Effect of fuel injection pressure and EGR techniques on various engine performance and emission characteristics on a CRDI diesel engine when run with linseed oil methyl ester

Manish Kumar, Varun Kumar Singh, Abhishek Sharma, Naushad Ahmad Ansari, Raghvendra Gautam and Yashvir Singh

Energy & Environment, 2022, vol. 33, issue 1, 41-63

Abstract: Nowadays, owing to the reduction in petroleum supplies due to the growing oil demand, the search for alternate fuels has intensified. However, as alternate fuel choice grows, checking whether alternative fuels are suitable for use in engines has become time-consuming and expensive. Therefore, the usage of Linseed oil methyl ester (linseed biodiesel) in the common rail direct injection (CRDI) diesel engine was optimized for a smaller number of trials in this research. Response surface methodology (RSM) was employed for optimization. Input variables were chosen for LOME content in the blend, fuel injection pressure (FIP), exhaust gas recirculation (EGR) rates, and engine load while output parameters were selected for like indicated power (IP), indicated thermal efficiency (η(I)), indicated mean effective pressure (IMEP), hydrocarbon (HC), and NOx (Oxide of Nitrogen).The model layout employed in the analysis is focused on the matrix of the CCRD (central composite rotating design). The optimal input variables configuration is estimated at 5.45% LOME blend, 57.77 MPa FIP, 6.50% EGR, and 6.909 kg engine load leading to better efficiency together with reduced emissions. The optimized output of the engine at this input configurations are as IP 4.878 kW, IMEP 0.5886 MPa, indicated thermal efficiency 48.36%, HC 23.43 ppm vol., and NOx 533.15 ppm vol. Testing and optimum output response results are measured at acceptable input parameters and are considered to be within an acceptable error range. The findings of this analysis have shown that RSM is an appropriate technique for optimizing CRDI diesel engines.

Keywords: Linseed biodiesel; performance; emission; common rail direct injection; response surface methodology (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:sae:engenv:v:33:y:2022:i:1:p:41-63

DOI: 10.1177/0958305X20983477

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