Machine learning-based multi-objective optimization and thermodynamic evaluation of organic Rankine cycle (ORC) system for vehicle engine under road condition-Reference-Cited by-同舟云学术

Machine learning-based multi-objective optimization and thermodynamic evaluation of organic Rankine cycle (ORC) system for vehicle engine under road condition

Published:2023-08 Issue: Volume:231 Page:120904
ISSN:1359-4311
Container-title:Applied Thermal Engineering
language:en
Short-container-title:Applied Thermal Engineering

Author:

Xing Chengda,Ping Xu,Guo Ruilian,Zhang Hongguang,Yang Fubin,Yu Mingzhe,Yang Anren,Wang Yan

Funder

Natural Science Foundation of Beijing Municipality

State Key Laboratory of Engines

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Energy Engineering and Power Technology,Fluid Flow and Transfer Processes,Mechanical Engineering

Reference52 articles.

1. Zeotropic working fluid selection for an organic Rankine cycle bottoming with a marine engine;Wang;Energy,2022

2. An outlier removal and feature dimensionality reduction framework with unsupervised learning and information theory intervention for organic Rankine cycle (ORC);Ping;Energy,2022

3. Effect factors of part-load performance for various Organic Rankine cycles using in engine waste heat recovery;Wang;Energ. Conver. Manage.,2018

4. Experimental study on operating parameters matching characteristic of the organic Rankine cycle for engine waste heat recovery;Zhang;Energy,2022

5. Experimental study of an organic Rankine cycle with R1233zd(E) for waste heat recovery from the coolant of a heavy-duty truck engine;Rijpkema;Energ. Conver. Manage.,2021

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