Requirements on ships are rapidly increasing. In particular, safety and environmental impact are under increasing scrutiny. At the same time, cost and profitability remain as important as they have ever been. These increasingly stringent constraints are beginning to pose problems during the design process. For example, the energy efficiency design index (EEDI) aims to reduce emissions of carbon dioxide by progressively limiting engine power installed on board. However, these reductions in propulsive power raise concerns about the ship's manoeuvrability in rough seas. Moreover, the expected introduction of novel power and propulsion systems based on, for example, fuel cell technology, further raises uncertainty regarding the performance of future ships and propulsion systems in dynamic environments. Considering these developments, detailed predictions of manoeuvrability and propulsion plant behaviour are becoming increasingly important in the ship design process. Yet, present prediction methods are insu_cient to evaluate manoeuvrability and behaviour of ship propulsion systems in complex, dynamic environments such as heavy seas. Fully numerical methods based on computational fluid dynamics (CFD) and first principles are inherently uncertain and compute-intensive. As such, these methods are presently unsuitable to assess the dynamic interaction between machinery and hydrodynamics over prolonged periods of time. As an alternative to numerical methods, experiments with scale model ships can be conducted. However, such experiments are subject to hydrodynamic scale effects: viscous friction, spray formation and propeller cavitation are not the same as at full scale. Moreover, these model ships are powered by considerably simplified propulsion systems, causing entirely different propulsion plant dynamics than at full scale. Ideally, scale model experiments would be conducted with, for example, a perfectly downscaled diesel engine, gearbox and propeller; in practice, however, this is generally not feasible. As such, existing prediction methods leave great uncertainty how future ship designs can simultaneously meet all requirements regarding operational performance, safety and compliance with environmental regulations. A possible way to bridge this knowledge gap is by conducting hardware in the loop (HIL) experiments in the ship model basin. Such experiments combine numerical simulations with a physical test setup. During HIL experiments with free sailing ship models, the propulsion engine and other machinery are simulated by a computer. These simulations are then used to control an electric motor, powering the propeller of a physical scale model ship. As such, the complex interaction between engine, propeller, hull and environment can be physically reproduced, allowing to assess design choices early on in the ship design process.