Predictive In-Cycle Closed-Loop Combustion Control with Pilot-Main Injections
Jorques Moreno, Carlos LU ; Stenlåås, Ola LU and Tunestål, Per LU
(2021)
21th IFAC World Congress
In IFAC-PapersOnLine
53(2).
p.14000-14007
- Abstract
- This paper studies the use of predictive in-cycle close-loop combustion control to reduce the stochastic cyclic variations of diesel combustion. The combustion metrics that fully define the pressure trace with a pilot-main injection i.e. pilot and main start of combustion, burned pilot mass, and engine load are used as the set-point reference. These metrics are in-cycle predicted by calibrated models as functions of the current cylinder state, estimated by in-cylinder pressure measurements. The proposed approach uses four individual controllers for the set-point error minimization, which respectively regulate the injection’s timing and duration of the pilot-main injection. The controllers are implemented in a FPGA and tested in a Scania... (More)
- This paper studies the use of predictive in-cycle close-loop combustion control to reduce the stochastic cyclic variations of diesel combustion. The combustion metrics that fully define the pressure trace with a pilot-main injection i.e. pilot and main start of combustion, burned pilot mass, and engine load are used as the set-point reference. These metrics are in-cycle predicted by calibrated models as functions of the current cylinder state, estimated by in-cylinder pressure measurements. The proposed approach uses four individual controllers for the set-point error minimization, which respectively regulate the injection’s timing and duration of the pilot-main injection. The controllers are implemented in a FPGA and tested in a Scania D13 engine. The steady-state error reduction, disturbance rejection and transient response are discussed. The results confirm the error reduction in both, cycle-to-cycle and cylinder-to-cylinder variations. The error dispersion, measured by the 95% confidence interval, was reduced between 25% and 75% for all the controlled parameters. By on-line adaptation, the controllers are robust against model uncertainties and fuel types. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/e2f2da25-2348-4012-baf8-fc89b1bd2cf0
- author
- Jorques Moreno, Carlos
LU
; Stenlåås, Ola
LU
and Tunestål, Per
LU
- organization
- publishing date
- 2021-04-14
- type
- Contribution to journal
- publication status
- published
- subject
- in
- IFAC-PapersOnLine
- volume
- 53
- issue
- 2
- pages
- 8 pages
- publisher
- IFAC Secretariat
- conference name
- 21th IFAC World Congress
- conference location
- Berlin, Germany
- conference dates
- 2020-07-12 - 2020-07-17
- external identifiers
-
- scopus:85092738251
- ISSN
- 2405-8963
- DOI
- 10.1016/j.ifacol.2020.12.920
- language
- English
- LU publication?
- yes
- id
- e2f2da25-2348-4012-baf8-fc89b1bd2cf0
- date added to LUP
- 2021-04-20 09:13:27
- date last changed
- 2025-04-04 14:51:24
@article{e2f2da25-2348-4012-baf8-fc89b1bd2cf0,
abstract = {{This paper studies the use of predictive in-cycle close-loop combustion control to reduce the stochastic cyclic variations of diesel combustion. The combustion metrics that fully define the pressure trace with a pilot-main injection i.e. pilot and main start of combustion, burned pilot mass, and engine load are used as the set-point reference. These metrics are in-cycle predicted by calibrated models as functions of the current cylinder state, estimated by in-cylinder pressure measurements. The proposed approach uses four individual controllers for the set-point error minimization, which respectively regulate the injection’s timing and duration of the pilot-main injection. The controllers are implemented in a FPGA and tested in a Scania D13 engine. The steady-state error reduction, disturbance rejection and transient response are discussed. The results confirm the error reduction in both, cycle-to-cycle and cylinder-to-cylinder variations. The error dispersion, measured by the 95% confidence interval, was reduced between 25% and 75% for all the controlled parameters. By on-line adaptation, the controllers are robust against model uncertainties and fuel types.}},
author = {{Jorques Moreno, Carlos and Stenlåås, Ola and Tunestål, Per}},
issn = {{2405-8963}},
language = {{eng}},
month = {{04}},
number = {{2}},
pages = {{14000--14007}},
publisher = {{IFAC Secretariat}},
series = {{IFAC-PapersOnLine}},
title = {{Predictive In-Cycle Closed-Loop Combustion Control with Pilot-Main Injections}},
url = {{http://dx.doi.org/10.1016/j.ifacol.2020.12.920}},
doi = {{10.1016/j.ifacol.2020.12.920}},
volume = {{53}},
year = {{2021}},
}