Development of High Compression-Ratio Stepped-Lip Piston using Machine Learning

Format:

Book

Conference/Event

Author/Creator:

Jhā, Prabhāta, author.

Contributor:

Zainal Abidin

Bitsis, Chris

Briggs, Thomas

Cung Khanh

Shah, Bansal

Smith, Edward

Conference Name:

SAE Powertrains, Fuels & Lubricants Conference & Exhibition (2022-09-06 : Krakow, Poland)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2022

Summary:

Interaction between a diesel spray and piston plays a significant role in overall combustion and emissions performance in compression-ignition engines. It is essential to design the lip feature respective to spray targeting and the following charge motion for combustion systems that rely on spray-piston interaction strongly, such as a stepped-lip piston. This study used a numerical campaign using computational fluid dynamics (CFD) simulation to optimize a stepped-lip combustion system at a 22:1 compression ratio (CR) for both performance and emissions. This is a substantial step up in CR from the stock value of 17:1 for the same engine platform.A machine learning model was used to identify the best combination of features from a design space involving hundreds of potential piston designs and injector nozzle configurations. This study provides a discussion on the general combustion characteristics of the stepped-lip combustion system and the sensitivity of the design parameters. Comparison of the CFD predictions for the final system design and single-cylinder engine (SCE) experimental results showed good agreement for combustion performance and emissions. Further opportunities for improvements to the combustion system are also discussed

Notes:

Vendor supplied data

Publisher Number:

2022-01-1054

Access Restriction:

Restricted for use by site license