Data-Driven Propulsion Load Profile Prediction for All-Electric Ships-Reference-Cited by-同舟云学术

Data-Driven Propulsion Load Profile Prediction for All-Electric Ships

Published:2022-11-16 Issue: Volume: Page:
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Container-title:2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)
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Author:

Chen Wenjie¹,Tai Kang¹,Lau Michael²,Abdelhakim Ahmed³,Chan Ricky R.⁴,Adnanes Alf Koare⁵,Tjahjowidodo Tegoeh⁶

Affiliation:

1. School of Mechanical and Aerospace Engineering, Nanyang Technological University,Singapore

2. Newcastle University in Singapore,Singapore

3. ABB Corporate Research,Västerås,Sweden

4. Marine and Ports, ABB Oy,Helsinki,Finland

5. Marine and Ports ABB Engineering (Shanghai) Ltd.,Shanghai,China

6. Katholieke Universiteit Leuven,Department of Mechanical Engineering,Leuven,Belgium

Publisher

IEEE

Link

Reference23 articles.

1. Prediction of full-scale propulsion power using artificial neural networks;pedersen;Compit '09,2009

4. Diesel engines: for ship propulsion and power plants;kuiken;Target Global Energy Training,2008

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