Data-driven ship typical operational conditions: A benchmark tool for assessing ship emissions
Journal article, 2024

Analysing operational conditions of ships presents a novel approach to assessing emission levels, motivated by the inadequacy of traditional static weighting factors, such as ISO 8178-E3 cycle, to capture the dynamic and complex operating characteristics of ships at sea. This study introduces a data-driven method to construct and validate ship typical operational conditions. The method encompasses identifying ship motion states, extracting features, compressing time series data based on these features, and performing cluster analysis. It has been applied to process over 12.6 million data points, demonstrating its applicability to a large dataset. The results indicate that by using actual measurement data and the proposed methodology, three typical operational conditions for ships were successfully established. There are significant differences in the feature parameters among these conditions, highlighting the distinct characteristics of each operational state. The validity of the constructed typical operational conditions was confirmed through a validation process, which involved analysing the differences in feature parameters and comparing the probability distributions of speed and acceleration to the overall dataset. Additionally, energy consumption and emission levels calculated using the typical conditions were validated through comparison with real-world data from upstream and downstream voyages. This study providing a novel tool for assessing emissions in the maritime industry.

Emission evaluation

Data-driven approach

Ship operational conditions

Kinematic segments

ISO 8178-E3 cycle

Author

Ailong Fan

Wuhan University of Technology

East Lake Laboratory

Xuelong Fan

Wuhan University of Technology

Mingyang Zhang

Aalto University

Liu Yang

Wuhan University of Technology

Yuqi Xiong

Fudan University

Xiao Lang

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Chenxing Sheng

Wuhan University of Technology

Yapeng He

Wuhan University of Technology

Journal of Cleaner Production

0959-6526 (ISSN)

Vol. 483 144252

Subject Categories

Energy Engineering

Vehicle Engineering

Other Civil Engineering

DOI

10.1016/j.jclepro.2024.144252

More information

Latest update

11/29/2024