Optimization of Engine Operating Parameters for Turpentine Mixed Diesel Fueled DI Diesel Engine Using Taguchi Method

Over a significant period of time, efforts have been made towards a valid and accurate estimation of DI diesel engine NOx emissions. Considering the fact that experiments have a high cost in both time and money, modelling approaches have been developed in an effort to overcome these issues. It is well known that accuracy in the prediction of NOx emissions lies specifically on the accurate estimation of local temperature and O2 histories inside the combustion chamber that govern NOx formation, fulfilled by an accurate estimation of the combustion mechanism. To account for the actual effect of parameters that control NOx formation and overcome inefficiencies introduced from existing purely empirical models or artificial neural networks, valid only on the combustion systems for which they were developed [1], an alternative solution is the introduction of physically based semi-empirical models. Towards this direction, in the present work is presented and evaluated a new modelling approach, based on the combustion rate obtained from the measured cylinder pressure trace using Heat Release Rate Analysis. The model used is a semi-empirical two-zone one which makes use of the estimated elementary fuel mass burnt at each crank angle interval. The combustion process is considered to be adiabatic, while chemical dissociation is also considered. With this approach, temperature distribution throughout the combustion chamber is considered for, together with its evolution during the engine cycle. In addition, O2 availability is also considered for through the calculated charge composition. The result is an extremely fast computational model, combining the advantages of both empirical and physically based ones. In the present work is given a detailed validation of the model, from its application on two different types of diesel engines: a heavy-duty DI diesel engine and a light-duty DI diesel engine with pilot fuel injection. A significant number of cases where tested for both engine configurations, considering different operation points and variation of operating parameters, such as rail pressure and EGR. The twelve points of the European Stationary Cycle (ESC) were covered for the case of the heavy duty DI diesel engine, whilst for the light-duty DI engine a total number of forty-six operating points was studied. For both engine configurations the model reveals a very good predictive ability, considering for the effect of all operating parameters examined on NOx emissions. However, there is potential for improvement and development on its physical base for even more accurate predictions. The merits of good accuracy in prediction trends with varying engine operating parameters — even without calibration — and low computational time establish a potential for model use in engine development, optimization studies and model based control applications.

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The effect of operating parameters on performance and emissions of DI diesel engine fuelled with Jatropha biodiesel

Fuel ◽

10.1016/j.fuel.2020.118256 ◽

2020 ◽

Vol 278 ◽

pp. 118256

Author(s):

Vineet Kumar ◽

Rajesh Kumar Saluja

Keyword(s):

Diesel Engine ◽

Operating Parameters ◽

Performance And Emissions ◽

Di Diesel Engine

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Humidification Effect on the Performance and Emissions of (DI) Diesel Engine Running on Diesel Fuel with Biodiesel Blended Nano Additives

Engineering and Technology Journal ◽

10.30684/etj.v39i5a.1935 ◽

2021 ◽

Vol 39 (5A) ◽

pp. 790-803

Author(s):

Hussein Jumaa ◽

Mahmoud A. Mashkour

Keyword(s):

Diesel Engine ◽

Taguchi Method ◽

Diesel Fuel ◽

Direct Injection ◽

Waste Cooking Oil ◽

Compression Ignition Engine ◽

Performance And Emissions ◽

Di Diesel Engine ◽

Nano Additives ◽

20 Nm

The effect of humidification of the air on the performance of a compression ignition engine operating on diesel, biodiesel with nano additives was investigated. The experiment was carried out on a single-cylinder, four-stroke, naturally aspirated water-cooled, direct injection Ricardo (E6/US) diesel engine at a constant speed of 1800 rpm, and varying loads. A mixture of Biodiesel (waste cooking oil) and diesel fuel by four ratios (B5, B10, B15, and B20) was used in the experiment. Besides, five concentrations of Iron oxide nanoparticles (Fe2O3, with particle size 20 nm) as fuel-additives were prepared (10 ppm, 30 ppm, 50 ppm, 70 ppm, and 100 ppm), and added to the test fuels (Bio-Diesel). Taguchi Method by DOE was used for the optimization in this investigation. The results of Taguchi Method experiments identified the biodiesel (B20), nano additive (100 ppm), relative humidity (65%). The experimental results manifested that BTE improved by 17.62% and BSFC decreased by 12.72%, while NOx and PM reduced by 8.45%, 24.17%, respectively.

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