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SI Engine Controls and Mean Value Engine Modelling

Authors: Elbert Hendricks; Spencer C. Sorenson;

SI Engine Controls and Mean Value Engine Modelling

Abstract

<div class="htmlview paragraph">Many existing classical electronic control systems (speed-throttle, speed-density, MAF (mass air flow)) are based on quasistatic engine models and static measured engine maps. They are thus time consuming to adapt to new engine types, are sensitive to dynamic sensor errors and in general have undesirable dynamic characteristics. One of the main reasons for the characteristics of these strategies has been the lack of a precise, systems oriented, equation based, dynamic engine model. Recently a compact dynamic mean value engine model (MVEM) has been presented by the authors which displays good global accuracy. A mean value model is one which predicts the mean value of the gross internal and external engine variables. This paper shows how the engine model can be applied to the systematic design and analysis of classical electronic engine control systems.</div> <div class="htmlview paragraph">One of the main aims of the paper is to eliminate the use of cut and try methods in designing dynamic engine controls. The goal is also to improve transient drivability and emissions performance. The main subjects treated are steady state and transient fueling strategies, lambda control and idle-speed control. There is also a comparison of conventional speed density and MAF control systems including the limitations imposed by signal conditioning filters and available sensors.</div>

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
67
Average
Top 1%
Top 10%
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