Work

Data-driven Modeling and Predictive Control of Maximum Pressure Rise Rate in RCCI Engines

Year: 2020

Type: conference-paper

Source: IEEE Conference on Control Technology and Applications (CCTA)

DOI: 10.1109/ccta41146.2020.9206358

Authors: L. N. Aditya Basina, Behrouz K. Irdmousa, Javad Mohammadpour Velni, Hoseinali Borhan, Jeffrey D. Naber, Mahdi Shahbakhti

Institutions: Michigan Technological University, University of Georgia, Cummins (United States), University of Alberta

Language: English

Topic: Advanced Combustion Engine Technologies

Subfield: Fluid Flow and Transfer Processes

Field: Chemical Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: closed

OpenAlex ID: W3089638218

FWCI: 5.692

Cites: 15

Cited by: 20

Related to: 10