In the field of polymer electrolyte membrane fuel cells (PEMFC), significant research has focused on the membrane electrode assembly (MEA) and electrochemical characterization methods. For real applications optimizing the fuel cell system (FCS) design is essential, requiring careful monitoring of electrochemical and thermodynamic process parameters such as pressure, temperature, relative humidity, heat flux, and gas composition. These operating conditions, provided by balance of plant (BoP) components, significantly impact FCS efficiency, especially relative humidity, which demands high energy input. The first step in a system development involves comprehensively characterizing the MEA by mapping a wide range of operating parameters, not just peak performance points, which are not necessarily the most beneficial for the FCS. This requires precise and dynamic adjustments of process parameters during testing to capture all relevant data efficiently. Currently available test stands lack the capability for high throughput testing with sufficient data accuracy. This paper addresses the essential attributes of an ideal testing environment for fuel cells, using relative humidity as a key example. It examines the limitations of conventional humidification methods, such as slowly adjustable bubble humidifiers. Experimental characterization of a bubble humidification system revealed inaccuracies of up to 5 °C in dew point temperature, leading to a deviation of up to 25% in relative humidity depending on the fuel cell temperature. The reproducibility and accuracy of this humidification technique are evaluated, demonstrating an optimal operating range for a bubbler and boundary regions where it functions less accurately. Basic requirements for humidification units for fuel cell test stands are derived. A proposed solution involves precise mass flow control of the water, which is the focus of future work. In summary, this paper represents a crucial step towards faster and more accurate testing methods, ensuring the precise adjustment of operating conditions to optimize system design and efficiency.