Investigations of diesel engine in the road test

Grytsyuk, Oleksandr; Vrublevskyi, Oleksandr

doi:10.29354/diag/90279

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…As a result of working out the presented methodological sequence, new original results had been obtained, containing a new concept to ensure the required power for an aircraft engine, using the supercharging as a decisive parameter and the maximum combustion pressure and energy costs for air compression. Tests results with the prototype engine HADI-100A [25] under normal atmospheric conditions (altitude above the sea level h = 0 m) showed: engine effective power Ne = 103 kW with excess air ratio λ(0) = 1.65 and pressurization ps= 273300 Pa.…”

Section: Starting Positions and Backgrounds For Analytical Calculationsmentioning

confidence: 99%

Study of super/turbocharger system for helicopter diesel engine

Прохоренко¹,

Vrublevskyi²,

Grytsyuk³

et al. 2021

Diagnostyka

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The article demonstrates a rational scheme of the supercharging system in a helicopter diesel engine with a power of 100 kW, regardless of the flight altitude, and proposes a method for assessing the power losses for a diesel engine depending on the flight altitude using a mathematical model. There are three variants of an engine supercharger scheme with a single-stage turbocharger, a two-stage one with parallel or sequential compressor drive and a turbo-blower. As a result of the computational analysis according to the original method, it was shown that from the point of view of the least energy consumption two-stage scheme with a compressor and a sequential drive is the most rational. To reduce energy losses in the drive with two-stage supercharging, a concept for controlling the pressure system was proposed, which includes changing the rotational speed of the compressor drive and adjusting the throttles. Simulation of the engines running during the climb / descent of the helicopter showed that the proposed pressure scheme and control concept is effective. In order to improve the quality of regulation, the possibility to use an electric drive with the first stage compressor is being considered.

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Section: Starting Positions and Backgrounds For Analytical Calculationsmentioning

confidence: 99%

Study of super/turbocharger system for helicopter diesel engine

Прохоренко¹,

Vrublevskyi²,

Grytsyuk³

et al. 2021

Diagnostyka

Self Cite

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“…They combine the advantages of different models to reduce computation time, increase accuracy and facilitate calibration. In diesel engines fuel consumption can be calculated using the method based on processing the pressure data from inside the cylinder [7]. Fuel consumption models can be implemented into microscopic traffic simulation software, which allows the evaluation of the environmental impact of transportation management strategies [22].…”

Section: Modeling Of Fuel Consumptionmentioning

confidence: 99%

Modeling of fuel consumption using artificial neural networks

Witaszek¹

2020

Diagnostyka

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The article presents a model of operational fuel consumption by a passenger car from the B segment, powered by a spark ignition engine. The model was developed using artificial neural networks simulated in the Stuttgart Neural Network Simulator (SNNS) package. The data for the model was obtained from longterm operational tests, during which data from the engine control unit were recorded via the OBDII diagnostic interface. The model is based on neural networks with two hidden layers, the size of which was selected using an original iterative algorithm. During the structure selection process, a total of 576 different networks were tested. The analysis of the obtained test errors made it possible to select the optimal structure of the 6-19-17-1 model. The network input values were: vehicle speed and acceleration, road slope, throttle opening degree, selected gear number and engine speed. The networks were trained using the efficient RPROP method. A correctly trained network, based on the set parameters, was able to forecast the instantaneous fuel consumption. These forecasts showed a high correlation with the measured values. Average fuel consumption calculated on their basis was close to the real value, which was calculated on the basis of two consecutive fuelings of the vehicle.

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“…The phenomena accompanying the running-in period prevent the unequivocal identification of wear as well as technological and construction factors affecting its nature during operation. The tests of friction pairs under operating conditions were carried out in a 4DTNA1 [18] engine mounted in a light-duty truck (LDV). Wear products in oil result from the processes taking place in the following friction pairs -cylinder-piston system, crankshaft, camshaft, auxiliary mechanisms (Fig.…”

Section: Aim and Scope Of The Workmentioning

confidence: 99%

Method of Accelerated Testing of Crankshaft Shells of the Combustion Engine in the Operating Process

Grytsyuk¹,

Vrublevskyi²

2019

Tribol. Ind.

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This article discusses the method and results of accelerated tests of crankshaft bearings of the compression ignition engine, carried out to determine the possibility of modernising the basic engine model and improving the methods of friction joint diagnostics. The essence of the method consists in changing the operating conditions of the crankshaft bearings of one of the engine cylinders. This increases the bearing load and causes changes in the engine oil temperature. The bearing condition was monitored non-invasively by determining the share of wear products in the oil samples. The results obtained from the tests have shown that on the basis of oil analysis for the presence of wear products, the cause of engine failure related to the acceptable wear of engine friction pairs can be clearly identified and located.

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Investigations of diesel engine in the road test

Cited by 5 publications

References 10 publications

Study of super/turbocharger system for helicopter diesel engine

Study of super/turbocharger system for helicopter diesel engine

Modeling of fuel consumption using artificial neural networks

Method of Accelerated Testing of Crankshaft Shells of the Combustion Engine in the Operating Process

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