Journals / International Journal of Automotive Engineering and Technologies / 2015 / Cilt: 4 - Sayı: 1

Estimating engine performance and emission values using anfis

Pages
63–67
Publication Date
2022-10-18
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It is seen that the obtained ANFIS model can makesolid estimations about output emission and performance values of an internal combustionengine with different methanol mixtures.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, the effect of methanol mixtures in different proportions to emission andperformance of the motor has been estimated using Adaptive Neuro Fuzzy Inference System(ANFIS) model.
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Key Findings & Data:The estimatedperformance of the model has been obtained by comparison of the estimated results of theANFIS model and the experimental results.
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Conclusion & Impact:It is seen that the obtained ANFIS model can makesolid estimations about output emission and performance values of an internal combustionengine with different methanol mixtures.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this study, the effect of methanol mixtures in different proportions to emission andperformance of the motor has been estimated using Adaptive Neuro Fuzzy Inference System(ANFIS) model. Traini ng data and test data have been obtained from the results of experimentson a single cylinder, four- stroke engine with direct- injection under different spraying pressures.An ANFIS model has been developed using these experimental data. The estimatedperformance of the model has been obtained by comparison of the estimated results of theANFIS model and the experimental results. It is seen that the obtained ANFIS model can makesolid estimations about output emission and performance values of an internal combustionengine with different methanol mixtures.

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Cite This Article

ÖZKAN, İ. A., CINIVIZ, M., CANDAN, F. (2022). Estimating engine performance and emission values using anfis. International Journal of Automotive Engineering and Technologies, Cilt: 4 - Sayı: 1, 63–67. https://ajindex.com/articles/540394

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References (6)

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