Experimental and numerical fatigue-based design optimisation of clutch diaphragm spring in the automotive industry

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Date

2019

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Publisher

Inderscience Enterprises

Abstract

In the present study, the fatigue behaviour of a clutch diaphragm spring is investigated experimentally and numerically. Differential evolution optimisation algorithm and response surface methodology are used to define optimal variables of the diaphragm springs under constraints both minimum stress and required clamp load. The required clamp load is checked by the chi-square theorem vs. to target clamp load curve. Ten design variables are considered for creating a design of experiment with two steps, including finger shape optimisation with eight variables, load, and stress optimisation with two variables as the aim of maximum fatigue definition. One hundred seventy-five different designs are analysed numerically. As a result of the optimisation study, the optimum design is provided an endless lifetime subject to the required load, minimum stress, and minimum weight. The optimum design is manufactured and tested experimentally.

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Keywords

Optimum design, Differential evolution algorithm, Diaphragm spring, Fatigue analysis, Gravitational search, Structural design, Algorithms, Evolutionary algorithms, Optimization, Springs (components), Design optimisation, Design variables, Differential evolution, Fatigue behaviour, Minimum weight, Optimal variables, Optimum designs, Response surface methodology, Design of experiments, Engineering, Transportation

Citation

Karaduman, A. vd. (2019). ''Experimental and numerical fatigue-based design optimisation of clutch diaphragm spring in the automotive industry''. International Journal of Vehicle Design, 80(2-4), 330-345.