An experimental-based artificial neural network performance study of common rail direct injection engine run on plastic pyrolysis oil

Khandal, S. V.; Gadwal, Sudershan B.; Raikar, Venkatesh A.; Badruddin, Irfan Anjum

doi:10.1080/19397038.2020.1773568

Cited by 8 publications

(2 citation statements)

References 39 publications

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“…High levels of accuracy were achieved in successfully obtaining the forecast values. It explains how the engine output parameters are predicted and validated using ANN (Khandal 2021). In addition to this, a thermo-economic analysis has also been made to address the signi cance of waste plastic oil as a cost-effective alternative fuel to diesel without any modi cation in engine operation.…”

Section: Introductionmentioning

confidence: 99%

Optimization of diesel engine performance and emission using waste plastic pyrolytic oil by ANN and its thermo-economic assessment

Panda

Rout²,

Das

2023

Environ Sci Pollut Res

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The current study focuses on the engine performance and emission analysis of a 4 stroke compression ignition engine powered by medical waste plastic oil (WPO) followed by their optimization study and economic analysis. Engine tests were conducted using WPO blended diesel at various proportions to acquire required data for training the ANN model, which enables better prediction for the engine performance by making use of the standard back-propagation algorithm.Considering supervised data obtained from repeated engine tests, an arti cial intelligence-based model of ANN was designed to select different parameters of performance and emission as output layers, at the same time engine loading and different blending ratio of the test fuels were taken as the input layers. The ANN model was built up making use of 80% of testing outcomes for training. The ANN model forecasted engine performance and exhaust emission with regression coe cients (R) at 0.989-0.998 intervals and a mean relative error from 0.002% to 0.348%. Such results illustrated the effectiveness of the ANN model for estimating emissions and the performance of diesel engines. This study demonstrates the use of arti cial neural networks (ANNs) to forecast a multi-component fuel mixture, which is novel and reduces the amount of experimental effort required to determine the engine output characteristics. Moreover, the economic viability of the use of 20WPO as an alternative to diesel was justi ed by thermo-economic analysis.The Important Highlights Of The Work Are 1. Study of performance and emission diesel engine fuelled with WPO blended diesel. 2. Development of an arti cial intelligence-based ANN model at speci c engine conditions. 3. Analysis of productivity of ANN model developer for this experiment and test the economic feasibility.

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Section: Introductionmentioning

confidence: 99%

Optimization of diesel engine performance and emission using waste plastic pyrolytic oil by ANN and its thermo-economic assessment

Panda

Rout²,

Das

2023

Environ Sci Pollut Res

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“…Different approaches have been reported on utilization of TPO in diesel engine like blending TPO with diesel (Frigo et al, 2014, Martínez et al, 2014Aydın et al, 2015& Seljak et al, 2015 or biodiesel (Sharma et al, 2015 (a); Sharma et al, 2015(b)), increasing the intake temperature of air (McNeil et al, 2012), increasing compression ratio (Van de Beld et al, 2013),varying injection timing and pressure (Sudershan et al, 2018a), artificial neural network (ANN) modeling (Khandal et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Performance and Emission analysis of Multi-Cylinder Common Rail Direct Injection Diesel Engine Powered with Blends of Tyre Pyrolysis Oil-Ethanol-Diesel

Khandal¹,

Badruddin²,

Kamangar³

et al. 2021

JER is an international, peer-reviewed journal that publishes f

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This paper mainly focuses on optimal replacement of diesel by Tyre Pyrolysis oil-Ethanol blends to run a common rail direct injection (CRDI) multi cylinder engine and to compare the results with neat diesel fuel operation results at 1500 rpm. The engine was operated at different loads and speeds. From the experimental study, decrease in brake thermal efficiency (BTE) and oxides of nitrogen (NOx) emission with increase in carbon monoxide (CO), hydrocarbon (HC), and smoke emission was observed for blends as compared to diesel fuel. Further, it was also observed that increase in speed from 1200 rpm to 1800 rpm yielded higher BTE with decrease in CO, HC and smoke emission. But slightly increase in NOx, peak pressure (PP) and heat release rate (HRR) was reported at higher speed as compared to lower speeds. Beyond engine speed of 1800 rpm, knocking was observed.

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Characterization of SPW pyrolysis oils: Products spectra and opportunities

Perez

Jonnalagedda

Toraman

2022

Advances in Chemical Engineering

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An experimental-based artificial neural network performance study of common rail direct injection engine run on plastic pyrolysis oil

Cited by 8 publications

References 39 publications

Optimization of diesel engine performance and emission using waste plastic pyrolytic oil by ANN and its thermo-economic assessment

Optimization of diesel engine performance and emission using waste plastic pyrolytic oil by ANN and its thermo-economic assessment

Performance and Emission analysis of Multi-Cylinder Common Rail Direct Injection Diesel Engine Powered with Blends of Tyre Pyrolysis Oil-Ethanol-Diesel

Characterization of SPW pyrolysis oils: Products spectra and opportunities

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