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Knock characterization, simulation, ...
~
Spelina, Jill McAfee.
Knock characterization, simulation, and control.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Knock characterization, simulation, and control./
作者:
Spelina, Jill McAfee.
面頁冊數:
1 online resource (202 pages)
附註:
Source: Dissertation Abstracts International, Volume: 78-05(E), Section: B.
Contained By:
Dissertation Abstracts International78-05B(E).
標題:
Automotive engineering. -
電子資源:
click for full text (PQDT)
ISBN:
9781369336450
Knock characterization, simulation, and control.
Spelina, Jill McAfee.
Knock characterization, simulation, and control.
- 1 online resource (202 pages)
Source: Dissertation Abstracts International, Volume: 78-05(E), Section: B.
Thesis (Ph.D.)
Includes bibliographical references
Engine knock is an undesirable phenomenon which requires feedback control in order to maximize engine efficiency and avoid damage to the engine. However, knock behaves as a random process and is stochastic in nature, therefore, deterministic notions for control and performance evaluation do not apply. In this dissertation, an extensive statistical analysis is performed on knock intensity data recorded under a broad range of operating conditions in order to characterize the statistical properties of the knock process. In particular, it is shown that knock intensity closely approximates a cyclically independent random process which was implicitly assumed in previous studies. Parametric log-normal and gamma distribution models are also fitted to the empirically defined knock intensity distributions. Using a variety of methods to assess the degree of fit for each, it is shown that the data does not conform to either model at the 0.05 significance level.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9781369336450Subjects--Topical Terms:
1104081
Automotive engineering.
Index Terms--Genre/Form:
554714
Electronic books.
Knock characterization, simulation, and control.
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2016.
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Includes bibliographical references
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Engine knock is an undesirable phenomenon which requires feedback control in order to maximize engine efficiency and avoid damage to the engine. However, knock behaves as a random process and is stochastic in nature, therefore, deterministic notions for control and performance evaluation do not apply. In this dissertation, an extensive statistical analysis is performed on knock intensity data recorded under a broad range of operating conditions in order to characterize the statistical properties of the knock process. In particular, it is shown that knock intensity closely approximates a cyclically independent random process which was implicitly assumed in previous studies. Parametric log-normal and gamma distribution models are also fitted to the empirically defined knock intensity distributions. Using a variety of methods to assess the degree of fit for each, it is shown that the data does not conform to either model at the 0.05 significance level.
520
$a
The identified knock probability characteristics of an engine are used to simulate the closed look behavior of three knock control algorithms, particularly with regard to the threshold level used to define 'knock event'. Traditionally, knock thresholds are set at a high level in order to identify those 'knocking' cycles most likely to cause engine damage or driver annoyance. However, since most cycles fall below this threshold, this results in considerable loss of information. A new method for optimizing the knock threshold is developed based on maximizing the sensitivity of the resultant knock event rate to changes in the spark timing of the engine. The method is applied to both traditional and Cumulative-Summation-based controllers and show a fast transient response, improved mean spark advance, and reduced cyclic dispersion.
520
$a
Finally, a new Markov-based analysis is used to compute the statistical properties and distribution of the closed loop response of a system using a traditional knock control law. The analysis shows the closed loop spark advance distribution is initially periodic, although it finally collapses to a steady state distribution as a result of limits applied to the spark advance actuation. The stochastic response of the controller to different initial conditions is also investigated, providing a more rigorous insight into its performance. The results of the Markov--based analysis are confirmed using Monte Carlo simulations.
533
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Electronic reproduction.
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Ann Arbor, Mich. :
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ProQuest,
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2018
538
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Mode of access: World Wide Web
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click for full text (PQDT)
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