AI-enhanced energy efficiency measures for optimal ship operations to reduce GHG emissions
Research Project , 2021 – 2024

Ship operation-related energy efficiency measures (EEMs) can help reach the IMO 2030 emission goals. However, today, their benefits have not been fully realized. Through the digital transformation in shipping, vast amounts of vessel data are being collected, enabling activation of AI-powered solutions to further improve vessel performance. Our purpose is to support the shipping industry to achieve greener ship operations. Our goal is to develop an operational support solution strengthened by AI on taking EEMs into account for enhanced energy efficiency.

Participants

Wengang Mao (contact)

Professor at Chalmers, Mechanics and Maritime Sciences, Marine Technology

Zhang Daiyong

Doctoral Student at Chalmers, Mechanics and Maritime Sciences, Marine Technology

Xiao Lang

Doctoral Student at Chalmers, Mechanics and Maritime Sciences, Marine Technology

Collaborations

DNV Advisory Services

Goteborg, Sweden

Molflow AB

Gråbo, Sweden

Yara Marine Technologies AB

Göteborg, Sweden

Funding

VINNOVA

Project ID: 2021-02768
Funding Chalmers participation during 2021–2024

Related Areas of Advance and Infrastructure

Information and Communication Technology

Areas of Advance

Transport

Areas of Advance

Energy

Areas of Advance

Innovation and entrepreneurship

Driving Forces

More information

Latest update

2021-11-03