{"id":{"repo_id":"bradford","oai_identifier":"oai:bradscholars.brad.ac.uk:10454/19084"},"canonical_url":"https://search.dev.ndltd.org/etd/bradford/oai:bradscholars.brad.ac.uk:10454/19084","repository":{"repo_id":"bradford","name":"University of Bradford","base_url":"https://bradscholars.brad.ac.uk/oai/request"},"display":{"title":"Multi-Physics Engine Simulation Framework for Drive Cycle Emissions Prediction. Development and Validation of a Framework for Transient Drive Cycle NOx Prediction Modelling based on Combining 1-D and 0-D Internal Combustion Engine Simulation and Statistical Meta-Modelling","abstract":"Real-time full powertrain drive cycle simulations with high-fidelity engine-out NOx emissions prediction capability is a significant challenge nowadays. Specifically, being able to perform these simulations early in engine development process would allow powertrain optimisation in virtual space, leading to reduction in powertrain development cost and time saving benefits. This thesis presents the development of a Multi-Physics Engine Simulation (MPES) platform to address this challenge. The development of the MPES platform is based on a coupled virtual 2.0 litre Diesel engine model (GT- Suite 1-D air path model) and in-cylinder combustion model (CMCL Stochastic Reactor Model (SRM) Engine Suite). A set of steady state and drive cycle physical measurements obtained from physical engine testing on a dynamometer was available for the calibration and validation of the simulation models and the MPES framework. A comprehensive study on SRM NOx prediction potential is presented, underpinned by a detailed space-filling design of experiments (DoE)-based sensitivity analysis of both external and internal parameters, evaluating their effects on the accuracy in matching physical measurements of both in-cylinder conditions and NOx output. Moreover, an automatic stochastic reactor engine model calibration methodology across the engine operating envelope, based on a multi-objective optimization approach is presented. Real-time simulation capability for the MPES platform was achieved by substituting the time-expensive combustion chemistry solver (SRM) with a surrogate model for NOx emissions, based on OLH experiments replicating steady state testing, on the engine simulation platform. The transient performance of MPES was validated on a simulated NEDC drive cycle, against the experimental data available. The capability of MPES to capture the transient NOx trends and values shows promising results and reveals great potential for further exploration and application to powertrain development process.","abstract_html":"Real-time full powertrain drive cycle simulations with high-fidelity engine-out NOx emissions prediction capability is a significant challenge nowadays. Specifically, being able to perform these simulations early in engine development process would allow powertrain optimisation in virtual space, leading to reduction in powertrain development cost and time saving benefits. This thesis presents the development of a Multi-Physics Engine Simulation (MPES) platform to address this challenge. The development of the MPES platform is based on a coupled virtual 2.0 litre Diesel engine model (GT- Suite 1-D air path model) and in-cylinder combustion model (CMCL Stochastic Reactor Model (SRM) Engine Suite). A set of steady state and drive cycle physical measurements obtained from physical engine testing on a dynamometer was available for the calibration and validation of the simulation models and the MPES framework. A comprehensive study on SRM NOx prediction potential is presented, underpinned by a detailed space-filling design of experiments (DoE)-based sensitivity analysis of both external and internal parameters, evaluating their effects on the accuracy in matching physical measurements of both in-cylinder conditions and NOx output. Moreover, an automatic stochastic reactor engine model calibration methodology across the engine operating envelope, based on a multi-objective optimization approach is presented. Real-time simulation capability for the MPES platform was achieved by substituting the time-expensive combustion chemistry solver (SRM) with a surrogate model for NOx emissions, based on OLH experiments replicating steady state testing, on the engine simulation platform. The transient performance of MPES was validated on a simulated NEDC drive cycle, against the experimental data available. The capability of MPES to capture the transient NOx trends and values shows promising results and reveals great potential for further exploration and application to powertrain development process.","abstract_has_math":false,"creators":["Korsunovs, Aleksandrs"],"institution":"University of Bradford","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Campean, Felician"],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019","date_published":"2019","updated_at":"2026-07-24T01:12:58Z","subjects":["Engine modelling","Stochastic Reactor Model","Thermodynamic models","Emissions prediction","Metamodelling","OLH Design of Experiments","NOx prediction modelling","Internal combustion engine simulation"],"languages":["en"],"rights":["<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/3.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png\" /></a><br />The University of Bradford theses are licenced under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/3.0/\">Creative Commons Licence</a>."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10454/19084","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Campean, Felician"]},{"key":"dc:creator","label":"Author","values":["Korsunovs, Aleksandrs"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-08-02T14:00:24Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-08-02T14:00:24Z"]},{"key":"dc:date.issued","label":"Date","values":["2019"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Faculty of Engineering and Informatics"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Bradford"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["PhD"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engine modelling","Stochastic Reactor Model","Thermodynamic models","Emissions prediction","Metamodelling","OLH Design of Experiments","NOx prediction modelling","Internal combustion engine simulation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/3.