https://search.dev.ndltd.org/etd/bradford/oai:bradscholars.brad.ac.uk:10454/17403
type: CreativeWork
name: Multi-Physics Co-Simulation of Engine Combustion and Exhaust Aftertreatment system: Development of a Multi-Physics Co-Simulation Framework of Engine Combustion and Exhaust Aftertreatment for Model-Based System Optimisation
description: The incorporation of detailed chemistry models in internal combustion engine simulations is becoming mandatory as new combustion strategies and lower global emissions limits are setting the path towards a more efficient engine cycle simulation tool. In this report, the computational capability of the stochastic-based Kinetics SRM engine suite by CMCL Innovations is evaluated in depth. With the main objectives of this research to create a multi-physics co-simulation framework and improve the traditional engine modelling approach of individual simulation of engine system parts, the Kinetics SRM code was coupled with a GT-SUITE engine model to fill in the gap of accurate emissions predictions from one-dimensional simulation tools. The system was validated against testing points collected from the AJ133 V8 5L GDI engine running on the NEDC. The Kinetics SRM model is further advanced through a sensitivity analysis for the “unknown” internal parameters of the chemistry tool. A set of new parameters’ values has been established that gives the best overall trade-off between prediction accuracy and computational time. However, it still showed high percentage errors in modelling the emissions and it was discovered that the specific software package currently cannot simulate directed injection events. This is the first time a Kinetics SRM/GT-SUITE coupled code is employed to model a full 8-cylinder GDI SI engine. The approach showed some limitations regarding the Kinetics SRM and that in many cases is limited to trend analysis. The coupled engine – combustion emissions model is then linked with an exhaust aftertreatment system model in MATLAB Simulink, creating a multi-physics model-based co-simulation framework of engine performance, combustion characterisation, in-cylinder emissions formation and aftertreatment efficiency.
abstract: The incorporation of detailed chemistry models in internal combustion engine simulations is becoming mandatory as new combustion strategies and lower global emissions limits are setting the path towards a more efficient engine cycle simulation tool. In this report, the computational capability of the stochastic-based Kinetics SRM engine suite by CMCL Innovations is evaluated in depth. With the main objectives of this research to create a multi-physics co-simulation framework and improve the traditional engine modelling approach of individual simulation of engine system parts, the Kinetics SRM code was coupled with a GT-SUITE engine model to fill in the gap of accurate emissions predictions from one-dimensional simulation tools. The system was validated against testing points collected from the AJ133 V8 5L GDI engine running on the NEDC. The Kinetics SRM model is further advanced through a sensitivity analysis for the “unknown” internal parameters of the chemistry tool. A set of new parameters’ values has been established that gives the best overall trade-off between prediction accuracy and computational time. However, it still showed high percentage errors in modelling the emissions and it was discovered that the specific software package currently cannot simulate directed injection events. This is the first time a Kinetics SRM/GT-SUITE coupled code is employed to model a full 8-cylinder GDI SI engine. The approach showed some limitations regarding the Kinetics SRM and that in many cases is limited to trend analysis. The coupled engine – combustion emissions model is then linked with an exhaust aftertreatment system model in MATLAB Simulink, creating a multi-physics model-based co-simulation framework of engine performance, combustion characterisation, in-cylinder emissions formation and aftertreatment efficiency.
author: Themi, Vasos
language: en
keywords: Model-based, Multi-physics, Co-simulation, Engine powertrain
date modified: 2026-07-24T01:13:10Z
provider: University of Bradford
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Bradford

PropertyValue
property ID: Handle
value: http://hdl.handle.net/10454/17403