A model-based Design of Experiments method was employed for the optimisation of measurements on a Solid Oxide Fuel Cell (SOFC). Based on a simplified SOFC model, a variation of the D-optimality was used as optimisation criterion for the calculation of optimal experimental designs (determinant of the covariance matrix with weighting factors). Solutions for different numbers of design points were calculated and the behaviour of optimisation criteria as functions of the number of design points as well as of the number of repetitions of measurements was analysed. A new type of graph was introduced which depicts the behaviour of optimisation criteria for constant number of measurements. This approach showed that, for constant numbers of measurements, the precision is higher and therefore the reliability in the cell’s model identification is improved when repeated measurements of a small set of optimal design points are effectuated, instead of many different measurements. Finally, a sensitivity analysis was performed showing the influence of the parameter values on the values of the optimisation criterion and the optimal measurements. The used methodology and its theoretical conclusions may be used as a basis for development of diagnostics tools or filtering existing data for optimal parameter estimations.