Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/172465
Title: Modelling treatment of deposits in particulate filters for internal combustion emissions
Authors: Lao, Chung Ting
Akroyd, Jethro
Kraft, Markus
Keywords: Engineering::Chemical engineering
Issue Date: 2023
Source: Lao, C. T., Akroyd, J. & Kraft, M. (2023). Modelling treatment of deposits in particulate filters for internal combustion emissions. Progress in Energy and Combustion Science, 96, 101043-. https://dx.doi.org/10.1016/j.pecs.2022.101043
Journal: Progress in Energy and Combustion Science 
Abstract: Internal combustion in transport vehicles is still one of the biggest contributors to ultrafine particle emissions which have been proven to have many adverse effects on human health and the environment in general. To mitigate this problem a variety of particle filters have been developed and along with these filters a whole range of models aiming to optimise filter performance. This paper reviews a wide variety of particulate filter models for vehicular emission control and presents the volume of work in a unified and consistent notation. Particle filtration models are examined with respect to their filtration efficiency, the way they handle particle deposits within the filter wall, the formation of filter cake and the role of catalytic conversion and the effect of gaseous emission. Further, the impact of the chemical and physical properties of particulate deposits on the filter regeneration process is analysed and reaction pathways and rates are presented. In addition the accumulation of ash deposits and its impact on the filter behaviour is critically reviewed. Finally, various measures are identified that can potentially improve the current particle filter models.
URI: https://hdl.handle.net/10356/172465
ISSN: 0360-1285
DOI: 10.1016/j.pecs.2022.101043
Schools: School of Chemical and Biomedical Engineering 
Organisations: Cambridge Centre for Advanced Research and Education in Singapore 
Rights: © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCBE Journal Articles

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