ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472020-01-01202010.1155/2020/88910468891046Model-Based Stochastic Adaptive Air-Fuel Ratio Control of Direct Injection Biogas-Fuelled EnginesJun Yang0Yanxiao Li1Jian Wang2Fangyuan Li3Department of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, ChinaDepartment of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, ChinaDepartment of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, ChinaDepartment of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, ChinaThe problem of stochastic adaptive air-fuel ratio control by the dynamic model of biogas-fuelled engines is investigated in this paper. An adaptive law is employed to estimate the theoretical air-fuel ratio, which is undetermined due to the uncertainty of the methane concentration in the biogas. A stochastic adaptive air-fuel ratio controller in consideration of the stochasticity of the residual gas is designed based on the adaptive law, and the closed-loop system is proven to be mean-square stable. The proposed stochastic adaptive air-fuel ratio controller is validated through a numerical simulation when the theoretical air-fuel ratio is unknown constants and jump signals.http://dx.doi.org/10.1155/2020/8891046
collection DOAJ
language English
format Article
sources DOAJ
author Jun Yang
Yanxiao Li
Jian Wang
Fangyuan Li
spellingShingle Jun Yang
Yanxiao Li
Jian Wang
Fangyuan Li
Model-Based Stochastic Adaptive Air-Fuel Ratio Control of Direct Injection Biogas-Fuelled Engines
Mathematical Problems in Engineering
author_facet Jun Yang
Yanxiao Li
Jian Wang
Fangyuan Li
author_sort Jun Yang
title Model-Based Stochastic Adaptive Air-Fuel Ratio Control of Direct Injection Biogas-Fuelled Engines
title_short Model-Based Stochastic Adaptive Air-Fuel Ratio Control of Direct Injection Biogas-Fuelled Engines
title_full Model-Based Stochastic Adaptive Air-Fuel Ratio Control of Direct Injection Biogas-Fuelled Engines
title_fullStr Model-Based Stochastic Adaptive Air-Fuel Ratio Control of Direct Injection Biogas-Fuelled Engines
title_full_unstemmed Model-Based Stochastic Adaptive Air-Fuel Ratio Control of Direct Injection Biogas-Fuelled Engines
title_sort model-based stochastic adaptive air-fuel ratio control of direct injection biogas-fuelled engines
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2020-01-01
description The problem of stochastic adaptive air-fuel ratio control by the dynamic model of biogas-fuelled engines is investigated in this paper. An adaptive law is employed to estimate the theoretical air-fuel ratio, which is undetermined due to the uncertainty of the methane concentration in the biogas. A stochastic adaptive air-fuel ratio controller in consideration of the stochasticity of the residual gas is designed based on the adaptive law, and the closed-loop system is proven to be mean-square stable. The proposed stochastic adaptive air-fuel ratio controller is validated through a numerical simulation when the theoretical air-fuel ratio is unknown constants and jump signals.
url http://dx.doi.org/10.1155/2020/8891046
work_keys_str_mv AT junyang modelbasedstochasticadaptiveairfuelratiocontrolofdirectinjectionbiogasfuelledengines
AT yanxiaoli modelbasedstochasticadaptiveairfuelratiocontrolofdirectinjectionbiogasfuelledengines
AT jianwang modelbasedstochasticadaptiveairfuelratiocontrolofdirectinjectionbiogasfuelledengines
AT fangyuanli modelbasedstochasticadaptiveairfuelratiocontrolofdirectinjectionbiogasfuelledengines
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