M&TT Colloquia 2025-2026

16-10-2025 - Lecture Hall E

Mini Symposium - Technical Talk

Data Driven Decision making for the Maritime Industry

Roy de Winter

As we speak, the entire world fleet and the environmental conditions they are operating in are continuously monitored by AIS transceivers, (onboard) sensors, and satellites.
The main characteristics of these vessels can be retrieved from shipping registers, databases, and classification societies. More data about ships and their environment is readily available now than ever before. Unfortunately, naval architects, operators, and policy makers rarely exploit this data to its fullest extent.
During this M&TT Colloquia presentation, I aim to show you some examples on how data analysis can be used to improve ship designs, ship operations, and how we can use it to inform policymakers.

02-10-2025 - Lecture Hall E

PhD presentation

Dynamic Modeling, Parameter Identification, and Control of PEM Fuel Cells for Maritime Applications

Ege Ceyhun

The decarbonization of the maritime industry requires efficient and reliable power and energy systems that can operate under demanding conditions.
Proton Exchange Membrane (PEM) fuel cells are a promising zero-emission solution for ships, offering high efficiency and flexibility, but their integration into maritime applications depends on accurate system modeling and carefully designed control strategies.
In this work, a control-oriented dynamic PEM fuel cell model is developed to represent the essential electrochemical, thermal, and flow processes with the minimum number of states. The parameters of the model are identified using the collected data from the experiments, which provides a connection between theoretical formulations and practical system behavior. The identified model is used for the design and comparison of different control strategies, addressing key objectives such as state tracking.
Future work will extend this framework by comparing additional control approaches relevant to maritime operations, enhancing the model to capture further dynamic phenomena and integrating it with a battery model to design different energy management strategies.

18-09-2025 - Lecture Hall J

PhD presentation

Safe Autonomous Navigation in Inland Waterways: Results from Diagnosis and Control

Abhishek Dhyani

Autonomy and digitalisation are paving the way for a safer, cleaner, and efficient inland waterway transportation system. The benefits of smart shipping include making the job safer for the human crew, reducing fuel consumption and better utilisation of the inland waterways. New challenges must, however, be addressed first to ensure that the underlying technologies can be incorporated safely.
In this presentation, I will discuss some results involving model-based design methodologies for ensuring safer autonomous navigation, namely: robust vessel maneuvering modelling and identification, multiple sensor fault diagnosis and autonomous control system design. The resulting algorithms prioritise safety, robustness and fault tolerance in the system design and onboard decision-making.

18-09-2025 - Lecture Hall J

PhD presentation

Modular Energy Management for Fuel Cell-Battery Shipboard Microgrids

Timon Kopka

The electrification of ship power systems plays a central role in the mobility transition towards sustainable transport solutions. It allows the integration of various power sources, energy storage systems, and intermittent generation. An increasing number of components with distinct characteristics shapes the notion of a shipboard microgrid which benefits from a modular approach in its design to reduce costs and uncertainties. DC distribution facilitates the modular design by simplifying the control, and, combined with power electronics interfaces, increases the controllability of power flows in the system.
To handle the increasing system complexity, we propose a distributed and predictive energy management approach, addressing the modular topology of future shipboard power systems and leveraging load power forecasting. Preliminary investigations show that a distributed, predictive energy management reaches a similar performance as a centralized implementation. For a modular shipboard power system, the proposed approach decreases both fuel and degradation costs with increasing performance gains for longer prediction horizons.