Bayesian Method for Fuel Mass Estimation of Short Pilot Injections based on its Misfire Probability

Carlos Jorques Moreno; Ola Stenlaas; Per Tunestal

doi:10.23919/ACC45564.2020.9147866

Bayesian Method for Fuel Mass Estimation of Short Pilot Injections based on its Misfire Probability

Carlos Jorques Moreno, Ola Stenlaas, Per Tunestal

Combustion Engines

Scania CV AB

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

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 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.

Original language	English
Title of host publication	2020 American Control Conference, ACC 2020
Publisher	IEEE - Institute of Electrical and Electronics Engineers Inc.
Pages	1507-1513
Number of pages	7
ISBN (Electronic)	9781538682661
DOIs	https://doi.org/10.23919/ACC45564.2020.9147866
Publication status	Published - 2020
Event	2020 American Control Conference, ACC 2020 - Denver, United States Duration: 2020 Jul 1 → 2020 Jul 3

Publication series

Name	Proceedings of the American Control Conference
Volume	2020-July
ISSN (Print)	0743-1619

Conference

Conference	2020 American Control Conference, ACC 2020
Country/Territory	United States
City	Denver
Period	2020/07/01 → 2020/07/03

Subject classification (UKÄ)

Control Engineering
Vehicle and Aerospace Engineering

Access to Document

10.23919/ACC45564.2020.9147866

Cite this

Moreno, C. J., Stenlaas, O., & Tunestal, P. (2020). Bayesian Method for Fuel Mass Estimation of Short Pilot Injections based on its Misfire Probability. In 2020 American Control Conference, ACC 2020 (pp. 1507-1513). Article 9147866 (Proceedings of the American Control Conference; Vol. 2020-July). IEEE - Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC45564.2020.9147866

@inproceedings{48741f4cdab74588a01617c5d5588294,

title = "Bayesian Method for Fuel Mass Estimation of Short Pilot Injections based on its Misfire Probability",

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 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.",

author = "Moreno, \{Carlos Jorques\} and Ola Stenlaas and Per Tunestal",

year = "2020",

doi = "10.23919/ACC45564.2020.9147866",

language = "English",

series = "Proceedings of the American Control Conference",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

pages = "1507--1513",

booktitle = "2020 American Control Conference, ACC 2020",

address = "United States",

note = "2020 American Control Conference, ACC 2020 ; Conference date: 01-07-2020 Through 03-07-2020",

}

Moreno, CJ, Stenlaas, O & Tunestal, P 2020, Bayesian Method for Fuel Mass Estimation of Short Pilot Injections based on its Misfire Probability. in 2020 American Control Conference, ACC 2020., 9147866, Proceedings of the American Control Conference, vol. 2020-July, IEEE - Institute of Electrical and Electronics Engineers Inc., pp. 1507-1513, 2020 American Control Conference, ACC 2020, Denver, United States, 2020/07/01. https://doi.org/10.23919/ACC45564.2020.9147866

Bayesian Method for Fuel Mass Estimation of Short Pilot Injections based on its Misfire Probability. / Moreno, Carlos Jorques; Stenlaas, Ola; Tunestal, Per.
2020 American Control Conference, ACC 2020. IEEE - Institute of Electrical and Electronics Engineers Inc., 2020. p. 1507-1513 9147866 (Proceedings of the American Control Conference; Vol. 2020-July).

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

TY - GEN

T1 - Bayesian Method for Fuel Mass Estimation of Short Pilot Injections based on its Misfire Probability

AU - Moreno, Carlos Jorques

AU - Stenlaas, Ola

AU - Tunestal, Per

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/85089603518

U2 - 10.23919/ACC45564.2020.9147866

DO - 10.23919/ACC45564.2020.9147866

M3 - Paper in conference proceeding

AN - SCOPUS:85089603518

T3 - Proceedings of the American Control Conference

SP - 1507

EP - 1513

BT - 2020 American Control Conference, ACC 2020

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 American Control Conference, ACC 2020

Y2 - 1 July 2020 through 3 July 2020

ER -

Bayesian Method for Fuel Mass Estimation of Short Pilot Injections based on its Misfire Probability

Abstract

Publication series

Conference

Subject classification (UKÄ)

Access to Document

Other files and links

Fingerprint

Design and Optimization of In-Cycle Closed-Loop Combustion Control with Multiple Injections

Cite this