Efficient ELM Model With Parameter Optimization Using Pso Algorithms in the Prediction of Combustion Pressure Parameters of Dsi Engine Using Ethanol- Gasoline Blends

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Authors

  • Suresh Shetty
     Department of Mechanical Engineering, N.M.A.M Institute of Technology, Nitte (Deemed to be University), Udupi - 574110, Karnataka ,IN
  • Chennabasappa Hampali
     School of Mechanical Engineering, REVA University, Bangalore - 560064, Karnataka ,IN

DOI:

https://doi.org/10.18311/jmmf/2023/36265

Keywords:

ANN, ELM, PSO-ELM, TSI

Abstract

The present study focused mainly on developing PSO based ELM model to predict cylinder pressure associated parameters. Performance of PSO-ELM model then compared with ELM model to obtain its credential. For training and testing the models, data has been acquired through experiments on a Twin Spark Ignition (TSI) gasoline engine using EGB as fuel. The various operating variables are treated as input data whereas cylinder pressure associated parameters are treated as output data for the model. The result of the proposed modelling study indicated that PSO-ELM model has obtained the best performance with lowest value of MSE, MAPE (%) and hidden layer size as compared to ELM model. Hence PSO-ELM results in an efficient model structure with great generalization performance. Further, it is also observed that PSO-ELM takes more time as it calls for an iterative procedure for searching the optimal solution as compared to ELM, which takes only a single epoch.

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Published

2023-11-30

How to Cite

Shetty, S., & Hampali, C. (2023). Efficient ELM Model With Parameter Optimization Using Pso Algorithms in the Prediction of Combustion Pressure Parameters of Dsi Engine Using Ethanol- Gasoline Blends. Journal of Mines, Metals and Fuels, 71(11), 2373–2388. https://doi.org/10.18311/jmmf/2023/36265

Issue

Volume 71, Issue 11, November 2023

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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