Bayesian Method for Fuel Mass Estimation of Short Pilot Injections based on its Misfire Probability
(2020) 2020 American Control Conference, ACC 2020 In Proceedings of the American Control Conference 2020-July. p.1507-1513- Abstract
A fuel mass estimation method for short pilot diesel injections is proposed and analyzed in this article. Previous studies showed that the pilot misfire ratio was more strongly correlated with the fuel mass than the on-time. This characteristic is exploited for the fuel mass estimation in a region where it is otherwise challenging to get good estimation accuracy due to the low signal-to-noise ratio, such as by rail pressure measurements or in-cylinder pressure for heat release estimation. The suggested method uses a Bayesian approach where the calibrated injectors, the pilot misfire ratio and the misfire detection are stochastically modelled. The effect of the different model parameters and dispersion on the estimator properties are... (More)
A fuel mass estimation method for short pilot diesel injections is proposed and analyzed in this article. Previous studies showed that the pilot misfire ratio was more strongly correlated with the fuel mass than the on-time. This characteristic is exploited for the fuel mass estimation in a region where it is otherwise challenging to get good estimation accuracy due to the low signal-to-noise ratio, such as by rail pressure measurements or in-cylinder pressure for heat release estimation. The suggested method uses a Bayesian approach where the calibrated injectors, the pilot misfire ratio and the misfire detection are stochastically modelled. The effect of the different model parameters and dispersion on the estimator properties are analyzed. Experimental results in a Scania D13 Diesel engine confirm the improvement in the pilot mass estimation, for the regions within the transition from full misfire to full combustion. In this region, a 60% reduction in the estimation error was obtained, from 0.66mg to 0.27mg standard deviation.
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- author
- Moreno, Carlos Jorques LU ; Stenlaas, Ola LU and Tunestal, Per LU
- organization
- publishing date
- 2020
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2020 American Control Conference, ACC 2020
- series title
- Proceedings of the American Control Conference
- volume
- 2020-July
- article number
- 9147866
- pages
- 7 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2020 American Control Conference, ACC 2020
- conference location
- Denver, United States
- conference dates
- 2020-07-01 - 2020-07-03
- external identifiers
-
- scopus:85089603518
- ISSN
- 0743-1619
- ISBN
- 9781538682661
- DOI
- 10.23919/ACC45564.2020.9147866
- language
- English
- LU publication?
- yes
- id
- 48741f4c-dab7-4588-a016-17c5d5588294
- date added to LUP
- 2020-08-27 14:28:31
- date last changed
- 2022-04-19 00:23:39
@inproceedings{48741f4c-dab7-4588-a016-17c5d5588294,
abstract = {{<p>A fuel mass estimation method for short pilot diesel injections is proposed and analyzed in this article. Previous studies showed that the pilot misfire ratio was more strongly correlated with the fuel mass than the on-time. This characteristic is exploited for the fuel mass estimation in a region where it is otherwise challenging to get good estimation accuracy due to the low signal-to-noise ratio, such as by rail pressure measurements or in-cylinder pressure for heat release estimation. The suggested method uses a Bayesian approach where the calibrated injectors, the pilot misfire ratio and the misfire detection are stochastically modelled. The effect of the different model parameters and dispersion on the estimator properties are analyzed. Experimental results in a Scania D13 Diesel engine confirm the improvement in the pilot mass estimation, for the regions within the transition from full misfire to full combustion. In this region, a 60% reduction in the estimation error was obtained, from 0.66mg to 0.27mg standard deviation.</p>}},
author = {{Moreno, Carlos Jorques and Stenlaas, Ola and Tunestal, Per}},
booktitle = {{2020 American Control Conference, ACC 2020}},
isbn = {{9781538682661}},
issn = {{0743-1619}},
language = {{eng}},
pages = {{1507--1513}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{Proceedings of the American Control Conference}},
title = {{Bayesian Method for Fuel Mass Estimation of Short Pilot Injections based on its Misfire Probability}},
url = {{http://dx.doi.org/10.23919/ACC45564.2020.9147866}},
doi = {{10.23919/ACC45564.2020.9147866}},
volume = {{2020-July}},
year = {{2020}},
}