4391251 Electronic controller for controlling the air/fuel ratio of the mixture supplied to an internal combustion engine

1983 ◽  
Vol 17 (12) ◽  
pp. 2644
Author(s):  
Pierre Planteline ◽  
Roger Machetel
2013 ◽  
Vol 376 ◽  
pp. 383-389
Author(s):  
Mohammad Javad Nekooei ◽  
Koto Jaswar ◽  
Agoes Priyanto

A Multi Input Multi Output (MIMO) fuzzy estimator variable structure control (VSC) which containing an on-line controller coefficient tuned with the aim of a fuzzy back stepping algorithm. Satisfactory trajectories tracking among the internal combustion engine (IC engine) air to fuel ratio and the preferred input is certified in this paper. The fuzzy controller deployed in developed fuzzy estimator variable structure controller works using Lyapunov fuzzy inference system (FIS) with least model based rule base. Function among variable structure function, error and the error’s rate is represented by model. The outputs show fuel ratio. The fuzzy back stepping tactic is an on-line variable structure function fixing with the aim of an adaptive approach. MIMO fuzzy estimator and VSC performance with an on-line fuzzy back stepping algorithm (FBAFVSC) tuned with the aim of controller coefficient is confirmed using a comparison with VSC and planned approach. Simulation outputs indicate excellent presentation of fuel ratio in attendance of ambiguity and exterior annoyance.


1998 ◽  
Vol 118 (6) ◽  
pp. 333-338 ◽  
Author(s):  
Masashi Tsuzuki ◽  
Takeshi Kawai ◽  
Tessho Yamada ◽  
Kanemitsu Nishio

Author(s):  
Yiran Hu ◽  
Sai S. V. Rajagopalan ◽  
Stephen Yurkovich ◽  
Yann Guezennec

Modeling the internal combustion engine for air-to-fuel ratio (AFR) control has been widely studied and several methodologies have been adopted toward the end goal of applying model based control schemes. In this paper, an online binary sensor identification (BID) technique using switching sensors is adopted for modeling the response from fuel input to AFR output of a spark-ignited, internal combustion engine, to be used in AFR control. In general terms, the algorithm identifies the impulse response of a linear time invariant (LTI) system by choosing an optimal sequence of inputs. The entire modeling process is done online with a four-cylinder engine in a test cell, using typical production switching sensors. Finite impulse response (FIR) linear time invariant (LTI) models are identified at prescribed operating points of the engine (specified by engine speed and the manifold air pressure). The validity of the resulting model is then tested on separate data streams with AFR measured from a wide-range sensor output. By scheduling the coefficients of the FIR models based on the operating condition, it is possible to identify a linear parameter varying AFR model for the appropriate operating regions of the engine.


1997 ◽  
Vol 119 (3) ◽  
pp. 568-573
Author(s):  
S. Thompson ◽  
C. Gong

In order to minimize emissions the Air-Fuel Ratio (AFR) of a spark-ignited internal combustion engine needs to be maintained at stoichiometric. Whenever the air and fuel enter the engine’s cylinder the AFR cannot be changed; therefore the problem of AFR control is a problem of intake manifold control. Although the problem of AFR control (and hence of intake manifold modelling) appears to be solved for a fully warmed-up engine the problem of AFR control during the warm-up period remains. This paper addresses this problem by using a novel AFR control strategy, which can be based on a given intake manifold model, to test the AFR control of a partially warmed-up engine. The results of engine tests demonstrate that during the warm-up period tight AFR control is not possible using any of the intake manifold models developed for a fully warmed-up engine. This can only be the result of unmodeled dynamics in the intake manifold and it is therefore concluded that further work in the area of manifold modelling is required. Possible areas of model improvement are indicated.


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