Clean gaseous fuel application in diesel engine: A sustainable option for rural electrification in India

Das, Sutapa; Kashyap, Dhrubajyoti; Kalita, Pankaj; Kulkarni, Vinayak; Itaya, Yoshinori

doi:10.1016/j.rser.2019.109485

Cited by 58 publications

(22 citation statements)

References 118 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The petroleum diesel combustion has the least NO x emission. Similar results are reported in the literature 37,38 …”

Section: Resultssupporting

confidence: 92%

Artificial intelligence‐based model prediction of biodiesel‐fueled engine performance and emission characteristics: A comparative evaluation of gene expression programming and artificial neural network

Sharma¹

2021

Heat Trans

View full text Add to dashboard Cite

The prognostic capability of gene expression programming (GEP) and artificial neural network (ANN) are compared to estimate the engine performance and emission characteristics. A stationary diesel engine was powered with linseed oil biodiesel‐mineral diesel blends. A total of 60 lab‐based test‐run were conducted by varying the engine input operating conditions, namely fuel injection parameters, diesel/biodiesel blending ratio, and engine load. The engine output data, namely brake thermal efficiency and brake‐specific fuel consumption, were calculated, while emission data for oxides of nitrogen, carbon monoxide, and unburnt hydrocarbon, were recorded. The experimental data were used for predictive model development using artificial intelligence‐based GEP and ANN techniques. The developed models were tested on statistical outcomes, such as the absolute fraction of variance (0.9698–0.997 for GEP and 0.9949–0.9998 for ANN), correlation coefficient (0.9848–0.998 for GEP and 0.9974–0.9998 for ANN), establishing these two models as an efficient machine identical tool. Also, Nash–Sutcliffe efficiency (0.937–0.9999 for GEP and 0.995–0.999 for ANN) and Kling–Gupta efficiency (0.834–0.9999 for GEP and 0.989–0.999 for ANN) elevate the prediction quality of developed models. The result showed that the ANN model was slightly more accurate than the GEP‐based model for the same parametric range.

show abstract

“…The petroleum diesel combustion has the least NO x emission. Similar results are reported in the literature 37,38 …”

Section: Resultssupporting

confidence: 92%

Artificial intelligence‐based model prediction of biodiesel‐fueled engine performance and emission characteristics: A comparative evaluation of gene expression programming and artificial neural network

Sharma¹

2021

Heat Trans

View full text Add to dashboard Cite

show abstract

“…Thus, laws of a circular economy offer using biogas resources not only for heat [10] and electricity production, but also in transportation as an alternative to fossil fuels [11]. Using biogas as a fuel for internal combustion engines allows one to also use it in vehicles and stationary cogeneration power plants, which use a diesel generator to produce electricity [12]. However, even though supported by respective regulations and directives, the transport sector does not use biogas resources that quickly.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study on the Energetic and Ecologic Parameters of Dual Fuels (Diesel–NG and HVO–Biogas) and Conventional Diesel Fuel in a CI Engine

2020

View full text Add to dashboard Cite

The Article presents the results of the experimental research and numerical analysis of a compression ignition (CI) engine adapted for running on dual fuels of different composition (diesel and natural gas, diesel and biogas, biodiesel and natural gas, and biodiesel and biogas). The main goal was to find out the impact of different dual fuels on energy performance and emissions depending on the start of injection (SOI) of diesel and the crank angle degree (CAD). Pure conventional diesel fuel and second generation hydrotreated vegetable oil (HVO) (Neste) was used in the research. Natural gas contained 97 vol. % of methane. Biogas (biomethane) was simulated using a methane and carbon dioxide blend consisting of 60 vol. % of methane and 40 vol. % of carbon dioxide. Dual (liquid and gaseous) fuels were used in the tests, with the energy share of liquid fuels accounting for 40% and gas for 60%. The research results have shown that having replaced conventional diesel fuel with dual fuel, engine’s BTE declined by 11.9–16.5%. The use of methane in the dual fuel blend reduced CO2 volumetric fraction in the exhaust gases by 17–20%, while biomethane increased CO2 volumetric fraction by 10–14%. Dual fuel significantly increased CO and HC emissions, but NOx volumetric fraction decreased by 67–82% and smoke by 23–39%. The numerical analysis of the combustion process revealed changes in the ROHR (Rate of Heat Release) that affected engine efficiency and exhaust emissions was done by AVL (Anstalt für Verbrennungskraftmaschinen List) BOOST program.

show abstract

“…On the other hand, the second-order approximation is utilized for approximating two-variable functions that include the inactivity of two independent components. It may be stated as per Equation (3).…”

Section: Design Of Experiments and Data Collectionmentioning

confidence: 99%

“…Diesel engines are widely utilized in off-grid energy production, agriculture, industrial, land transportation, and maritime transportation. It is recommended due to its reliability, low initial cost, simple maintenance, and higher energy conversion efficiency [3]. Their exhaust, on the other hand, comprises hazardous greenhouse gases (GHGs).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Exploring the Exhaust Emission and Efficiency of Algal Biodiesel Powered Compression Ignition Engine: Application of Box–Behnken and Desirability Based Multi-Objective Response Surface Methodology

Sharma¹,

Chhillar²,

Said

et al. 2021

Energies

View full text Add to dashboard Cite

Sustainable Development Goals were established by the United Nations General Assembly to ensure that everyone has access to clean, affordable, and sustainable energy. Third-generation biodiesel derived from algae sources can be a feasible option in tackling climate change caused by fossil fuels as it has no impact on the human food supply chain. In this paper, the combustion and emission characteristics of Azolla Pinnata oil biodiesel-diesel blends are investigated. The multi-objective response surface methodology (MORSM) with Box–Behnken design is employed to decrease the number of trials to conserve finite resources in terms of human labor, time, and cost. MORSM was used in this study to investigate the interaction, model prediction, and optimization of the operating parameters of algae biodiesel-powered diesel engines to obtain the best performance with the least emission. For engine output prediction, a prognostic model is developed. Engine operating parameters are optimized using the desirability technique, with the best efficiency and lowest emission as the criteria. The results show Theil’s uncertainty for the model’s predictive capability (Theil’s U2) to be between 0.0449 and 0.1804. The Nash–Sutcliffe efficiency is validated to be excellent between 0.965 and 0.9988, whilst the mean absolute percentage deviation is less than 4.4%. The optimized engine operating conditions achieved are 81.2% of engine load, 17.5 of compression ratio, and 10% of biodiesel blending ratio. The proposed MORSM-based technique’s dependability and robustness validate the experimental methods.

show abstract

Clean gaseous fuel application in diesel engine: A sustainable option for rural electrification in India

Cited by 58 publications

References 118 publications

Artificial intelligence‐based model prediction of biodiesel‐fueled engine performance and emission characteristics: A comparative evaluation of gene expression programming and artificial neural network

Artificial intelligence‐based model prediction of biodiesel‐fueled engine performance and emission characteristics: A comparative evaluation of gene expression programming and artificial neural network

Comparative Study on the Energetic and Ecologic Parameters of Dual Fuels (Diesel–NG and HVO–Biogas) and Conventional Diesel Fuel in a CI Engine

Exploring the Exhaust Emission and Efficiency of Algal Biodiesel Powered Compression Ignition Engine: Application of Box–Behnken and Desirability Based Multi-Objective Response Surface Methodology

Contact Info

Product

Resources

About