Improvement of Intelligent Internal Combustion Engines (2025)

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System of operation monitoring and of early detection of technical condition changes of a marine piston diesel engine based on artificial intelligence

Dariusz Pielka

2009

In the modern systems of operation monitoring and of early detection of technical condition changes, additionally to the monitoring and measuring function, there is required the analysis of information in purpose to support the operator in making decisions. Such high complexity of a problem needs application of the fast methods of analysing the information in variety of aspects. Presently, in monitoring of a marine piston diesel engine tremendous importance the methods have, which are based on artificial intelligence both in a meaning of analysis of the individual processes and in complex analysis of a whole object. Merits of the artificial intelligence methods arehigh flexibility, versatility and possibility to use the object for analysis with no need to have a mathematical description of the examined object, or occurring processes, what often imposes the considerable difficulty and restrictions in examination to be carried out. Słowa kluczowe: okrętowy silnik o zapłonie samoczynnym, monitoring, bezpieczeństwo, sztuczna inteligencja Abstrakt Od dzisiejszych systemów kontroli pracy i wczesnej detekcji zmian stanu technicznego, oprócz funkcji kontrolno-pomiarowej, wymaga się analizy informacji, których zadaniem ma być wspieranie operatora w podejmowaniu decyzji. Tak duża złożoność problemu wymaga zastosowania szybkich metod wielotorowo analizujących informacje. Aktualnie w kontroli pracy okrętowego silnika spalinowego olbrzymie znaczenie mają metody oparte na sztucznej inteligencji zarówno w rozumieniu analizy poszczególnych procesów, jak i analizy kompleksowej całego obiektu. Zaletą metod sztucznej inteligencji jest ich duża elastyczność, uniwersalność i możliwość wykorzystania do analizy obiektu bez potrzeby posiadania matematycznego opisu badanego obiektu i zachodzących procesów, co często stanowi poważną trudność i ograniczenia w przeprowadzeniu badań.

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Prediction of Internal Combustion Engine Performance Using Artificial Intelligence

Lukman Shalahuddin

Majalah Ilmiah Pengkajian Industri

The potential of artificial intelligence (AI) application for prediction of internal combustion engine performance is assessed in this paper. A literature survey on this subject is first reviewed, in which previous researches utilized the advance of artificial neural networks (ANN) as one type of AI. Previous works commonly obtained the data from experimental engine tests. Under the same engines, they varied the fuel compositions or the engine operating conditions. Whereas in this study, an ANN model is developed to calculate the inputs from an engine simulation software package database and to predict the engine performance based on the simulation software outputs as the ANN target outputs. Results from the ANN model in the “learning” step indicates good agreement with the software simulation outputs. Improvement and development of the program are required, including optimation of the ANN model architecture, such as the choice of activation function, the number of neurons in the hi...

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Performance analysis of artificial neural networks for control in internal combustion engines

Nicola Matteazzi

SECOND INTERNATIONAL CONFERENCE ON MATERIAL SCIENCE, SMART STRUCTURES AND APPLICATIONS: ICMSS-2019

In the last years the Electronic Control Units (ECUs) technology has evolved both in terms of hardware and firmware. The tasks requested to ECUs are, as a matter of fact, ever more challenging, due to the growing complexity of the internal combustion engines control, causing increasing needs in terms of computational speed, as well as memory amount. In order to limit look up tables and white box models in ECUs, also Artificial Neural Networks (ANNs) were proposed for the use in different types of tasks, as On-Board Diagnosis, virtual sensors and ECU look up table replacement. ANNs showed a good performance in all these cases. In this paper, the application of ANNs as virtual sensors is further analyzed, in particular in order to verify their performance when used to setup multiple sensors by using a single ANN module. In this work ANNs were used to evaluate pressure and flowrate in different points of a lubrication circuit of bench and connecting rod bearings.

