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A predictive dynamic model of a small pressure swing adsorption (PSA) air separation process was developed for the purposes of evaluation, optimization, and control of oxygen generation systems on board military aircraft. A mathematical model of the adsorption beds was formulated by application of fundamental mass- and energy-transport modeling techniques. These equations were discretized using the Galerkin finite element technique. The resulting ODE systems were coupled with ODEs describing the rate of change of pressure in each bed and models of the feed and exhaust valves and purge orifice. The model was developed so that it is possible to predict the dynamic response of product oxygen composition and feed air consumption to step changes in feed pressure, product flow rate, and cycle time. A laboratory PSA unit similar in size to an on-board oxygen generation system (OBOGS) was constructed to validate the model. The laboratory unit was constructed so that step changes could be implemented and the responses observed for comparison with the model. All parameters in the model were estimated from literature sources with the exception of the feed/exhaust valve and purge orifice discharge coefficients. Excellent dynamic predictions of bed pressure, cycle-averaged feed flow rate, and cycle-averaged bed temperature vs time in response to step changes in all three input variables compared to the two-bed PSA data were achieved without additional parameter estimation from two-bed data.