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Model-based air-fuel ratio control o...

Fekete, Nicholas Patrick.

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Model-based air-fuel ratio control of a multicylinder leanburn engine.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Model-based air-fuel ratio control of a multicylinder leanburn engine./
作者:	Fekete, Nicholas Patrick.
面頁冊數:	127 p.
附註:	Adviser: J. David Powell.
Contained By:	Dissertation Abstracts International56-04B.
標題:	Engineering, Automotive. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9525829

Model-based air-fuel ratio control of a multicylinder leanburn engine.
Fekete, Nicholas Patrick.

Model-based air-fuel ratio control of a multicylinder leanburn engine. - 127 p.

Adviser: J. David Powell.

Thesis (Ph.D.)--Stanford University, 1995.

Realization of the leanburn spark-ignition engine's potential for improved fuel economy strongly depends on precise control of the air-fuel ratio (AFR), especially during transients, for acceptable driveability and low exhaust emissions. Very high-bandwidth transient AFR control is also necessary for production engines which use a three-way catalyst, in order to maximize the catalytic conversion efficiency.Subjects--Topical Terms:

1018477
Engineering, Automotive.

Model-based air-fuel ratio control of a multicylinder leanburn engine.
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035 $a (UnM)AAI9525829
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040 $a UnM $c UnM
100 1 $a Fekete, Nicholas Patrick. $3 1253090
245 1 0 $a Model-based air-fuel ratio control of a multicylinder leanburn engine.
300 $a 127 p.
500 $a Adviser: J. David Powell.
500 $a Source: Dissertation Abstracts International, Volume: 56-04, Section: B, page: 2162.
502 $a Thesis (Ph.D.)--Stanford University, 1995.
520 $a Realization of the leanburn spark-ignition engine's potential for improved fuel economy strongly depends on precise control of the air-fuel ratio (AFR), especially during transients, for acceptable driveability and low exhaust emissions. Very high-bandwidth transient AFR control is also necessary for production engines which use a three-way catalyst, in order to maximize the catalytic conversion efficiency.
520 $a This work describes the implementation of an adaptive-feedforward model-based AFR controller. A discrete, nonlinear, control-oriented engine model was developed and used in the AFR control algorithm. The engine model includes intake-manifold airflow dynamics, fuel wall-wetting dynamics, process delays inherent in the four-stroke engine cycle, and exhaust gas oxygen (EGO) sensor dynamics. The sampling period is synchronous with crank-angle ("event-based").
520 $a The controller relies on the engine speed and throttle angle for load information. An intake-manifold pressure (MAP) sensor is used for identification of the airflow dynamics, but not for control. The MAP sensor would also be useful for the cold start and for engine diagnostics. No mass-airflow sensor is used nor indicated. Accurate in-cylinder air-mass estimation is made possible by controlling the airflow with an electronic throttle.
520 $a The estimator-based controller has been tested on a single-cylinder engine using the feedback from a switch-type production EGO sensor. The limit-cycle associated with the on-off EGO sensor in conventional systems is eliminated with the estimator-based control structure. Furthermore, the in-cylinder AFR tracks the commanded value, so that if a limit cycle is desired in some areas of the engine's operating range for better catalyst operation, its amplitude and frequency can be set arbitrarily.
520 $a Cycle-to-cycle AFR control has been demonstrated using the model-based approach on a warm four-cylinder Mercedes-Benz leanburn engine at the stoichiometric AFR and near the lean limit. A constant AFR was commanded during load transients, and a wide-range oxygen (UEGO) sensor was used for feedback. The AFR was controlled to within 0.8% RMS, with peak excursions of about 2%. The transient AFR control during lean engine operation was accurate enough to prevent the occurrence of misfires, even though the engine was running near the lean limit.
590 $a School code: 0212.
650 4 $a Engineering, Automotive. $3 1018477
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Engineering, Mechanical. $3 783786
690 $a 0540
690 $a 0544
690 $a 0548
710 2 0 $a Stanford University. $3 754827
773 0 $t Dissertation Abstracts International $g 56-04B.
790 $a 0212
790 1 0 $a Powell, J. David, $e advisor
791 $a Ph.D.
792 $a 1995
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9525829