Lightweight design method and application of MEWP bracket based on multi-level optimization

Author:

Li Wen12,Wang Jian3,Du Zhanpeng3,Ma Hongfeng2,Zhang Lijie1,Duan Libin3

Affiliation:

1. Hebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control, Yanshan University, Qinhuangdao 066004, China

2. Jiangsu XCMG State Key Laboratory Technology Co., Ltd., Xuzhou 221000, China

3. Institute of Lightweight and Safety of New Energy Vehicle, School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China

Abstract

<abstract> <p>Mobile elevating work platform (MEWP) is a large-scale engineering machinery equipment that transports workers and tools to the designated height for operation. As the key supporting component of MEWP, the bracket simultaneously needs to meet the performances of high stiffness and strength. Furthermore, the mechanical performance of the bracket can be significantly influenced by its cross-sectional shape. However, the optimal cross-sectional shape of bracket is not easily to obtain owing to the lacking of lightweight design method. Thus, a lightweight design method of MEWP bracket based on multi-level optimization is proposed in this paper. Firstly, the multi-case topology optimization model of MEWP bracket is constructed by using the compromise programming method, and the optimal section configuration of MEWP bracket is obtained based on Solid Isotropic Material with Penalization (SIMP). Secondly, the parameterization of the cross-sectional shape of bracket is realized using the mesh deformation technology, and the multi-case optimization mathematical model of the MEWP bracket is established. Then, the cross-sectional shape and gauge of the bracket are optimized using multi-level optimization method. The optimized results show that weight reduction mass is 11.66 kg and the ratio is 52.4% under the premise that the stiffness of the bracket does not decrease. Furthermore, the weight of MEWP bracket optimized by the multi-level optimization method reduced by 1.27 kg compared with single gauge optimization method. Finally, a physical prototype is developed according to the optimization results.</p> </abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

General Mathematics

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