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In automotive market, today more than in the past, it is very important to reduce time to market and, mostly, developing costs before the final production start. Ideally, bench and on-road tests can be replaced by multi-body studies because virtual approach guarantees test conditions very close to reality and it is able to exactly replicate the standard procedures. Therefore, today, it is essential to create very reliable models, able to forecast the vehicle behavior on every road condition (including uneven surfaces). The aim of this study is to build an accurate multi-body model of a heavy-duty truck, check its handling performance, and correlate experimental and numerical data related to comfort tests for model tuning and validation purposes. Experimental results are recorded during tests carried out at different speeds and loading conditions on a Belgian blocks track. Simulation data are obtained reproducing the on-road test conditions in multi-body environment.

The paper discusses a gearbox design method based on an optimization algorithm coupled to a fully integrated tool to draw 3D virtual models, in order to verify both functionality and design. The aim of this activity is to explain how the state of the art of the gear design may be implemented through an optimization software for the geometrical parameters selection of helical gears of a manual transmission, starting from torque and speed time histories, the required set of gear ratios and the material properties. This approach can be useful in order to use either the experimental acquisitions or the simulation results to verify or design all of the single gear pairs that compose a gearbox. Genetic algorithm methods are applied to solve the optimization problems of gears design, due to their capabilities of managing objective functions discontinuous, non-differentiable, stochastic, or highly non-linear.