Understanding the influence of intake valve deposits on ICE performance
Lead Research Organisation:
University of Cambridge
Department Name: Chemical Engineering and Biotechnology
Abstract
The project will investigate the influence of intake valve deposits (IVDS) on the combustion performance of naturally aspirated and turbocharged gasoline fuelled internal combustion engines (ICEs) using state-of-the-art computational modelling.
A stochastic reactor model will be set up to simulate steady state operating points for both fuel injection and direct injection spark ignition engines with varying levels of IVDs. The impact of the IVDs on the combustion characteristics of the engine will be investigated. The resulting stochastic reactor model simulations, including the description of the IVDs will be coupled to a 1D engine cycle simulator and, using 1D engine maps provided by Shell, will be applied to investigate the impact of the IVDs on the overall engine performance.
A stochastic reactor model will be set up to simulate steady state operating points for both fuel injection and direct injection spark ignition engines with varying levels of IVDs. The impact of the IVDs on the combustion characteristics of the engine will be investigated. The resulting stochastic reactor model simulations, including the description of the IVDs will be coupled to a 1D engine cycle simulator and, using 1D engine maps provided by Shell, will be applied to investigate the impact of the IVDs on the overall engine performance.
People |
ORCID iD |
| Markus Kraft (Primary Supervisor) | |
| Chung Lao (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/N509103/1 | 01/10/2015 | 31/03/2022 | |||
| 1622599 | Studentship | EP/N509103/1 | 01/10/2015 | 30/09/2019 | Chung Lao |
| Description | A numerical model for exhaust after-treatment devices for internal combustion engines has been developed. By comparing model predictions with experimental results, the proposed model is able to better describe the filtration performance of after-treatment device on particulate emission from diesel engines than classic model found in literature. Potential processes that could bridge the gap between classic model prediction and experimental observation are identified. |
| Exploitation Route | The performance of the proposed model may be evaluated against more experimental data-sets provided by academic experimentalists or manufacturers. The predictability of the proposed model may be improved by working with other computational modeling experts who specialises in nano-scale simulations, where the inherent physical processes may be investigated in greater detail. |
| Sectors | Environment,Transport |
| Title | Research data supporting "Modelling Particle Mass and Particle Number Emissions during the Active Regeneration of Diesel Particulate Filters" |
| Description | This is a repository of input files, executable codes, output files and post-processing scripts required to re-produce the results and figures for the paper "Modelling Particle Mass and Particle Number Emissions during the Active Regeneration of Diesel Particulate Filters". |
| Type Of Material | Database/Collection of data |
| Year Produced | 2018 |
| Provided To Others? | Yes |