An investigation of performance and emission of diesel engine by using quaternary blends of neem biodiesel–neem oil–decanol–diesel

Khan, Md Modassir; Kadian, Arun Kumar; Sharma, Rishi

doi:10.1007/s12046-023-02084-5

Cited by 4 publications

(3 citation statements)

References 40 publications

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“…The results indicate that BTE increases with an increase in the load of the diesel engine. It is due to the improved combustion and decreased friction losses at higher loads [ 76 ]. The BTE of biodiesel blends is higher compared with D100, and there is a trend that the higher the proportion of biodiesel in the blend, the higher the BTE.…”

Section: Resultsmentioning

confidence: 99%

Utilization of renewable biodiesel blends with different proportions for the improvements of performance and emission characteristics of a diesel engine

Chen,

Zhang,

Zhang

et al. 2023

Heliyon

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Section: Resultsmentioning

confidence: 99%

Utilization of renewable biodiesel blends with different proportions for the improvements of performance and emission characteristics of a diesel engine

Chen,

Zhang,

Zhang

et al. 2023

Heliyon

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“…The research on quaternary blend of neem biodiesel, pure neem oil, decanal and diesel indicated enhanced engine lubricity, higher BTE and marginal loss in BP. The smoke and CO missions were also less because of better combustion of the quaternary blends [15]. CaO derived from ostrich eggshell for synthesis of biodiesel production in ultrasonic system increased biodiesel yield by 93%.…”

Section: Introductionmentioning

confidence: 99%

“…15, 7415 12 of 20 cumulative influence of the blended fuel samples' lower energy content and highest viscosity relative to diesel[42].…”

mentioning

confidence: 99%

Performance, Emission, and Spectroscopic Analysis of Diesel Engine Fuelled with Ternary Biofuel Blends

et al. 2023

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The demand for sustainable alternative-fuels in the transportation and agriculture domains is essential due to the quick depletion of petroleum supplies and the growing environmental challenges. The ternary-blends (diesel, biodiesel, and Methyl oleate) have the ability to report the existing challenges in this area because they offer significant promise for reducing exhaust emissions and improving engine performance. In the current work, soy methyl ester is blended with methyl oleate and diesel. The emissions and performance of blended biodiesel was conducted in common rail direct injection engine (CRDI). The characterization and physical properties were also evaluated by utilizing various methods like Fourier-Transform Infrared Spectroscopy (FTIR), UV-vis Spectroscopy (UV-vis), and Nuclear Magnetic Resonance. FTIR spectra showed the existence of the strong C=O, indicating the presence of FAME at 1745 cm−1. Again, UV-vis has reported the appearance of conjugated dienes in the oxidized biodiesel. The results indicated all blended samples retained the properties of diesel. The addition of methyl oleate improved brake specific fuel consumption of blended biodiesel almost near to diesel. D50::S80:M20 produced a mean reduction in hydrocarbon 42.64% compared to diesel. The average carbon monoxide emission reduction for D50::S80:M20 was 49.36% as against diesel.

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Optimising novel methanol/diesel blends as sustainable fuel alternatives: Performance evaluation and predictive modelling

Deka,

Abd Elaziz,

Osman

et al. 2024

Energy Conversion and Management

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An investigation of performance and emission of diesel engine by using quaternary blends of neem biodiesel–neem oil–decanol–diesel

Cited by 4 publications

References 40 publications

Utilization of renewable biodiesel blends with different proportions for the improvements of performance and emission characteristics of a diesel engine

Utilization of renewable biodiesel blends with different proportions for the improvements of performance and emission characteristics of a diesel engine

Performance, Emission, and Spectroscopic Analysis of Diesel Engine Fuelled with Ternary Biofuel Blends

Optimising novel methanol/diesel blends as sustainable fuel alternatives: Performance evaluation and predictive modelling

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