Multi-objective structural optimization of hub unit bearing using response surface methodology and genetic algorithm

作者：Lu Xiaohui^*; Xie Xiaopeng

来源：Journal of Advanced Mechanical Design, Systems and Manufacturing, 2014, 8(3): 14-00019.

DOI：10.1299/jamdsm.2014jamdsm0035

• Hub unit bearing
• Uniform design
• Response surface methodology
• Genetic algorithm
• Multi-objective optimization

Hub unit bearings are key components in automobiles for carrying load and accurate piloting. The hub unit bearing must be of a smaller size and lighter weight to meet the requirements of automobile for higher fuel efficiency, improved ease of movement and freedom in sizing of peripheral components. Reduction of such basic performance as strength, stiffness or the like due to reduced weight must be avoided. In this study, an efficient lightweight of hub unit bearing is investigated by integrating finite element (FE) analysis, uniform design (UD), response surface methodology (RSM), and genetic algorithm (GA). The FE analysis of the hub unit bearing is conducted, its validity is verified by the test of moment rigidity. A multi-objective optimization model with constraint functions is established by RSM according to FE analysis results from the samples of UD. The exterior point penalty function method is used to convert the constrained optimization problem into an unconstrained optimization problem. The normalized weighting method is used to transform the multi-objective optimization problem into a single-objective problem. By ensuring that the maximum equivalent stress is below the yield limit stress and that the rigidity hardly changes, the optimization model is interfaced with an effective GA to match the lightweight target.

• 出版日期2014
• 单位华南理工大学