Adding ZnO Nanoparticle in Mahua Oil Methyl Ester (MoME) Biodiesel for Eco-Friendly and Better Performance in DI Engine

Kumar, D. Anantha; Chhibber, Vijay K.; Singh, Ajay

doi:10.1007/s40009-021-01090-7

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…The NSGA II sorting algorithm has been considered for overcoming the limitation of elitism and sharing parameter which is superior to the NSGA. The best solution has been obtained using NSGA-II code under the MATLAB environment with different functions required to run the computer software [15][16][17][18][19].…”

Section: Multi-objective Optimization Using Nsga-iimentioning

confidence: 99%

“…For estimating the fluctuation of BSFC, BTE, and emission parameters (CO, NOx, HC, etc) with load, speed, blending ratios, and injection time, performance examination of various biodiesels from non-edible and edible sources of oils was carried out by many researchers [8][9][10][11][12][13][14][15][16]. The best sets of solutions have been predicted using multi-objective optimization approaches such as MOGA (Multi-objective genetic algorithm), NSGA (Nondominated sorting genetic algorithm), PSO, Desirability approach, etc [17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

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Multi-objective parameter optimization for four-stroke single-cylinder diesel engine with soyabean oil blends using NSGA-II

Kumar,

Kumar Dhingra,

Chhabra

et al. 2023

Eng. Res. Express

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Due to the continuous scarcity of petroleum and related products, there is a greater need for alternative product to petroleum derivatives. The current work investigates the factors influencing the output characteristics of a single-cylinder four-stroke compression ignition engine by utilizing different combinations of blends of soybean biodiesel and fossil diesel, by weight/weight. The experiments have been conducted using the Response Surface Method based on full factorial CCRD and NSGA-II. Mathematical models for BSFC (brake-specific fuel consumption), BTE (brake thermal efficiency), and emission (CO, NOx, and unburned HC) have been proposed using regression equations for optimizing the combustion characteristics (brake-specific fuel consumption), performance characteristics (brake thermal efficiency), and emission parameters (CO, NOx, HC) in NSGA II. A multi-objective optimization problem is created since this investigation aims to minimize BSFC, CO, NOx, and HC and maximize BTE. This research evaluated five optimum combinations of BSFC, BTE, NOx, CO, and HC at variable input factors’ blending ratio and load, and their conformity was checked. It is observed that at a blending ratio of 25.03, the engine performance and emission give better results. At a blending ratio of 25.03 % w/w and load 2.08 kW, the brake thermal efficiency is 24.96%, and emission parameters are NOx 52.56 ppm, CO 0.08 %, and hydrocarbon 18.11 ppm.

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