Comparative performance and emissions assessments of a single-cylinder diesel engine using artificial neural network and thermodynamic simulation

Castresana, Joseba; Gabiña, Gorka; Martín, Leopoldo; Uriondo, Zigor

doi:10.1016/j.applthermaleng.2020.116343

Cited by 34 publications

(16 citation statements)

References 45 publications

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“…The advantage of such a solution is the ability to define any area. Based on the analysis of the literature [20], the optimal combination of networks should be structure 5-5-5. During the research, it turned out that the proposed combination is not optimal due to an error during the calculation, which ranged from 0.7564 to 2.5320 and the difference is 1.7756.…”

Section: Resultsmentioning

confidence: 99%

“…The results of the analysis showed a high degree of alignment of the algorithm with the values obtained during the measurements. There is a possibility to implement a neural network to estimate the emission of toxic substances by an engine powered by a vegetable fuel [18][19][20]. The authors achieved agreement of over 95% with the measurement results.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Comparing Polynomials and Neural Network to Modelling Injection Dosages in Modern CI Engines

Osipowicz¹,

Abramek²,

Mozga³

2022

Applied Sciences

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The article discusses the possibility of using computational methods for modelling the size of the injection doses. Polynomial and artificial intelligence methods were used for prediction. The aim of the research was to analyze whether it is possible to model the operating parameters of the fuel injector without knowing its internal dimensions and tribological associations. The black box method was used to make the model. This method is based on the analysis of input and output parameters and their correlation. The paper proposes a mathematical model determined on the basis of a polynomial and a neural network based on input and output parameters. The above models make it possible to predict the amount of fuel injection doses on the basis of their operating parameters. Modelling was performed in the Matlab environment. Calculating methods could support the diagnosis processes of fuel injectors. Fuel injection characteristic is non-linear. Study shows that it is possible to predict injection characteristic with high matching using polynomial and neural network. That way accelerates fuel injector work parameters research process. Fuel injector test basis on known its work areas. Mathematical modelling can calculate all injection area using few parameters. To modelling fuel injection dosages by neural network have been used back propagation and Levenberg—Marquardt algorithms.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparing Polynomials and Neural Network to Modelling Injection Dosages in Modern CI Engines

Osipowicz¹,

Abramek²,

Mozga³

2022

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Therefore, the engine can be repaired and maintained in time. At present, thermodynamic modeling [13] is a commonly used prediction method, but it has the disadvantages of slow speed, inability to adapt to high-load engines, and long time-consuming. But using artificial neural network methods to make predictions can solve these problems well.…”

Section: Heat Engines Combined With Artificial Intelligencementioning

confidence: 99%

Analysis of the social impact of heat engine and its future application

Yang

Guo

2022

IOP Conf. Ser.: Earth Environ. Sci.

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This paper aims to evaluate the social impact of the heat engine and analyze the application of heat engines in the future. This paper starts with some background information on heat engines and the challenges of gas pollution and gas shortage. The concepts of efficiency and environmental friendliness of the heat engine are widely discussed, which speeds up the development of several kinds of heat engines. We discuss the application of heat engines in different industries from three main aspects: agriculture, marine engine, and aviation. They improve our daily life and provide the required energy to the community. Thermoacoustic Heat Engine (TAHE), Liquid Air Cycle Engines (LACE), and a new class of Heat engine without the expulsion of reaction mass are introduced in this paper. Furthermore, the article will cover some futures. One is artificial intelligence, and another one is about biofuel, which helps heat engines to have higher efficiency and less pollution, and also how heat engines are involved in the next decade.

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“…This method is time-consuming and labor-intensive, it is impossible to create models for all operating points, and it is difficult to obtain the optimal solution for the entire domain. Therefore, the combination of thermodynamic simulation calculations through intelligent optimization methods has become an effective technical approach [16][17][18][19]. Among them, the genetic algorithm (GA) has been widely used in engine operating condition optimization and external geometry optimization due to its randomness and ability to avoid becoming trapped in local minima [20,21].…”

Section: Introductionmentioning

confidence: 99%

Using a Genetic Algorithm to Achieve Optimal Matching between PMEP and Diameter of Intake and Exhaust Throat of a High-Boost-Ratio Engine

Yang

Cheng

et al. 2022

Energies

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With the increasingly stringent CO2 emission regulations, the degree of strengthening of the engines is increasing. Under high-pressure conditions, the airway throat parts of the intake and exhaust systems have a great influence on the flow loss of the diesel engine. The reasonable distribution of the throat area of the intake and exhaust ports in the limited cylinder headspace is key to improving the performance of supercharged engines. This study took a large-bore, high-pressure ratio diesel engine as the research object. Firstly, the three-dimensional (3D) flow simulation method was used to reveal the influence law of different throat areas on the engine intake and exhaust flow under steady-state conditions, and a steady-flow test bench was built to verify the accuracy of the simulation model and law. Secondly, based on the 3D steady-state calculation and test results, a more accurate one-dimensional simulation model was constructed, and a joint optimization simulation platform was established based on the dynamic data link library. On this basis, the mathematical description of the multi-objective optimization of airway throat size was established using machine learning methods, such as a genetic algorithm, the design domain and boundary conditions of variable parameters were clarified, and the collaborative optimization objective of integrated flow coefficient and flow loss is proposed to achieve the fast and accurate optimization of intake and exhaust throat diameters.

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Comparative performance and emissions assessments of a single-cylinder diesel engine using artificial neural network and thermodynamic simulation

Cited by 34 publications

References 45 publications

Comparing Polynomials and Neural Network to Modelling Injection Dosages in Modern CI Engines

Comparing Polynomials and Neural Network to Modelling Injection Dosages in Modern CI Engines

Analysis of the social impact of heat engine and its future application

Using a Genetic Algorithm to Achieve Optimal Matching between PMEP and Diameter of Intake and Exhaust Throat of a High-Boost-Ratio Engine

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