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png\" /></a><br />The University of Bradford theses are licenced under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/3.0/\">Creative Commons Licence</a>."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10454/19084"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Real-time full powertrain drive cycle simulations with high-fidelity engine-out NOx emissions prediction capability is a significant challenge nowadays. Specifically, being able to perform these simulations early in engine development process would allow powertrain optimisation in virtual space, leading to reduction in powertrain development cost and time saving benefits. This thesis presents the development of a Multi-Physics Engine Simulation (MPES) platform to address this challenge. The development of the MPES platform is based on a coupled virtual 2.0 litre Diesel engine model (GT- Suite 1-D air path model) and in-cylinder combustion model (CMCL Stochastic Reactor Model (SRM) Engine Suite). A set of steady state and drive cycle physical measurements obtained from physical engine testing on a dynamometer was available for the calibration and validation of the simulation models and the MPES framework. A comprehensive study on SRM NOx prediction potential is presented, underpinned by a detailed space-filling design of experiments (DoE)-based sensitivity analysis of both external and internal parameters, evaluating their effects on the accuracy in matching physical measurements of both in-cylinder conditions and NOx output. Moreover, an automatic stochastic reactor engine model calibration methodology across the engine operating envelope, based on a multi-objective optimization approach is presented. Real-time simulation capability for the MPES platform was achieved by substituting the time-expensive combustion chemistry solver (SRM) with a surrogate model for NOx emissions, based on OLH experiments replicating steady state testing, on the engine simulation platform. The transient performance of MPES was validated on a simulated NEDC drive cycle, against the experimental data available. The capability of MPES to capture the transient NOx trends and values shows promising results and reveals great potential for further exploration and application to powertrain development process."]},{"key":"dc:title","label":"Title","values":["Multi-Physics Engine Simulation Framework for Drive Cycle Emissions Prediction. Development and Validation of a Framework for Transient Drive Cycle NOx Prediction Modelling based on Combining 1-D and 0-D Internal Combustion Engine Simulation and Statistical Meta-Modelling"]}]}],"canonical_facts":{"dc:contributor.advisor":["Campean, Felician"],"dc:creator":["Korsunovs, Aleksandrs"],"dc:date.accessioned":["2022-08-02T14:00:24Z"],"dc:date.available":["2022-08-02T14:00:24Z"],"dc:date.issued":["2019"],"dc:description.abstract":["Real-time full powertrain drive cycle simulations with high-fidelity engine-out NOx emissions prediction capability is a significant challenge nowadays. Specifically, being able to perform these simulations early in engine development process would allow powertrain optimisation in virtual space, leading to reduction in powertrain development cost and time saving benefits. This thesis presents the development of a Multi-Physics Engine Simulation (MPES) platform to address this challenge. The development of the MPES platform is based on a coupled virtual 2.0 litre Diesel engine model (GT- Suite 1-D air path model) and in-cylinder combustion model (CMCL Stochastic Reactor Model (SRM) Engine Suite). A set of steady state and drive cycle physical measurements obtained from physical engine testing on a dynamometer was available for the calibration and validation of the simulation models and the MPES framework. A comprehensive study on SRM NOx prediction potential is presented, underpinned by a detailed space-filling design of experiments (DoE)-based sensitivity analysis of both external and internal parameters, evaluating their effects on the accuracy in matching physical measurements of both in-cylinder conditions and NOx output. Moreover, an automatic stochastic reactor engine model calibration methodology across the engine operating envelope, based on a multi-objective optimization approach is presented. Real-time simulation capability for the MPES platform was achieved by substituting the time-expensive combustion chemistry solver (SRM) with a surrogate model for NOx emissions, based on OLH experiments replicating steady state testing, on the engine simulation platform. The transient performance of MPES was validated on a simulated NEDC drive cycle, against the experimental data available. The capability of MPES to capture the transient NOx trends and values shows promising results and reveals great potential for further exploration and application to powertrain development process."],"dc:identifier.uri":["http://hdl.handle.net/10454/19084"],"dc:language.iso":["en"],"dc:publisher.department":["Faculty of Engineering and Informatics"],"dc:publisher.institution":["University of Bradford"],"dc:rights":["<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/3.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png\" /></a><br />The University of Bradford theses are licenced under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/3.0/\">Creative Commons Licence</a>."],"dc:subject":["Engine modelling","Stochastic Reactor Model","Thermodynamic models","Emissions prediction","Metamodelling","OLH Design of Experiments","NOx prediction modelling","Internal combustion engine simulation"],"dc:title":["Multi-Physics Engine Simulation Framework for Drive Cycle Emissions Prediction. Development and Validation of a Framework for Transient Drive Cycle NOx Prediction Modelling based on Combining 1-D and 0-D Internal Combustion Engine Simulation and Statistical Meta-Modelling"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["PhD"]},"updated_at":"2026-07-24T01:12:58Z"}