An Optimal Rail Vehicle Robust Stability Design Using Imperialist Competition-Inspired Optimization


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The DOI number for this article will be assigned as soon as the final version of the IREME Vol 18, No 1 (2024) issue will be available

Abstract


The industry for railroad vehicles has overcome several obstacles with great success. The largest issue for any engineer with the upcoming launch of fast rail vehicles (FRAV) is actually how to ensure the stability of these trains. In this research, a robust design of FRAV stability with uncertain design variables (DEV) is proposed. In fact, due to the uncertainty of material properties, manufacturing and geometry, it is necessary to integrate uncertainty analysis into the design of FRAV stability, in order to obtain reliable results. This robust FRAV stability aims to both limit the train's sensitivity to the uncertain DEV and increase the critical speed (beyond which the vehicle becomes unstable). This robust design uses the Monte Carlo simulation (MCAS) technique in combination with the multi-objective Colonial competitive algorithm (MOCCA). The effectiveness of this robust design of the FRAV stability is verified by comparing the obtained results with determinist ones and with literature results.
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Keywords


Security; Critical Speed; Optimization; Algorithms; Simulation



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