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Digital Twin Test-Bench Performance for Marine Diesel Engine Applications

试验台 汽车工程 燃烧 内燃机 柴油机循环 柴油机 柴油 工程类 计算机科学 环境科学 海洋工程 机械工程 压缩比 化学 有机化学
作者
Dmytro Minchev,Roman Varbanets,Oleksandr Shumylo,Vitalii Zalozh,Nadiia Aleksandrovska,Pavlo Bratchenko,Thanh Hai Truong
出处
期刊:Polish Maritime Research [De Gruyter]
卷期号:30 (4): 81-91 被引量:2
标识
DOI:10.2478/pomr-2023-0061
摘要

Abstract The application of Digital Twins is a promising solution for enhancing the efficiency of marine power plant operation, particularly their important components – marine internal combustion engines (ICE). This work presents the concept of applying a Performance Digital Twin for monitoring the technical condition and diagnosing malfunctions of marine ICE, along with its implementation on an experimental test-bench, based on a marine diesel-generator. The main principles of implementing this concept involve data transmission technologies, from the sensors installed on the engine to a server. The Digital Twin, also operating on the server, is used to automatically process the acquired experimental data, accumulate statistics, determine the current technical state of the engine, identify possible malfunctions, and make decisions regarding changes in operating programs. The core element of the Digital Twin is a mathematical model of the marine diesel engine’s operating cycle. In its development, significant attention was devoted to refining the fuel combustion model, as the combustion processes significantly impact both the engine’s fuel efficiency and the level of toxic emissions of exhaust gases. The enhanced model differs from the base model, by considering the variable value of the average droplets’ diameter during fuel injection. This influence on fuel vapourisation, combustion, and the formation of toxic components is substantial, as shown. Using the example of calibrating the model to the test results of a diesel engine under 27 operating modes, it is demonstrated that the application of the improved combustion model allows better adjustment of the Digital Twin to experimental data, thus achieving a more accurate correspondence to a real engine.
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