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An efficient analysis and optimization method for powertrain mounting systems involving interval uncertainty

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Uncertainty widely exists in the powertrain mounting system of a vehicle. The traditional analysis and optimization methods for powertrain mounting system design are often based on deterministic or random models.… Click to show full abstract

Uncertainty widely exists in the powertrain mounting system of a vehicle. The traditional analysis and optimization methods for powertrain mounting system design are often based on deterministic or random models. In this study, an efficient analysis and optimization method is developed for powertrain mounting system design involving interval uncertainty. In the proposed method, the uncertain parameters of powertrain mounting system are treated as interval variables, and an efficient method called as Chebyshev-Vertex method is developed to fast calculate the lower and upper bounds of the natural frequencies and decoupling ratios of powertrain mounting system. Monte-Carlo method is taken as a reference method to verify the calculation. Then, an optimization model is established based on Chebyshev-Vertex method, in which the interval responses of decoupling ratios are used to build up optimization objective while the interval responses of natural frequencies and decoupling ratios are taken to create optimization constraints. The optimization model of the powertrain mounting system with interval parameters is generally a double-loop nested problem, and it is rather time-consuming on calculation. However, based on Chebyshev-Vertex method, the optimization model can be approximately simplified into a single-loop one and the calculation efficiency is greatly improved. A numerical example is provided to demonstrate the effectiveness of the proposed method on the analysis and optimization design of the powertrain mounting system involving interval uncertainty.

Keywords: powertrain mounting; mounting system; method; analysis optimization

Journal Title: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Year Published: 2019

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