Journal article

Pressure Sensor Data-Driven Optimization of Combustion Phase in a Diesel Engine

Qingyuan Tan, Prasad S Divekar, Ying Tan, Xiang Chen, Ming Zheng

IEEE/ASME Transactions on Mechatronics | Institute of Electrical and Electronics Engineers (IEEE) | Published : 2020

Abstract

In this article, a pressure sensor data-driven optimization by using extremum seeking (ES) technique is applied to optimize the combustion phase in a diesel engine. In particular, a cost function is constructed for the ES optimization with the in-cylinder maximum temperature T^maxn , which is an indication of NOx emission performance, and the thermal efficiency ηn as tradeoff considerations. The data-driven nature lies in the fact that T^maxn is estimated from the in-cylinder pressure measurement within each engine cycle by assuming the in-cylinder process to be a quasi-steady state process, which is, then, compensated with the model-free ES optimization. It is noted that the approach develo..

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University of Melbourne Researchers

Grants

Funding Acknowledgements

The work of Clean Combustion Engine Laboratory was supported in part by the Canada Research Chair program, in part by Natural Sciences and Engineering Research Council, in part by Canada Foundation for Innovation, in part by the University of Windsor, in part by Ford Motor Company, and in part by other OEMs.