A computationally efficient Kalman filter based estimator for updating look-up tables applied to NOx estimation in diesel engines

No-x estimation in diesel engines is an up-to-date problem but still some issues need to be solved. Raw sensor signals are not fast enough for real-time use while control-oriented models suffer from drift and aging. A control-oriented gray box model based on engine maps and calibrated off-line is us...

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Autores: Guardiola, Carlos|||0000-0002-3150-8566, Pla Moreno, Benjamín|||0000-0001-9238-2939, Blanco-Rodriguez, David, Eriksson, L.
Tipo de recurso: artículo
Fecha de publicación:2013
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/40391
Acceso en línea:https://riunet.upv.es/handle/10251/40391
Access Level:acceso abierto
Palabra clave:NOx
Kalman filter
Adaptive model
Look-up tables
Diesel
INGENIERIA AEROESPACIAL
MAQUINAS Y MOTORES TERMICOS
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network_name_str España
repository_id_str
spelling A computationally efficient Kalman filter based estimator for updating look-up tables applied to NOx estimation in diesel enginesGuardiola, Carlos|||0000-0002-3150-8566Pla Moreno, Benjamín|||0000-0001-9238-2939Blanco-Rodriguez, DavidEriksson, L.NOxKalman filterAdaptive modelLook-up tablesDieselINGENIERIA AEROESPACIALMAQUINAS Y MOTORES TERMICOSNo-x estimation in diesel engines is an up-to-date problem but still some issues need to be solved. Raw sensor signals are not fast enough for real-time use while control-oriented models suffer from drift and aging. A control-oriented gray box model based on engine maps and calibrated off-line is used as benchmark model for No-x estimation. Calibration effort is important and engine data-dependent. This motivates the use of adaptive look-up tables. In addition to, look-up tables are often used in automotive control systems and there is a need for systematic methods that can estimate or update them on-line. For that purpose, Kalman filter (KF) based methods are explored as having the interesting property of tracking estimation error in a covariance matrix. Nevertheless, when coping with large systems, the computational burden is high, in terms of time and memory, compromising its implementation in commercial electronic control units. However look-up table estimation has a structure, that is here exploited to develop a memory and computationally efficient approximation to the KF, named Simplified Kalman filter (SKF). Convergence and robustness is evaluated in simulation and compared to both a full KF and a minimal steady-state version, that neglects the variance information. SKF is used for the online calibration of an adaptive model for No-x estimation in dynamic engine cycles. Prediction results are compared with the ones of the benchmark model and of the other methods. Furthermore, actual online estimation of No-x is solved by means of the proposed adaptive structure. Results on dynamic tests with a diesel engine and the computational study demonstrate the feasibility and capabilities of the method for an implementation in engine control units. (C) 2013 Elsevier Ltd. All rights reserved.International Federation of Automatic Control (IFAC)Departamento de Máquinas y Motores TérmicosEscuela Técnica Superior de Ingeniería Aeroespacial y Diseño IndustrialInstituto Universitario de Investigación CMT - Clean Mobility & ThermofluidsEscuela Técnica Superior de Ingeniería IndustrialRepositorio Institucional de la Universitat Politècnica de València Riunet20132013-11-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/40391reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Reserva de todos los derechoshttp://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/403912026-06-13T07:49:27Z
dc.title.none.fl_str_mv A computationally efficient Kalman filter based estimator for updating look-up tables applied to NOx estimation in diesel engines
title A computationally efficient Kalman filter based estimator for updating look-up tables applied to NOx estimation in diesel engines
spellingShingle A computationally efficient Kalman filter based estimator for updating look-up tables applied to NOx estimation in diesel engines
Guardiola, Carlos|||0000-0002-3150-8566
NOx
Kalman filter
Adaptive model
Look-up tables
Diesel
INGENIERIA AEROESPACIAL
MAQUINAS Y MOTORES TERMICOS
title_short A computationally efficient Kalman filter based estimator for updating look-up tables applied to NOx estimation in diesel engines
title_full A computationally efficient Kalman filter based estimator for updating look-up tables applied to NOx estimation in diesel engines
title_fullStr A computationally efficient Kalman filter based estimator for updating look-up tables applied to NOx estimation in diesel engines
title_full_unstemmed A computationally efficient Kalman filter based estimator for updating look-up tables applied to NOx estimation in diesel engines
title_sort A computationally efficient Kalman filter based estimator for updating look-up tables applied to NOx estimation in diesel engines
dc.creator.none.fl_str_mv Guardiola, Carlos|||0000-0002-3150-8566
Pla Moreno, Benjamín|||0000-0001-9238-2939
Blanco-Rodriguez, David
Eriksson, L.
author Guardiola, Carlos|||0000-0002-3150-8566
author_facet Guardiola, Carlos|||0000-0002-3150-8566
Pla Moreno, Benjamín|||0000-0001-9238-2939
Blanco-Rodriguez, David
Eriksson, L.
author_role author
author2 Pla Moreno, Benjamín|||0000-0001-9238-2939
Blanco-Rodriguez, David
Eriksson, L.
author2_role author
author
author
dc.contributor.none.fl_str_mv Departamento de Máquinas y Motores Térmicos
Escuela Técnica Superior de Ingeniería Aeroespacial y Diseño Industrial
Instituto Universitario de Investigación CMT - Clean Mobility & Thermofluids
Escuela Técnica Superior de Ingeniería Industrial
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv NOx
Kalman filter
Adaptive model
Look-up tables
Diesel
INGENIERIA AEROESPACIAL
MAQUINAS Y MOTORES TERMICOS
topic NOx
Kalman filter
Adaptive model
Look-up tables
Diesel
INGENIERIA AEROESPACIAL
MAQUINAS Y MOTORES TERMICOS
description No-x estimation in diesel engines is an up-to-date problem but still some issues need to be solved. Raw sensor signals are not fast enough for real-time use while control-oriented models suffer from drift and aging. A control-oriented gray box model based on engine maps and calibrated off-line is used as benchmark model for No-x estimation. Calibration effort is important and engine data-dependent. This motivates the use of adaptive look-up tables. In addition to, look-up tables are often used in automotive control systems and there is a need for systematic methods that can estimate or update them on-line. For that purpose, Kalman filter (KF) based methods are explored as having the interesting property of tracking estimation error in a covariance matrix. Nevertheless, when coping with large systems, the computational burden is high, in terms of time and memory, compromising its implementation in commercial electronic control units. However look-up table estimation has a structure, that is here exploited to develop a memory and computationally efficient approximation to the KF, named Simplified Kalman filter (SKF). Convergence and robustness is evaluated in simulation and compared to both a full KF and a minimal steady-state version, that neglects the variance information. SKF is used for the online calibration of an adaptive model for No-x estimation in dynamic engine cycles. Prediction results are compared with the ones of the benchmark model and of the other methods. Furthermore, actual online estimation of No-x is solved by means of the proposed adaptive structure. Results on dynamic tests with a diesel engine and the computational study demonstrate the feasibility and capabilities of the method for an implementation in engine control units. (C) 2013 Elsevier Ltd. All rights reserved.
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-11-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/40391
url https://riunet.upv.es/handle/10251/40391
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv International Federation of Automatic Control (IFAC)
publisher.none.fl_str_mv International Federation of Automatic Control (IFAC)
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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