  The paper deals with an empirical validation of a building thermal model. We
put the emphasis on sensitivity analysis and on research of inputs/residual
correlation to improve our model. In this article, we apply a sensitivity
analysis technique in the frequency domain to point out the more important
parameters of the model. Then, we compare measured and predicted data of indoor
dry-air temperature. When the model is not accurate enough, recourse to
time-frequency analysis is of great help to identify the inputs responsible for
the major part of error. In our approach, two samples of experimental data are
required. The first one is used to calibrate our model the second one to really
validate the optimized model.
