Machine Learning Model for Spark-Assisted Gasoline Compression Ignition Engine
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Publisher
SAE International
Reference32 articles.
1. Kalghatgi, G. and Johansson, B., “Gasoline Compression Ignition Approach to Efficient, Clean and Affordable Future Engines,” Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 232, no. 1 (2018): 118-138, doi:10.1177/0954407017694275.
2. Viollet, Y., Chang, J., and Kalghatgi, G., “Compression Ratio and Derived Cetane Number Effects on Gasoline Compression Ignition Engine Running with Naphtha Fuels,” SAE International Journal of Fuels and Lubricants 7, no. 2 (2014): 412-426. https://doi.org/10.4271/2014-01-1301.
3. Chang, J., Kalghatgi, G., Amer, A., and Viollet, Y., “Enabling High Efficiency Direct Injection Engine with Naphtha Fuel through Partially Premixed Charge Compression Ignition Combustion,” SAE Technical Paper 2012-01-0677, 2012, https://doi.org/10.4271/2012-01-0677.
4. Chang, J., Viollet, Y., Amer, A., and Kalghatgi, G., “Fuel Economy Potential of Partially Premixed Compression Ignition (PPCI) Combustion with Naphtha Fuel,” SAE Technical Paper 2013-01-2701, 2013, https://doi.org/10.4271/2013-01-2701.
5. Badra, J., Elwardany, A., Sim, J., Viollet, Y. et al., “Effects of In-Cylinder Mixing on Low Octane Gasoline Compression Ignition Combustion,” SAE Technical Paper 2016-01-0762, 2016, https://doi.org/10.4271/2016-01-0762.
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