Predictive Models for Biodiesel Performance and Emission Characteristics in Diesel Engines: A Review

Wenbo Ai and Haeng Muk Cho ()
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Wenbo Ai: Department of Mechanical Engineering, Kongju National University, Cheonan 31080, Republic of Korea
Haeng Muk Cho: Department of Mechanical Engineering, Kongju National University, Cheonan 31080, Republic of Korea

Energies, 2024, vol. 17, issue 19, 1-25

Abstract: With the increasing global demand for renewable energy, biodiesel has become a promising alternative to fossil fuels with significant environmental benefits. This article systematically reviews the latest advances in predictive modeling techniques for estimating the characteristics of biodiesel and its impact on diesel engine performance. Various methods for predicting the key performance of biodiesel and the performance and emissions of diesel engines have been summarized. According to the categories of parameters, research cases in recent years have been listed and discussed separately. This review provides a comprehensive overview and serves as a reference for future research and development of biodiesel.

Keywords: biodiesel; predictive modeling; diesel engine performance; emissions; statistical methods (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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