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Multi-objective optimization of vibration characteristics of steering systems based on GA-BP neural networks

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Currently, multi-objective optimization of steering systems has seldom been reported, and this paper adopted GA-BPNN algorithm to optimize the top two order frequencies of steering systems. Firstly, this paper established… Click to show full abstract

Currently, multi-objective optimization of steering systems has seldom been reported, and this paper adopted GA-BPNN algorithm to optimize the top two order frequencies of steering systems. Firstly, this paper established the multi-body dynamics model of the steering system and obtained the random road spectrum of 4 wheels through mathematical model. Results showed that random road spectrums at different wheels were not totally the same and the position and size of peak values were also different. Therefore, the road spectrum of a wheel could not be used to replace the road spectrum of all wheels in multi-body dynamics simulation model. Otherwise, computational results would have a big error. Then, vibration accelerations of the steering wheel at different positions were extracted through the multi-body dynamics model of steering system. Results showed that there were two obvious peak values on the curve of vibration acceleration, and peak frequencies were 48.6 Hz and 65.1 Hz. The finite element model of steering system was established to compute the vibration acceleration, and it was compared with the experimental result. Relative error was controlled within 5 %. It indicated that the finite element model in this paper was reliable. In addition, the computational two order modal frequencies were completely the same with the peak frequencies of vibration acceleration, which proved that the peak values of vibration acceleration were totally caused by the top two order modals. Finally, GA-BPNN algorithm was proposed to optimize the structural thickness of key parts on the steering system, and the optimized result was then compared with that of BPNN and PSO-BPNN. Results showed that the optimization efficiency and result of GA-BPNN were obviously superior to those of other algorithms in the process of optimization and iteration. The optimized parameters were reapplied to the computational model of this paper. Vibration accelerations of the steering system at many positions were extracted to compare with those of the original result. Peak frequencies were significantly improved. In addition, vibration accelerations at most frequency points of the whole frequency band were significantly improved.

Keywords: vibration; steering systems; model; optimization; steering system

Journal Title: Journal of Vibroengineering
Year Published: 2017

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