Published February 2019 | Version v1
Journal article

Multiple response optimizations to improve performance and reduce emissions of Argemone Mexicana biodiesel-diesel blends in a VCR engine

  • 1. Faculty, Mechanical Engineering Department, C.V. Raman College of Engineering, Bhubaneswar 752054 (India)
  • 2. Faculty, School of Mechanical Engineering, KIIT University, Bhubaneswar 752024 (India)
  • 3. Faculty, Department of Mathematics, C.V. Raman College of Engineering, Bhubaneswar 752054 (India)

Description

Highlights: • Engine load, compression ratio and biodiesel blends were taken as input parameters. • Optimized operating parameters were found as CR18, 20% blend and 9.8 kg load. • Best possible performances were obtained with composites desirability of 0.97. • Optimized performance characteristics are BTE 26.77%, BSFC 0.284 kg/kW h. • Optimized emission characteristics are CO 0.0059%, HC 114.84 ppm, NOx 905.6 ppm. -- Abstract: The characteristics of multi-fuel VCR engine fuelled with Argemone Mexicana methyl ester, prepared by two step trans-esterification process and its diesel blends (20%, 40%, 60% and 100%) were evaluated with variation of load (3–12 kg) and compression ratio (16–18). In the current analysis engine load, compression ratio and biodiesel blends were taken as input parameters. Response Surface Methodology of Full Factorial Design was used for modelling and analyzing the response parameters with Minitab-14.0 software. Data regression, significance analysis and individual model coefficients were studied for the developed models and presented for validation of the model. Multi objective optimization was carried out for the responses by using the desirability function. Confirmation experiments were executed for validation of optimization results by setting input parameters (Load = 9.8 kg, CR = 18.0, Blend = 20%). Output responses from the mathematical modeling such as BTE 26.77%, BSFC 0.284 kg/kW h, CO 0.0059%, HC 114.84 ppm, NOx 905.6 ppm respectively were obtained using D-optimal test with composites desirability of 0.97009. The predictions of RSM results were obtained in concurrence with the experimental ones, with errors less than 5% excepting for CO model.

Additional details

Identifiers

DOI
10.1016/j.applthermaleng.2018.11.061;
PII
S1359431118348002;

Publishing Information

Journal Title
Applied Thermal Engineering
Journal Volume
148
Journal Page Range
p. 1454-1466
ISSN
1359-4311
CODEN
ATENFT

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Copyright
Copyright (c) 2018 Elsevier Ltd. All rights reserved.