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Parameterizing Compact and Extensible Compressor Models Using Orthogonal Distance Minimization
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-1584-8165
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-8646-8998
2016 (English)In: Journal of engineering for gas turbines and power, ISSN 0742-4795, E-ISSN 1528-8919, Vol. 139, no 1, p. 012601-1-012601-10, article id GTP-15-1569Article in journal (Refereed) Published
Abstract [en]

A complete and compact control-oriented compressor model consisting of a mass flow submodel and an efficiency submodel is described. The final application of the model is a complete two-stroke mean value engine model (MVEM) which requires simulating the compressor operating at the low-flow and low-pressure ratio area. The model is based on previous research done for automotive-size compressors, and it is shown to be general enough to adapt well to the characteristics of the marine-size compressors. A physics-based efficiency model allows, together with the mass flow model, extrapolating to low-pressure ratios. The complexity of the model makes its parameterization a difficult task; hence, a method to efficiently estimate the 19 model parameters is proposed. The method computes analytic model gradients and uses them to minimize the orthogonal distances between the modeled speed lines (SpLs) and the measured points. The results of the parameter estimation are tested against nine different standard marine-size maps showing good agreement with the measured data. Furthermore, the results also show the importance of estimating the parameters of the mass flow and efficiency submodels at the same time to obtain an accurate model. The extrapolation capabilities to low-load regions are also tested using low-load measurements from an automotive-size compressor. It is shown that the model follows the measured efficiency trend down to low loads.

Place, publisher, year, edition, pages
ASME Press, 2016. Vol. 139, no 1, p. 012601-1-012601-10, article id GTP-15-1569
National Category
Applied Mechanics
Identifiers
URN: urn:nbn:se:liu:diva-136199DOI: 10.1115/1.4034152ISI: 000395511600016OAI: oai:DiVA.org:liu-136199DiVA, id: diva2:1086593
Note

Funding Agencies|European Union [634135]

Available from: 2017-04-03 Created: 2017-04-03 Last updated: 2018-09-26
In thesis
1. Modeling and Control of EGR on Marine Two-Stroke Diesel Engines
Open this publication in new window or tab >>Modeling and Control of EGR on Marine Two-Stroke Diesel Engines
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The international marine shipping industry is responsible for the transport of around 90% of the total world trade. Low-speed two-stroke diesel engines usually propel the largest trading ships. This engine type choice is mainly motivated by its high fuel efficiency and the capacity to burn cheap low-quality fuels. To reduce the marine freight impact on the environment, the International Maritime Organization (IMO) has introduced stricter limits on the engine pollutant emissions. One of these new restrictions, named Tier III, sets the maximum NOx emissions permitted. New emission reduction technologies have to be developed to fulfill the Tier III limits on two-stroke engines since adjusting the engine combustion alone is not sufficient. There are several promising technologies to achieve the required NOx reductions, Exhaust Gas Recirculation (EGR) is one of them.  For automotive applications, EGR is a mature technology, and many of the research findings can be used directly in marine applications. However, there are some differences in marine two-stroke engines, which require further development to apply and control EGR.

The number of available engines for testing EGR controllers on ships and test beds is low due to the recent introduction of EGR. Hence, engine simulation models are a good alternative for developing controllers, and many different engine loading scenarios can be simulated without the high costs of running real engine tests. The primary focus of this thesis is the development and validation of models for two-stroke marine engines with EGR. The modeling follows a Mean Value Engine Model (MVEM) approach, which has a low computational complexity and permits faster than real-time simulations suitable for controller testing. A parameterization process that deals with the low measurement data availability, compared to the available data on automotive engines, is also investigated and described. As a result, the proposed model is parameterized to two different two-stroke engines showing a good agreement with the measurements in both stationary and dynamic conditions.

Several engine components have been developed. One of these is a new analytic in-cylinder pressure model that captures the influence of the injection and exhaust valve timings without increasing the simulation time. A new compressor model that can extrapolate to low speeds and pressure ratios in a physically sound way is also described. This compressor model is a requirement to be able to simulate low engine loads. Moreover, a novel parameterization algorithm is shown to handle well the model nonlinearities and to obtain a good model agreement with a large number of tested compressor maps. Furthermore, the engine model is complemented with dynamic models for ship and propeller to be able to simulate transient sailing scenarios, where good EGR controller performance is crucial. The model is used to identify the low load area as the most challenging for the controller performance, due to the slower engine air path dynamics. Further low load simulations indicate that sensor bias can be problematic and lead to an undesired black smoke formation, while errors in the parameters of the controller flow estimators are not as critical. This result is valuable because for a newly built engine a proper sensor setup is more straightforward to verify than to get the right parameters for the flow estimators.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2018. p. 200
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1904
Keywords
Modeling for control, Ship Propulsion, Dynamic Simulation, Exhaust Gas Recirculation, Mean Value Engine Model, Parameterization, Compressor, Model Extrapolation
National Category
Control Engineering Vehicle Engineering
Identifiers
urn:nbn:se:liu:diva-144596 (URN)10.3384/diss.diva-144596 (DOI)9789176853689 (ISBN)
Public defence
2018-03-23, Ada Lovelace, Ingång 27, B-huset, Campus Valla, Linköping, 10:15 (English)
Opponent
Supervisors
Funder
EU, Horizon 2020, 634135VINNOVA, LINK-SIC
Available from: 2018-01-30 Created: 2018-01-30 Last updated: 2018-05-15Bibliographically approved

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Llamas, XavierEriksson, Lars

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