{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T01:10:43Z","timestamp":1789521043419,"version":"build-2803163510"},"reference-count":44,"publisher":"SAGE Publications","issue":"7","license":[{"start":{"date-parts":[[2024,12,29]],"date-time":"2024-12-29T00:00:00Z","timestamp":1735430400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2024,12,29]],"date-time":"2024-12-29T00:00:00Z","timestamp":1735430400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["551990"],"award-info":[{"award-number":["551990"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Engine Research"],"published-print":{"date-parts":[[2025,7]]},"abstract":"<jats:p>\n                    Decarbonizing long-haul goods transportation poses a substantial challenge. High-efficiency natural gas (NG) engines, which retain the efficiency of a diesel engine but reduce the carbon content of the fuel, offer substantial potential for near-term greenhouse gas (GHG) reductions. A fast-running model that can predict engine performance, GHG and air pollutant emissions is critical to assessing this approach for different applications and vehicle drivetrain configurations. This paper presents the development, validation and application of an engine system model that adapts GT-SUITE\u2122\u2019s phenomenological DI-Pulse predictive model to predict the performance and emissions of a 6-cylinder NG engine using a high pressure direct-injection combustion process. The model includes the engine air exchange system, enabling the prediction of the engine and in-cylinder conditions and overall performance over transient drive cycles. The engine model with a fixed set of calibration parameters captures the complex high-pressure direct injection combustion process and generates time-resolved parameters that are fed into a coupled machine learning model to predict emissions, including nitrogen oxide (NOx) and methane (CH\n                    <jats:sub>4<\/jats:sub>\n                    ) emissions. While the 1-D model\u2019s predictions for CH\n                    <jats:sub>4<\/jats:sub>\n                    were not accurate, coupling the 1-D engine model with a machine learning model has been shown to substantially improve the estimation of CH\n                    <jats:sub>4<\/jats:sub>\n                    emissions and allow accurate prediction of engine total GHG emissions over different duty cycles. The model has been validated using transient engine dynamometer data and is then applied to assess performance and emissions over several regulatory and real-world long-haul drive cycles. The model showed an average error of less than 5% in steady operation. Cumulative errors of NOx and CH\n                    <jats:sub>4<\/jats:sub>\n                    emissions in studied cycles were also less than 10%. The results showed that CH\n                    <jats:sub>4<\/jats:sub>\n                    share in total GHG emissions ranges from 0.2% to 1.4% over various drive cycles. By predicting engine performance and emissions, the developed combined model has considerable potential for use in engine evaluation studies, especially when combined with new technologies across different duty cycles.\n                  <\/jats:p>","DOI":"10.1177\/14680874241305732","type":"journal-article","created":{"date-parts":[[2024,12,29]],"date-time":"2024-12-29T23:59:52Z","timestamp":1735516792000},"page":"1070-1087","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":8,"title":["Predicting transient performance of a heavy-duty gaseous-fuelled engine using combined phenomenological and machine learning models"],"prefix":"10.1177","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4446-7561","authenticated-orcid":false,"given":"Navid","family":"Balazadeh","sequence":"first","affiliation":[{"name":"School of Sustainable Energy Engineering, Simon Fraser University, Surrey, BC, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sandeep","family":"Munshi","sequence":"additional","affiliation":[{"name":"Westport Fuel Systems Inc, Vancouver, BC, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahdi","family":"Shahbakhti","sequence":"additional","affiliation":[{"name":"Mechanical Engineering Department, University of Alberta, Edmonton, AB, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9784-6456","authenticated-orcid":false,"given":"Gordon","family":"McTaggart-Cowan","sequence":"additional","affiliation":[{"name":"School of Sustainable Energy Engineering, Simon Fraser University, Surrey, BC, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2024,12,29]]},"reference":[{"key":"e_1_3_4_2_2","unstructured":"Greenhouse Gas Sources and Sinks in Canada: Executive Summary 2022 https:\/\/www.canada.ca\/en\/environment-climate-change\/services\/climate-change\/greenhouse-gas-emissions\/sources-sinks-executive-summary-2022.html (accessed 15 June 2024)."},{"key":"e_1_3_4_3_2","doi-asserted-by":"crossref","unstructured":"Joshi A. Year in review: progress towards decarbonizing transport and near-zero emissions 2023 SAE Technical Paper 2023.","DOI":"10.4271\/2023-01-0396"},{"key":"e_1_3_4_4_2","unstructured":"CO2 emission standards for heavy-duty vehicles https:\/\/ec.europa.eu\/commission\/presscorner\/detail\/en\/qanda_23_763 (accessed 20 June 2024)."},{"key":"e_1_3_4_5_2","unstructured":"Europe proposes world-leading decarbonization targets for trucks and buses The International Council of Clean Transportation https:\/\/theicct.org\/pr-europe-co2-standards-trucks-feb-23\/ (accessed 15 June 2024)."},{"key":"e_1_3_4_6_2","unstructured":"US EPA proposed rule: greenhouse gas emissions standards for heavy-duty vehicles \u2013 phase 3 https:\/\/www.epa.gov\/regulations-emissions-vehicles-and-engines\/proposed-rule-greenhouse-gas-emissions-standards-heavy (accessed on 15 June 2024)."},{"key":"e_1_3_4_7_2","unstructured":"Heavy-Duty Omnibus Regulation | California Air Resources Board https:\/\/ww2.arb.ca.gov\/rulemaking\/2020\/hdomnibuslownox (accessed on 15 June 2024)."},{"key":"e_1_3_4_8_2","doi-asserted-by":"crossref","unstructured":"Joshi A. 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Operation of a natural gas direct injection compression ignition single-cylinder research engine. SAE Technical Paper 2023-01-0260 2023.","DOI":"10.4271\/2023-01-0260"},{"key":"e_1_3_4_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.applthermaleng.2024.123061"},{"key":"e_1_3_4_21_2","article-title":"Effect of injection strategies on emissions from a pilot-ignited direct-injection natural-gas engine \u2013 Part I: Late post injection","author":"Faghani E","unstructured":"Faghani E, Kheirkhah P, Mabson C, et al. Effect of injection strategies on emissions from a pilot-ignited direct-injection natural-gas engine \u2013 Part I: Late post injection. 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