Weight optimization of aluminium alloy automobile parts reduces their weight while maintaining their natural frequency away from the frequency range of the power spectral density (PSD) that describes the roadway profile. We present our algorithm developed to optimize the weight of an aluminium alloy sample relative to its fatigue life. This new method reduces calculation time; It takes into account the multipoint excitation signal shifted in time, giving a tangle of the constraint signals of the material mesh elements; It also reduces programming costs. We model an aluminium alloy lower vehicle suspension arm under real conditions. The natural frequencies of the part are inversely proportional to the mass and proportional to flexural stiffness, and assumed to be invariable during the process of optimization. The objective function developed in this study is linked directly to the notion of fatigue. The method identifies elements that have less than 10% of the fatigue life of the part's critical element. We achieved a weight loss of 5 to 11% by removing the identified elements following the first iteration.

Optimum design of an automotive part under random loading must satisfy two principal conditions: a safe fatigue life and a natural frequency far from the road power spectral density spectrum. Dynamic behaviour of the upper arm suspension was modelled solving the equation of motion. The quasi-static analysis was used in this study as it is highly efficient when the frequency of excitation is below the resonance frequency. The fatigue life was calculated from the multiaxial criterion equivalent to the uniaxial one based on Strain Energy Density. Finally, the critical elements were detected using a Matlab interface developed in previews work.

The objective of this study is to evaluate the potential of light alloy mechanical part use in automobile industry by studying their fatigue life using various parameters such as effect of suspension dynamic, excitation type, geometry and mechanical part weight. The studied part is the lower suspension arm made from 7075-T6 aluminium alloy. The strain density energy approach enables us to compare two same order tensor: the multiaxial and uniaxial cases. The random displacement excitation is obtained analytically from the power spectral density PSD. The force excitation is obtained by a simple normalisation of spectrum displacement. To avoid the use of Newton-Raphson method during the partial fatigue life calculation step in all mesh elements, a Matlab interface to identify the critical elements is developed. The strain energy density (SENER) signal of the critical element is corrected to remove anomalies by WAFO Matlab interface algorithm. Rainflow cycles are extracted using Markov formulation in order to calculate the number of signal repetitions to failure, which is calculated from Miner law.