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In the paper some methods are presented, with the corresponding practical examples, related to MonteCarlo (MC) techniques for thermal model/test correlation purposes. The MonteCarlo techniques applied to model correlation are intended to be used as an alternative to empirical ‘manual’ correlation techniques, gradients methods, matrix methods based on least square fit minimization. First of all, Design Of Experiments (DoE) tools are used to determine the model response to uncertain parameters and the confidence level of such a response. A sensitivity map is built, allowing the design of the test to maximize the response of the system to the uncertain parameters. Techniques derived from the extreme statistics are used to extrapolate data beyond test limits, with a sufficient confidence in the queue behaviour.

In the paper several application techniques of MonteCarlo (MC) method applied to thermal analysis of space vehicles are presented. Although these methods are widely used in other engineering domains, their introduction to the thermal one is quite recent and not fully developed in the industrial practice. This paper aims at showing that, even without demanding computation resources (all what presented has been obtained with a single processor PC) MonteCarlo analysis techniques, in a preliminary design phase, can support and integrate engineering judgment of the thermal designer. In particular, it is exploited the applicability of the method to reduced thermal models, with a clear advantage in terms of computation time. An original approach is proposed, and results are shown. The papers shows the applicability of the MC method to the case when experimental data of the uncertain parameters are available, using the bootstrap re-sampling techniques.

The evolution of automotive engines calls for the design of electronic control systems optimizing the engine performance in terms of reduced fuel consumption and pollutant emissions. However, the opportunities provided by modern engines have not yet completely exploited, since the adopted control strategies are still largely developed in a very heuristic way and rely on a number of SISO (Single Input Single Output) designs. On the contrary, the strong coupling between the available actuators calls for a MIMO (Multi Input Multi Output) control design approach. To this regard, the availability of reliable dynamic engine models plays an important role in the design of engine control and diagnostic systems, allowing for a significant reduction of the development times and costs. This paper presents a control-oriented model of the air-path system of today's gasoline internal combustion engines.

An experimental campaign is presented aiming at the characterization of thermal dissipation of batteries to be used on board of small satellites. A suitably designed device allows to manage automatically the orbital cycling simulation between battery cell charge and discharge. The cell thermal performance is characterized in various combinations of temperature, discharge current and Depth of Discharge. The gathered data are used for providing guidelines in the design of a family of Italian Small Satellites.

The paper presents a new test rig (named RuotaVia) composed basically by a drum (2,6 m diameter), providing a running contact surface for vehicle wheels. A number of measurements on either full vehicles or vehicle sub-systems (single suspension system or single tyre) can be performed. Tire characteristics influencing rollover can be assessed. The steady-state maximum loads are as follows: Radial: 100kN, tangential: 100kN, lateral (axial with respect to the drum): 100kN. The superstructure carrying a measuring hub can excite the wheel under test up to 20 Hz in lateral and vertical directions. The steer angle range is ± 25 deg, the camber range is ± 80 deg. The minimum eigenfrequency of the drum is higher than 90 Hz and its maximum tangential speed is 440 km/h.