This paper presents the modelling and real time implementation of PEM (polymer electrolyte membrane) fuel cell flow control. Flow control presents a critical performance requirement to achieving dynamic power responses for electric vehicle motor demands. However a fuel cell's complex structure and reactant requirements traditionally result in an unsatisfactory response to such dynamic loading instances. This in turn causes brief power losses associated with driving patterns such as acceleration and hill climbing. To improve the fuel cell's dynamic response to such drive cycles, this paper presents new methodology for system identification and controller design. The fuel cell is modelled initially with established linear model and parameter estimation methods. The approach is then expanded to an on-line system identification LabVIEW programme to account for the non-linear and time varying characteristics. Based upon this identification process, a novel LabVIEW self-tuning PID controller is implemented in real time to control the response. The self-tuning controller continuously re-calculates the critical gain and period, and then adjusts the controller actions accordingly. Conclusions are then summarised from the results and future ongoing work is discussed briefly.