A real-time lifecycle analysis model with digital twin and novel control method for enhancing the environmental performance of electric/hybrid propulsion ships
Heemoon Kim
Abstract
This paper presents a novel investigation into battery-hybrid electric propulsion systems using alternative fuels such as hydrogen and ammonia, integrating optimal load control mechanisms with real-time lifecycle assessment models. Through a digital twin framework, this study evaluates six vessel types under diverse propulsion configurations, incorporating real-time data and fuel lifecycle inventories to create a dynamic and adaptive assessment system. Digital twin technology is used to simulate and monitor ship power outputs, enabling comprehensive lifecycle analyses and identifying key operational and environmental performance metrics. Case studies demonstrate substantial lifecycle environmental benefits of renewable fuels like hydrogen, ammonia, and electricity, highlighting their potential to achieve significant greenhouse gas (GHG) reductions. The findings underscore the critical importance of fuel-specific strategies, regional energy conditions, and advanced load optimization techniques in maximizing emission reductions. Real-time monitoring and digital twin integration are shown to enhance decision-making, fuel efficiency, and emissions control by providing actionable insights and adaptive control mechanisms. These innovations redefine conventional approaches to lifecycle assessment and offer practical pathways for achieving cleaner, more efficient, and sustainable maritime operations, providing actionable guidance for ship operators, policymakers, and researchers dedicated to advancing a low-carbon maritime industry. • Hybrid propulsion using hydrogen/ammonia is analyzed with real-time life cycle assessment models. • Digital Twin-based real-time LCA is proposed to respond to dynamic challenges in shipping. • Case studies show real-time monitoring enhances decisions, fuel efficiency, and emission management. • Study proposes standard LCA framework and digital tools for adaptive environmental assessment.