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Current vehicle regulations demand for a challenging decrease in the overall exterior noise as a benefit for the health of citizens and road users. New limits have been implemented in UN R51.03 (based on ISO 362-1:2015) to reduce the emitted noise both at constant speed and in full load so as to cover most of the real urban driving conditions. In order to achieve those targets the carmakers have to refine the trim of their vehicles and an experimental approach can take place too late. This paper shows a method for the pass-by noise simulation exploiting the numerical transfer functions and a library of experimentally characterized sources with the aim to reduce the noise and find out a better tradeoff between costs and effectiveness of the modifications. Moreover a simple software tool for the treatment of the data and to ease the workflow has been created and used for the rank assessment of the different paths.

The time to market in the automotive industry is constantly decreasing pushing the carmaker companies to increase the efforts in numerical simulations and to decrease the number of prototypes. In the NVH field, this time constraint reflects in moving the well-established finite element simulations towards the so called “full-vehicle simulations”. Specifically, the CAE techniques should be able to predict the complete behavior of the vehicles in mission conditions, so to reproduce some usual tests, such as the “coast down” test on different roads. The aim of this paper is to present a methodology to improve rolling noise simulations exploiting an integrated full-vehicle approach. An accurate modeling of all the subsystems is needed, with particular attention to the wheels and the suspension systems. Therefore, the paper firstly covers the modeling approach used to obtain the FE models of tires and suspension system.

Within the automotive industry, a typical way to account for tires in a roadnoise mission simulation is to use the “modal model” supplied by tire manufacturers. Even though this kind of models is certified by the suppliers and is very simple to use, it has the drawback to be disconnected from the physical description of the tire. This reflects in limiting the carmaker company to be able only to request certain modal characteristics to the supplier. The aim of this paper is to present an accurate, yet easy to use, methodology to develop an FE model of a tire, to be used in a full-vehicle simulation. The determined model must be connected to the tire physical properties. These properties are not measured directly, but determined by tuning a properly created geometric FE model to the measured point inertances of the inflated tire. This allows creating the model only by using an optimization algorithm to tune such properties.

In the last years engineers have to deal with multiple, often conflicting targets, where improvement of one quantity leads to deterioration of others, therefore it is impossible to obtain simultaneous structure enhancements without automatic optimizations tools. The so-called trade-offs have to be applied, providing less efficient modifications, nevertheless, for all of the design objectives. The Pareto front is a method that helps to determine a set of equipotential designs. In order to explore entire design space, response surface methodology supplemented by genetic algorithms is often used. In the work presented, the Gaussian Processes Methodology and an Adaptive Range Multi-Objective Genetic Algorithm - ARMOGA were implemented. Basing on the solutions obtained by the design of experiment, response surface methodology is used to predict the values of the measured outputs throughout the full range of interest.

The cost and weight reduction requirements in automotive applications are very important targets in the design of a new car. For this reason all the components of the vehicle should be optimized and the design of the damping material layout needs thoroughly analyzing, in order to have a good NVH performance with the minimum weight and cost. A tool for optimizing the damping material layout has been implemented and tested here - the need to explore the entire design space with a large number of variables suggested the use of a multi-objective genetic algorithm. These algorithms require a large number of calculations, and so the solution of the complete NVH model would be too expensive in terms of computational time. For this reason a new software tool has been developed, based on simulation of the damping material treatments by means of auxiliary mass and stiffness matrices added to the baseline modal base.