Publication: Optimization strategies for enhancing diesel engine performance and emissions control with biofuel blends: A multi-objective approach
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Issued Date
2024-09-01
Resource Type
eISSN
25901230
Scopus ID
2-s2.0-85203014995
Journal Title
Results in Engineering
Volume
23
Rights Holder(s)
SCOPUS
Bibliographic Citation
Results in Engineering Vol.23 (2024)
Suggested Citation
Wiangkham A., Boontawan A., Pumpuang A., Aengchuan P., Ariyarit A., Sukjit E., Chuepeng S. Optimization strategies for enhancing diesel engine performance and emissions control with biofuel blends: A multi-objective approach. Results in Engineering Vol.23 (2024). doi:10.1016/j.rineng.2024.102819 Retrieved from: https://hdl.handle.net/20.500.14740/20293
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Abstract
This study examines the effects of engine compression ratio, load, and biofuel composition on performance, combustion, and emissions. The experimental setup includes testing different compression ratios (16, 17, 18) and loads (25 %, 50 %, 75 % torque) at a fixed speed of 1500 rpm, using Thai standard diesel as the control fuel. Biofuel variations tested include neat biodiesel, neat biokerosene, and blends of 30 % biokerosene with 70 % biodiesel and 50 % biokerosene with 50 % biodiesel. The results show that an increased compression ratio enhances combustion efficiency, reduces brake specific fuel consumption, and improves brake thermal efficiency, although it also leads to higher nitrogen oxide emissions. Biofuels improve brake thermal efficiency due to their higher oxygen content. However, the increased viscosity of biodiesel can hinder fuel atomization, resulting in higher emissions. In contrast, biokerosene improves brake thermal efficiency by facilitating earlier combustion and reducing emissions. Performance is primarily affected by load, while emissions are influenced by both biokerosene content and load. Gradient boosting models and optimization techniques, such as the non-dominated sorting genetic algorithm III (NSGA-III) and adaptive geometry estimation-based multi-objective evolutionary algorithms (AGE-MOEA), produce consistent results, with AGE-MOEA identifying denser optimal points. The findings suggest that optimal biokerosene blends ranging from 20 % to 40 %, across all compression ratios and loads of 50 %–75 %, provide valuable insights for advancing sustainable fuel utilization practices in automotive vehicles.