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Predictive Modeling and Optimization of Microalgae Chlorella vulgaris Biodiesel Production: Assessing the Performance of a Raw Biogas-Powered Diesel Engine with Diethyl Ether Blended Biodiesel

  • A. Ahmad*
  • , A. K. Yadav
  • , A. Singh
  • *Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

18 Scopus citations

Abstract

Biodiesel production has drawn significant interest due to its potential as a renewable and environmentally favorable alternative to conventional diesel fuel. This study focuses on the prediction and optimization of biodiesel synthesis from Chlorella vulgaris microalgae oil using response surface methodology (RSM) and genetic algorithm (GA). The transesterification process factors, including molar ratio, catalyst concentration, reaction temperature, reaction time, and stirring speed, are explored using a Box-Behnken Design (BBD). The GA proved to be the optimal parameter combination for achieving a high biodiesel yield. Under the optimized conditions of molar ratio of 6.77:1, catalyst concentration of 1.38 wt%, reaction temperature of 65 °C, reaction time of 90 min, and stirring speed of 574 rpm, the biodiesel yield reached 98.38% (wt%). Experimental validation confirms the accuracy of the predicted results. This study also investigates the efficient use of produced biodiesel with diethyl ether as an additive and diesel blend in a dual-fuel diesel engine mode by varying the biogas mass flow rate (6, 8, and 10 L/min). Test blends of biodiesel/diesel/diethyl ether as pilot fuel and biogas as the primary fuel demonstrate satisfactory engine performance and reduced NOx and smoke emissions compared to baseline diesel. However, carbon monoxide (CO) and hydrocarbon (HC) emissions increase. Among the tested blends, B20DEE10Bio (10) exhibited diesel-like engine performance, resulting in a 3.47% increase in brake thermal efficiency (BTE) and a 4.17% decrease in brake-specific fuel consumption (BSFC). While NOx and smoke emissions decreased by 30.78 and 54.6%, CO and HC emissions increased by 41.27 and 37.3%, respectively, compared to baseline diesel. This research contributes to the optimization of biodiesel production and its utilization in sustainable energy systems, offering a promising pathway towards reducing environmental impacts and achieving energy security.

Original languageEnglish
Pages (from-to)42-56
Number of pages15
JournalJournal of Environmental Informatics
Volume45
Issue number1
DOIs
StatePublished - Mar 2025
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2025 ISEIS All rights reserved.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • biogas
  • Chlorella vulgaris microalgae biodiesel
  • dual-fuel engine
  • emissions
  • genetic algorithm
  • optimization
  • performance

ASJC Scopus subject areas

  • General Decision Sciences
  • General Environmental Science
  • Computer Science Applications

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