DATA-BASED PREDICTION OF SOOT EMISSIONS FOR TRANSIENT ENGINE OPERATION
Michele Schaub
michele.schaub@hs-wismar.deWismar University of Applied Sciences, Faculty of Engineering, Maritime Department (Germany)
https://orcid.org/0000-0002-3566-7572
Abstract
Global vessel traffic is one of the origins responsible for air pollution. Annex VI of the IMO International Convention for the Prevention of Pollution from Ships (MARPOL) focusses on air pollution. Air pollution accrues mainly from energy conversion in combustion engines especially during transient engine operation. One significant pollutant is soot. It represents impure carbon substances in various sizes due to an incomplete combustion of hydrocarbons. This paper focusses on the data-based modelling of soot for transient engine operation in order to predict air pollution in the context of a sophisticated manoeuvring assistance system. In a first step, a stationary approach is investigated and extended for transient engine operation. If one knows about the consequences of his actions, then the role of the human is enforced to decide on energy efficient and emission reduced ship operation, especially during ship manoeuvres.
Keywords:
ship emissions, data processing, predictive modelsReferences
Ayoubi M.: Nonlinear system identification based on neural networks with locally distributed dynamics and application to technical processes. VDI edition, Düsseldorf 1996.
Google Scholar
Bockhorn H.: Soot formation in combustion. Springer edition, Berlin/Heidelberg 1994.
DOI: https://doi.org/10.1007/978-3-642-85167-4
Google Scholar
Dahms F., Reska M., Nocke J., Hassel E., Reißig M., Schaub M.: Characterizing of transient engine operating with investigation on particle size distribution on a four-stroke medium-speed engine. CIMAC 2019.
Google Scholar
http://www.imo.org/en/KnowledgeCentre/IndexofIMOResolutions/Marine-Environment-Protection-Committee-(MEPC)/Documents/MEPC.176(58).pdf (available: 24.07.2019).
Google Scholar
https://issims-gmbh.com/yoomla/products/sammon (available: 24.07.2019).
Google Scholar
Isermann R.: Engine Modeling and Control. Springer edition, Heidelberg 2014.
DOI: https://doi.org/10.1007/978-3-642-39934-3
Google Scholar
Nelles O.: Nonlinear System Identification. Springer, Heidelberg 2001.
DOI: https://doi.org/10.1007/978-3-662-04323-3
Google Scholar
Rohs H.: Simulation des transienten Betriebsverhalten von aufgeladenen Dieselmotoren. PhD Thesis, TH Aachen, 2006.
Google Scholar
Schaub M., Finger G., Dahms F., Hassel E., Jeinsch T., Kirchhoff M.: Data-based prediction of particle emissions during manoeuvring of ships. IIPhdW 2019.
DOI: https://doi.org/10.1109/IIPHDW.2019.8755419
Google Scholar
Schaub M., Finger G., Riebe T., Dahms F., Hassel E., Baldauf M.: Data-based modelling of ship emissions and fuel oil consumption for transient engine operation. OCEANS 2019.
DOI: https://doi.org/10.1109/OCEANSE.2019.8867061
Google Scholar
Wenzel S.P.: Modellierung der Ruß- und NOX-Emissionen des Dieselmotors. PhD thesis, Otto-von-Guericke-Universität Magdeburg, 2006.
Google Scholar
Authors
Michele Schaubmichele.schaub@hs-wismar.de
Wismar University of Applied Sciences, Faculty of Engineering, Maritime Department Germany
https://orcid.org/0000-0002-3566-7572
Michèle Schaub grew up in Switzerland. After finishing high school, she studied Comparative Religious Studies in Fribourg/CH before she discovered her passion for seafaring. 2006 she started her maritime studies at Wismar University (B.Sc.) and became a navigational officer on board a general cargo ship. After several years in practice, she began her work in maritime research at the Maritime Department of Wismar University accompanied by a distance learning course in environmental protection at University of Rostock (M.Sc.). She is currently working on her doctoral thesis, in which she combines seafaring and environmental protection.
Statistics
Abstract views: 417PDF downloads: 245
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.