Development and validation of a new turbocharger simulation methodology for marine two stroke diesel engine modelling and diagnostic applications

被引:28
作者
Sakellaridis, Nikolaos F. [1 ]
Raptotasios, Spyridon I. [1 ]
Antonopoulos, Antonis K. [1 ]
Mavropoulos, Georgios C. [1 ]
Hountalas, Dimitrios T. [1 ]
机构
[1] Natl Tech Univ Athens, Sch Mech Engn, Dept Thermal Engn, Internal Combust Engines Lab, Athens 15780, Greece
关键词
Two stroke diesel engine; Turbocharger simulation; Engine cycle simulation; Meanline model; MASS-FLOW RATE; PERFORMANCE PREDICTION; PULSATING FLOW; TURBINE; EFFICIENCY; STEADY; LOSSES;
D O I
10.1016/j.energy.2015.08.049
中图分类号
O414.1 [热力学];
学科分类号
摘要
Engine cycle simulation models are increasingly used in diesel engine simulation and diagnostic applications, reducing experimental effort. Turbocharger simulation plays an important role in model's ability to accurately predict engine performance and emissions. The present work describes the development of a complete engine simulation model for marine Diesel engines based on a new methodology for turbocharger modelling utilizing physically based meanline models for compressor and turbine. Simulation accuracy is evaluated against engine bench measurements. The methodology was developed to overcome the problem of limited experimental maps availability for compressor and turbine, often encountered in large marine diesel engine simulation and diagnostic studies. Data from the engine bench are used to calibrate the models, as well as to estimate turbocharger shaft mechanical efficiency. Closed cycle and gas exchange are modelled using an existing multizone thermodynamic model. The proposed methodology is applied on a 2-stroke marine diesel engine and its evaluation is based on the comparison of predictions against measured engine data. It is demonstrated model's ability to predict engine response with load variation regarding both turbocharger performance and closed cycle parameters, as well as NOx emission trends, making it an effective tool for both engine diagnostic and optimization studies. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:952 / 966
页数:15
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