L2M – Optimizing Energy Efficiency in Sea Transportation Using Machine Learning

Our project tackles the critical challenge of optimizing energy efficiency in electric boats, a vital issue in the growing market of sustainable marine transportation. The primary problem lies in the inefficient energy consumption of electric motors used in electric boats when navigating varying wave conditions, leading to reduced range and increased operational costs. This research will contribute towards sustainable and environmentally friendly marine travel by developing innovative strategies to improve motor efficiency, reduce energy loss, and extend battery life. Through this work, we aim to support the shift to cleaner marine transportation, minimizing carbon emissions and operational costs while enhancing the viability of electric boats as a reliable, eco-friendly alternative.

Faculty Supervisor:

Ashraf Ali Khan

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Automotive; Sustainability & the Environment; Transportation (excluding aerospace)

University:

Memorial University of Newfoundland

Program: