Armada Technologies Limited (ATL) is developing a novel "Passive Air Lubrication System" (PALS) to reduce fuel consumption and carbon emissions on merchant ships. The novel element has been designed and is currently under construction for testing in a pressurised cavitation tunnel this September.

PALS will utilise small rotating devices to regulate fluid flows through the system and optimise its performance contingent on operating conditions such as the vessel's speed, draft and trim.

This project is proposed to specify and develop a "PALS" control system to reduce fuel consumption and greenhouse gas (GHG) emissions as much as possible based on its operating conditions such as its speed, draft, trim and the weather and sea conditions.

The project will be delivered by working in partnership with the following UK based world class organisations.

**Arcsilea:** A specialist consultancy focussed on bespoke strategic, technical, data and machine learning based solutions for decarbonisation in the maritime sector.

**Queen's University Belfast,** School of Mechanical and Aerospace Engineering. Led by Professor Paul Maropoulos focussed on smart and Metrology Enabled Manufacturing, combining and linking the process and product verification from cyber to physical domains.

**QinetiQ:** a company of scientists and engineers committed to serving customers' needs. Extensive experience and unique science and engineering expertise can be deployed to equip customers with powerful solutions to their most pressing challenges.

The project is spilt into three separate sections fully utilising the skills and experience of our partners specifically;

**1\. Data:** Collection, analysis and transmission from ship to shore across the world and its oceans.

**2\. System learning**: Providing optimal vessel and PALS operating configurations. Often referred to as "AI" this will form the "brain" of PALS which will continuously learn to enable emission reductions in changing environments.

**3\. System Control:** Provide a design utilising data and learning which delivers instructions to PALS and adjusts its operating configuration to minimise GHG emissions .

These sections will combine to produce a designed and costed Minimum Viable Product of a "digital" twin model control system.

It is planned that PALS will be installed on an operational merchant ship during 2023 with this "brain " an integral part to evaluate 'live' performance data and feedback at sea.