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Condition Monitoring and Fault Diagnosis of a Marine Diesel Engine with Machine Learning Techniques

Gazi Kocak

Pomorstvo

A marine engine room is a complex system in which many different subsystems are interacting with each other. At the center of this system is the main diesel engine which produces the propulsion force. Many other components such as compressed air, cooling, heating, lubricating oil, fuel, and pumping systems act as auxiliary machines to the main engine. Automation of many functions in the engine room is starting to play an important role in new generation ships to provide better control using sensors monitoring the engine and its environment. Sensors exist in the current generation ships, but engineers evaluate the sensor data for the presence of any problems. Maintenance actions are taken based on these manual analyses or regular maintenance is carried out at times determined by manufacturers, whether such actions are needed or not. With machine learning, it is possible to develop an algorithm using past evaluations made by engineers. Recent studies show that highly accurate results ...

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Analyse of marine diesel engine performance

Roman Varbanets

Journal of Polish CIMAC, 2012

Ships safety and economic efficiency depends on the main and auxiliary diesel engines technical condition and technical operation. The probability of failure and a sudden stop of diesel at sea would be minimized if the routine monitoring of parameters is done and found defects removed on time. The purpose of this control is the even distribution of load between the cylinders under the condition of fuel equipment and main diesel systems normal state. The power plant capacity, fuel efficiency and compliance with MARPOL environmental restrictions depend on it. In this report we will discuss the survey methods of the ship’s diesels working process, which improve their efficiency. Use of such methods will enrich the information capability and modeling quality of the PC based Engine Room simulators.

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A survey on modeling, biofuels, control and supervision systems applied in internal combustion engines

Adriana Téllez

Renewable and Sustainable Energy Reviews, 2017

In this work, we present a survey on different topics related to Internal Combustion (IC) engines. The purpose of this work is to show the evolution on modeling, use of biofuels, simulation and/or implementation of different types of control laws applied to the IC engines. In the modeling section, we present a classification of the IC engines models according to their type; in this classification linear, nonlinear, and based on Neural Networks (NN) models are included. In the biofuels section, we included different works classified according to the used biofuel. In this classification, we consider pure biofuels (ethanol, methanol, hydrogen), gasoline-alcohol blends and gasoline-alcohol blend plus hydrogen as additive. In the control section, we include a classification according to the type of control, these are model-based control, observer-based control and intelligent control. Furthermore, in this section we include a review about Fault Diagnosis strategies applied to IC engines. Moreover, we present an overview of the failures provoked by corrosion effects when biofuels are used. 2. Internal combustion engines modeling At the early 70s, different characterizations of the Internal Combustion (IC) engines of 4, 6, 8 cylinders used in energy centrals

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Identification and Adaptive Neural Network Control of the Speed of Marine Diesel Engine

Co. SEP

Marine diesel engine is of characteristics of non-linear and time-varied, so it is difficult to be controlled with traditional PID controller. An adaptive controller based on back-propagation (BP) neural network and Wiener neural network was put forwarded to tune PID parameters for marine diesel engine speed control system, where Wiener neural network structure is applied to identify diesel engine nonlinear dynamic system. The weights in the Wiener neural network are adjusted with backward-propagation methods. The adaptive controller was improved via introduce relative error in target evaluation function of the BP neural network, and obtain sensitivity function of diesel engine output with respect to its input using the WNN identifier. A simulated test on a diesel engine demonstrated that the adaptive controller improved control performance over the conventional PID control.

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Automation and Electronic Control of Marine Gas Turbine Engine for Ship Revamp

Filip Niculescu

Technium, 2020

Gas turbines used in propulsion ensure increased efficiency and safety, with a very good power / weight ratio and with low maintenance and operation costs. Due to becoming out-of-date and reaching the maximum operation hours and expected lifetime, which can cause malfunctioning, older turbine engines on frigates need to be replaced with newer generation propulsion engines. The paper presents the replacement of the turbine engine on a defence frigate, focusing on the automation and electronic control solution employed for a propulsion turbine, integrating state-of-the-art techniques. The electronic system ensures control, monitoring and alarm functions, including overspeed protection. A local control panel interfacing the PLC displays the operating parameters and engine controls, also providing maintenance and calibration sequences. The proposed solution enables both the local and the remote control of the ship's gas turbine.

