Intelligent energy management is a cost-effective key path to realize efficient automotive drive trains [R. O’Hayre, S.W. Cha, W. Colella, F.B. Prinz. Fuel Cell Fundamentals, John Wiley & Sons, Hoboken, 2006]. To develop operating strategy in fuel cell drive trains, precise and computational efficient models of all system components, especially the fuel cell stack, are needed. Should these models further be used in diagnostic or control applications, then some major requirements must be fulfilled. First, the model must predict the mean fuel cell voltage very precisely in all possible operating conditions, even during transients. The model output should be as smooth as possible to support best efficient optimization strategies of the complete system. At least, the model must be computational efficient. For most applications, a difference between real fuel cell voltage and model output of less than 10 mV and 1000 calculations per second will be sufficient. In general, empirical models based on system identification offer a better accuracy and consume less calculation resources than detailed models derived from theoretical considerations [J. Larminie, A. Dicks. Fuel Cell Systems Explained, John Wiley & Sons, West Sussex, 2003]. In this contribution, the dynamic behaviour of the mean cell voltage of a polymer-electrolyte-membrane fuel cell (PEMFC) stack due to variations in humidity of cell’s reactant gases is investigated. The validity of the overall model structure, a so-called general Hammerstein model (or Uryson model), was introduced recently in [M. Meiler, O. Schmid, M. Schudy, E.P. Hofer. Dynamic fuel cell stack model for real-time simulation based on system identification, J. Power Sources 176 (2007) 523–528]. Fuel cell mean voltage is calculated as the sum of a stationary and a dynamic voltage component. The stationary component of cell voltage is represented by a lookup-table and the dynamic voltage by a parallel placed, nonlinear transfer function. A suitable experimental setup to apply fast variations of gas humidity is introduced and is used to investigate a 10 cell PEMFC stack under various operation conditions. Using methods like stepwise multiple-regression a good mathematical description with reduced free parameters is achieved.