Comparing different approaches for estimating tailpipe emissions in passenger cars

Detalhes bibliográficos
Autor(a) principal: Fernandes, Paulo
Data de Publicação: 2022
Outros Autores: Ferreira, Elisabete, Amorim, Paulo, Coelho, Margarida C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10773/33633
Resumo: Vehicles with Internal Combustion Engines (ICE) still represent the most prevalent form of road transport in Europe, being an important source of both greenhouse gases and air pollutants. In response to these concerns, Portable Emission Measurement Systems (PEMS) have been widely used by researchers to measure tailpipe emissions and to detect cheating of emissions regulations by manufacturers. This paper introduces four different approaches to estimate carbon dioxide (CO2) and nitrogen oxides (NOx) emissions for these vehicles. These approaches were based on: i) speed intervals (≤50 km.h-1, 50-90 km.h-1, ≥ 90 km.h-1); ii) internally observable variables (IOVs); iii) vehicle specific power (VSP); and iv) driving volatility indicators. The development of IOVs models was made by testing the most significant parameters on CO2 and NOx emission rates, which included the engine revolution per minute (RPM), manifold absolute pressure (MAP), and intake air temperate (IAT). VSP-modal approach centred on binning emission rates in 14 models that reflects deceleration, idling, cruise, and acceleration states. Driver volatility was characterized by means of vehicular jerk (i.e., first derivate of acceleration) using nine combinations of vehicular jerk types. To obtain real world emissions, data were collected from one petrol and one diesel passenger cars using an integrated PEMS. IOVs and jerk models based on the product of MAP and RPM presented similar CO2 compared to measured values for both vehicles, but they resulted in higher overestimation of NOx than a VSP-modal approach. The proposed methodology can be extended to other individual ICE or alternative fuel vehicles for which it may be expensive to get emissions, engine, and dynamic data.
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spelling Comparing different approaches for estimating tailpipe emissions in passenger carsVehicle EmissionsPredictive ModelsSpeedInternally observable variablesVehicle specific powerDriving volatilityVehicles with Internal Combustion Engines (ICE) still represent the most prevalent form of road transport in Europe, being an important source of both greenhouse gases and air pollutants. In response to these concerns, Portable Emission Measurement Systems (PEMS) have been widely used by researchers to measure tailpipe emissions and to detect cheating of emissions regulations by manufacturers. This paper introduces four different approaches to estimate carbon dioxide (CO2) and nitrogen oxides (NOx) emissions for these vehicles. These approaches were based on: i) speed intervals (≤50 km.h-1, 50-90 km.h-1, ≥ 90 km.h-1); ii) internally observable variables (IOVs); iii) vehicle specific power (VSP); and iv) driving volatility indicators. The development of IOVs models was made by testing the most significant parameters on CO2 and NOx emission rates, which included the engine revolution per minute (RPM), manifold absolute pressure (MAP), and intake air temperate (IAT). VSP-modal approach centred on binning emission rates in 14 models that reflects deceleration, idling, cruise, and acceleration states. Driver volatility was characterized by means of vehicular jerk (i.e., first derivate of acceleration) using nine combinations of vehicular jerk types. To obtain real world emissions, data were collected from one petrol and one diesel passenger cars using an integrated PEMS. IOVs and jerk models based on the product of MAP and RPM presented similar CO2 compared to measured values for both vehicles, but they resulted in higher overestimation of NOx than a VSP-modal approach. The proposed methodology can be extended to other individual ICE or alternative fuel vehicles for which it may be expensive to get emissions, engine, and dynamic data.Elsevier2022-04-06T15:48:03Z2022-01-01T00:00:00Z2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/33633eng10.1016/j.trpro.2022.02.063Fernandes, PauloFerreira, ElisabeteAmorim, PauloCoelho, Margarida C.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T12:04:22Zoai:ria.ua.pt:10773/33633Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:04:53.251535Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Comparing different approaches for estimating tailpipe emissions in passenger cars
title Comparing different approaches for estimating tailpipe emissions in passenger cars
spellingShingle Comparing different approaches for estimating tailpipe emissions in passenger cars
Fernandes, Paulo
Vehicle Emissions
Predictive Models
Speed
Internally observable variables
Vehicle specific power
Driving volatility
title_short Comparing different approaches for estimating tailpipe emissions in passenger cars
title_full Comparing different approaches for estimating tailpipe emissions in passenger cars
title_fullStr Comparing different approaches for estimating tailpipe emissions in passenger cars
title_full_unstemmed Comparing different approaches for estimating tailpipe emissions in passenger cars
title_sort Comparing different approaches for estimating tailpipe emissions in passenger cars
author Fernandes, Paulo
author_facet Fernandes, Paulo
Ferreira, Elisabete
Amorim, Paulo
Coelho, Margarida C.
author_role author
author2 Ferreira, Elisabete
Amorim, Paulo
Coelho, Margarida C.
author2_role author
author
author
dc.contributor.author.fl_str_mv Fernandes, Paulo
Ferreira, Elisabete
Amorim, Paulo
Coelho, Margarida C.
dc.subject.por.fl_str_mv Vehicle Emissions
Predictive Models
Speed
Internally observable variables
Vehicle specific power
Driving volatility
topic Vehicle Emissions
Predictive Models
Speed
Internally observable variables
Vehicle specific power
Driving volatility
description Vehicles with Internal Combustion Engines (ICE) still represent the most prevalent form of road transport in Europe, being an important source of both greenhouse gases and air pollutants. In response to these concerns, Portable Emission Measurement Systems (PEMS) have been widely used by researchers to measure tailpipe emissions and to detect cheating of emissions regulations by manufacturers. This paper introduces four different approaches to estimate carbon dioxide (CO2) and nitrogen oxides (NOx) emissions for these vehicles. These approaches were based on: i) speed intervals (≤50 km.h-1, 50-90 km.h-1, ≥ 90 km.h-1); ii) internally observable variables (IOVs); iii) vehicle specific power (VSP); and iv) driving volatility indicators. The development of IOVs models was made by testing the most significant parameters on CO2 and NOx emission rates, which included the engine revolution per minute (RPM), manifold absolute pressure (MAP), and intake air temperate (IAT). VSP-modal approach centred on binning emission rates in 14 models that reflects deceleration, idling, cruise, and acceleration states. Driver volatility was characterized by means of vehicular jerk (i.e., first derivate of acceleration) using nine combinations of vehicular jerk types. To obtain real world emissions, data were collected from one petrol and one diesel passenger cars using an integrated PEMS. IOVs and jerk models based on the product of MAP and RPM presented similar CO2 compared to measured values for both vehicles, but they resulted in higher overestimation of NOx than a VSP-modal approach. The proposed methodology can be extended to other individual ICE or alternative fuel vehicles for which it may be expensive to get emissions, engine, and dynamic data.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-06T15:48:03Z
2022-01-01T00:00:00Z
2022
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10773/33633
url http://hdl.handle.net/10773/33633
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1016/j.trpro.2022.02.063
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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