Co-optimization of miller degree and geometric compression ratio of a large-bore natural gas generator engine with novel Knock models and machine learning

Cao, Jiale; Li, Tie; Huang, Shuai; Chen, Run; Li, Shiyan; Kuang, Min; Yang, Rundai; Huang, Yating

doi:10.1016/j.apenergy.2023.121957

Applied Energy

2023

DOI: 10.1016/j.apenergy.2023.121957

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Co-optimization of miller degree and geometric compression ratio of a large-bore natural gas generator engine with novel Knock models and machine learning

Jiale Cao,

Tie Li,

Shuai Huang

et al.

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Co-optimization of miller degree and geometric compression ratio of a large-bore natural gas generator engine with novel Knock models and machine learning

Cited by 3 publications

References 37 publications

Optimization and prediction of a novel preignition in hydrogen direct injection engines through experimentation and the Random forest algorithms

Optimization and prediction of a novel preignition in hydrogen direct injection engines through experimentation and the Random forest algorithms

Experimental investigation of knock control criterion considering power output loss for a PFI SI methanol marine engine

Thermodynamics-based data-driven combustion modelling for modern spark-ignition engines

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