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Analysis of the Possibilities of Using Modern Process Working Marine Diesel Engine

Dominika Cuper Przybylska

Journal of KONES. Powertrain and Transport, 2016

Increasing public awareness of environmental protection, it has caused a lot of emphasis on the marine industry to create reciprocating diesel environmentally friendly. Conducting research on real objects in the laboratory gives us the solution to the problem. However, such studies generate large financial resources, especially for marine engines also take a lot of time. Creating a simulation on a computer allows for the limited financial resources and also speeding up work on the piston marine engine. Computer simulations allow the creation of more complex physical models, which can describe the process of operating a marine diesel engine. However, the complication models cause a problem of the future understanding of the model and the possibility of subsequent use of it, for example for control of the engine. The more it established the need to simplify complex models of engines for better understand the processes occurring in the engine. The article is a description of the Mean Value Engine Model (MVEM), which were analysed individual blocks of the model together with the modifications related to the environment in which the engine will run. Modular model allows better modifying it and adding new blocks. This model is based mainly designed for application control. Because of the simple structure easy to adjust for different types of engines. This is particularly good for use in motor drivers. It allows better matching engine operating parameters to reduce emissions of harmful substances into the environment and also achieve better efficiency of marine engine.

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Application of Soft Computing in the Field of Internal Combustion Engines: A Review

Nitin Shrivastava

Archives of Computational Methods in Engineering, 2017

gasoline, liquefied petroleum gas (LPG), compressed natural gas(CNG) and liquefied natural gas (LNG) [1]. rapid industrialization and modernization the demand for fossil fuel is increasing day by day [2].It is also assessed that the fossil fuel will get drained within 50 years creating a void between energy available and energy required [3] .The number of vehicles on the road is increasing day by day and so is the pollution due to the exhaust emission of vehicles. The major pollutants for the exhaust of an I.C. engine are carbon monoxide (CO), Nitrogen oxides (NO x), Hydro carbons (HC), smoke, particulate matter (PM) and Suphur oxides (SO x).Many researches are being conducted to reduce the exhaust emission from engines, performance improvement and also to find a suitable alternate fuel which is cheap and eco-friendly [4-6]. Performance and exhaust emission measuring experiments of an I.C. engine are complex, time consuming and costly. Mathematical modeling can be employed to prognosticate the performance and exhaust characteristics. However their accuracy is not high enough. In recent times many soft computing techniques are employed to prognosticate and optimize the performance characteristics of engine and its exhaust emission. Soft computing is a problem solving technique, which uses approximate model to give solution to complex problems. The term soft computing was introduced with the objective of exploiting the tolerance of imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost and better rapport with reality. Ultimate aim is to emulate the human mind as closely as possible. It became a formal area of study in computer science in early 1990s. Apart from prognosticating the performance parameters and exhaust emission of the I.C. engines these soft computing techniques are also used to diagnose engine Abstract It is well known that fossil fuels are depleting day by day, and with the increase in the number of vehicles the pollution has reached at an alarming stage. The need of the hour is to find an alternate fuel as well as to demote the exhaust emission and enhance the performance parameters of the internal combustion (I.C.) engine. Researches on I.C. engines are being conducted in order to come to a feasible solution. Since performing experiments on an I.C. engine is both time consuming and costly therefore many soft computing techniques are being adopted in this field. The term soft computing refers to find the solution of an inexact problem. Different soft computing techniques being used in this field are Artificial Neural Network, Fuzzy Based Approach, Adaptive Neuro Fuzzy Inference System, Gene Expression Programming, Genetic Algorithm and Particle Swarm Optimization. The motive of this work is to review the researches being carried out in the field of I.C. engine on different types of engines with various alternative fuels using these soft computing techniques.

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Improvement of Intelligent Internal Combustion Engines (2025)
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