Mathematical models become more and more indispensable tools for engine manufacturers. As nonlinear dynamic models based on first-principles are preferred by practitioners, model calibration or parameter estimation is often a time consuming task. The use of optimally designed dynamic inputs can reduce the experimental burden and increase the accuracy of the estimated pa-rameters. The current paper presents the calibration and validation of a Diesel engine airpath model. Optimal inputs have been designed based on random phase multisine inputs. These multisines can be adapted to excite exclusively a specific frequency band of interest. Moreover, they allow (i) to concentrate the input around an operating point, and (ii) to include fast variations in the input profile without introducing a large number of dis-cretization parameters. The resulting model has been found to provide an acceptable predictive power in both identification and validation.