Sichuan Provincial Key Laboratory of Process Equipment and Control Engineering

Zigong, China

Sichuan Provincial Key Laboratory of Process Equipment and Control Engineering

Zigong, China
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Zhou J.,University of Sichuan | Zhou J.,Sichuan Provincial Key Laboratory of Process Equipment and Control Engineering | Wang C.,University of Sichuan | Wang C.,Sichuan Provincial Key Laboratory of Process Equipment and Control Engineering | Zhu J.,Beijing Institute of Technology
Mathematical and Computational Applications | Year: 2016

The weight coefficients of the diaphragm spring depend on experiences in the traditional optimization. However, this method not only cannot guarantee the optimal solution but it is also not universal. Therefore, a new optimization target function is proposed. The new function takes the minimum of average compress force changing of the spring and the minimum force of the separation as total objectives. Based on the optimization function, the result of the clutch diaphragm spring in a car is analyzed by the non-dominated sorting genetic algorithm (NSGA-II) and the solution set of Pareto is obtained. The results show that the pressing force of the diaphragm spring is improved by 4.09% by the new algorithm and the steering separation force is improved by 6.55%, which has better stability and steering portability. The problem of the weight coefficient in the traditional empirical design is solved. The pressing force of the optimized diaphragm spring varied slightly during the abrasion range of the friction film, and the manipulation became remarkably light. © 2016 by the authors; licensee MDPI.

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