Project Summary

The project team are designing and building a zero-emission uncrewed surface vessel powered by a novel liquid hydrogen propulsion system. The project will focus on designing and building an advanced control and optimisation algorithm with a specific focus around the control of liquid hydrogen powered marine vessels.

Project Achievements

Activities a. Removing the need for human intervention in non-routine operations b. Automate control and environmental monitoring of vessel compartments • Workshops and engagement with electrical suppliers. next step in the automation of maintenance by capturing critical vessel data and distributing it securely to a ROC. This project demonstrates an end-to-end (from source to cloud-based analytics pipeline including a notification service) solution. The solution also uses an algorithm that models and identifies asset failures and raises alarms, e.g., hydrogen-related alarms from the fuel cell and fuel tank. • Integration of hardware redundancy for safer operations. • A digital platform for monitoring and anomaly detection for H-USV systems. • Control and monitoring of electrical and propulsion equipment including sensors. • Data analytics and sensor correlations and anomaly detection using the digital platform.

Conclusions

The TRIG project allowed us to continue the development of our software and hydrogen systems monitoring and control taking the monitoring and hydrogen safety system capability to TRL4. AcuaSight development continued and we carried out tests with multiple vessels (in a synthetic environment) publishing vessel data in real-time to a hybrid cloud-based C2 system. Both these capabilities are TRL5 ready. Although we do not have access to a representative test environment, AcuaSight

(running on a remote machine) was tested robustly tested with the hydrogen-powered vessel operating in a simulation.

Next Steps

Future work will focus on AI algorithms that can predict changes in the state of the vessel (including engine performance) using historical data along with sea state and weather station data. Our predictive maintenance works aim to collect vessel data over time and expand the operator’s awareness of the vessel by introducing a performance metric, the safe mobility score. The score, computed by onboard computers will feed into wider strategic and mission planning tools such that the vessel state is stable and optimised for its mission entirety. End-user engagement is ongoing with an aim to complete vessel integration and testing by September 2023.