Articles
| Open Access | ADVANTAGES OF USING ARTIFICIAL INTELLIGENCE TO OPTIMIZE FUEL-AIR MIXTURE IN AUTOMOBILE ENGINES
Muxtorov Oqilbek Ulug’bek ugli , Fergana State Technical University Faculty Of Mechanical Engineering student of group 34-23 TvmAbstract
Artificial intelligence can analyze large amounts of data from engine sensors (air pressure, temperature, engine speed, air mass, etc.) and automatically optimize the air-fuel ratio (AFR) in real time. This avoids leaving a "bare" or "dark" mixture in each case.
Keywords
Artificial intelligence, fuel-air mixture, engine.
References
Ali Fadiel, A. F. (2021). Analysis and optimization of thermal system efficiency in internal combustion engines using artificial intelligence technologies. Journal of Engineering Research and Development.
Owoyele, O., & Pal, P. (2020). A novel machine learning-based optimization algorithm for accelerating simulation-based engine design (ActivO). arXiv preprint arXiv:2012.04649.
Aithal, S. M., & Balaprakash, P. (2019). Machine learning for large-scale simulation-based time-varying driving cycles (MaLTESE). arXiv preprint arXiv:1909.09929.
Norouzi, A., et al. (2022). Machine learning integrated with model prediction for simulated optimal control of internal combustion engines. arXiv preprint arXiv:2204.00142.
Norouzi, A., et al. (2022). Deep learning-based model prediction control for internal combustion engines.
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