Model-based cold-start speed control scheme for spark ignition engines

Zhang, Jiangyan; Shen, Tielong; Marino, R.

doi:10.1016/j.conengprac.2010.01.010

Cited by 39 publications

(33 citation statements)

References 23 publications

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“…In particular, the problem of control of the rotation speed of SI-engines as well as the problem of control of the engine's pressure manifolds has been approached with different methods [1]- [2]. The paper proposes nonlinear feedback control for SI engines of an unknown dynamical model with the use of differential flatness theory-based adaptive fuzzy control method.…”

Section: Introductionmentioning

confidence: 99%

Flatness-based embedded adaptive fuzzy control of spark ignited engines

Rigatos¹,

Siano²,

Arsie³

2014

AIP Conference Proceedings

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The paper proposes a differential flatness theory-based adaptive fuzzy controller for spark-ignited (SI) engines. The system's dynamic model is considered to be completely unknown. By applying a change of variables (diffeomorphism) that is based on differential flatness theory the engine's dynamic model is written in the linear canonical (Brunovsky) form. After transforming the SI-engine model into the canonical form, the resulting control inputs are shown to contain nonlinear elements which depend on the system's parameters. These nonlinear terms are approximated with the use of neuro-fuzzy networks while a suitable learning law can be defined for the aforementioned neuro-fuzzy approximators so as to preserve the closed-loop system stability. Moreover, using Lyapunov stability analysis it is shown that the adaptive fuzzy control scheme succeeds H ∞ tracking performance, which means that the influence of the modeling errors and the external disturbances on the tracking error is attenuated to an arbitrary desirable level. The efficiency of the proposed adaptive fuzzy control scheme is checked through simulation experiments.

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Section: Introductionmentioning

confidence: 99%

Flatness-based embedded adaptive fuzzy control of spark ignited engines

Rigatos¹,

Siano²,

Arsie³

2014

AIP Conference Proceedings

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“…Chan develops a model that is capable of predicting the exhaust gas temperatures along the exhaust pipe and across the catalyst monolith, both spatially and temporally; and experiments with the conversions of toxic carbon monoxide and unburned hydrocarbons to harmless carbon dioxide and water at the catalytic converter [19]. Zhang presents a model-based control scheme of the cold-start speed in spark ignition (SI) engines, with the purpose of improving the transient performance of the starting engine speed [20]. Gumus has designed and investigated experimentally a new thermal energy storage system (TESS), which works on the effect of absorption and rejection of heat during the solid-liquid phase change of heat storage material, for pre-heating of a gasoline four cylinders engine at 2řC temperature (CO and HC emissions decreased about 64% and 15%, respectively, with effect of pre-heating engine at cold start and warming-up period) [21].…”

Section: Introductionmentioning

confidence: 99%

Research of some operating parameters and the emissions level variation in a spark ignited engine through on-board investigation methods in different loading conditions

Ferenţi

Baldean

2014

Open Engineering

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The present paper shows research made on a spark ignited engine with port fuel injection in different operation conditions in order to improve the comprehension about the cold start sequence, acceleration when changing the gear ratios, quality of combustion process and also any measures to be taken for pollutant reduction in such cases. The engineering endeavor encompasses the pollutants investigation during the operation time of gasoline supplied engine with four inline cylinders in different conditions. The temperature and any other parameters were measured with specific sensors installed on the engine or in the exhaust pipes. All the data collected has been evaluated using electronic investigation systems and highly developed equipment. In this manner it has enabled the outline of the idea of how pollutants of engine vary in different operating conditions. Air quality in the everyday environment is very important for the human health, and thus the ambient air quality has a well-known importance in the European pollution standards and legislation. The high level of attention directed to the pollution problem in the European lifestyle is a driving force for all kinds of studies in the field of the reduction of engine emission.

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“…In particular, the problem of control of the rotation speed of SI-engines as well as the problem of control of the engine's pressure manifolds has been approached with different methods [1][2]. In [3] a nonlinear state space controller for turn speed (and consequently the torque) of a spark-ignited engine is proposed.…”

Section: Introductionmentioning

confidence: 99%

“…In the above equations coefficients k pi , i = 1, 2, 3, k ωi , i = 1, 2, 3 and K d are associated with the combustion cycle of the SI-engine and are defined in [1][2].…”

Section: Introductionmentioning

confidence: 99%

Flatness-Based Adaptive Fuzzy Control Of Spark-Ignited Engines

Rigatos

Siano

2014

Journal of Artificial Intelligence and Soft Computing Research

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An adaptive fuzzy controller is designed for spark-ignited (SI) engines, under the constraint that the system's model is unknown. The control algorithm aims at satisfying the H ∞ tracking performance criterion, which means that the influence of the modeling errors and the external disturbances on the tracking error is attenuated to an arbitrary desirable level. After transforming the SI-engine model into the canonical form, the resulting control inputs are shown to contain nonlinear elements which depend on the system's parameters. The nonlinear terms which appear in the control inputs are approximated with the use of neuro-fuzzy networks. It is shown that a suitable learning law can be defined for the aforementioned neuro-fuzzy approximators so as to preserve the closed-loop system stability. With the use of Lyapunov stability analysis it is proven that the proposed adaptive fuzzy control scheme results in H ∞ tracking performance. The efficiency of the proposed adaptive fuzzy control scheme is checked through simulation experiments.

show abstract

Model-based cold-start speed control scheme for spark ignition engines

Cited by 39 publications

References 23 publications

Flatness-based embedded adaptive fuzzy control of spark ignited engines

Flatness-based embedded adaptive fuzzy control of spark ignited engines

Research of some operating parameters and the emissions level variation in a spark ignited engine through on-board investigation methods in different loading conditions

Flatness-Based Adaptive Fuzzy Control Of Spark-Ignited Engines

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