面向轮胎性能的非气动独特防刺胎系统辐条设计拓扑优化

IF 0.5 Q4 TRANSPORTATION SCIENCE & TECHNOLOGY SAE International Journal of Passenger Vehicle Systems Pub Date : 1900-01-01 DOI:10.4271/15-17-01-0001
Priyankkumar Dhrangdhariya, S. Maiti, B. Rai
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引用次数: 0

摘要

非充气轮胎(NPTs)由于其不发生打孔问题、不需要空气维护、滚动阻力小、减震效果好、提高乘客舒适度等优点而得到广泛应用。它有各种各样的应用,如推土机,行星漫游者,爬楼梯车,等等。最近,独特的防穿刺轮胎系统(UPTIS) NPT已被引入乘用车领域。NPT-UPTIS的辐条设计对轮胎的整体工作性能有重要影响。优化轮胎性能对消费者和原始设备制造商(oem)来说是一个至关重要的因素。因此,为了优化NPT-UPTIS轮辐的轮辐设计,采用解析方程的形式描述了轮辐轮廓的上下曲线。生成式设计概念已被引入创建约50,000辐条轮廓。建立了NPT-UPTIS轮辐刚度和抗损伤性能的有限元模型。采用有限元方法对商用NPT-Tweel的试验垂直刚度进行了验证,平均精度超过95%。在机器学习回归模型的帮助下,对生成的设计的刚度和抗损伤性能进行了预测,该模型是在200个这样的设计的有限元结果上训练的。根据不同级别的刚度和抗损伤性能,这50,000个生成的设计被分为四个不同的类别。在本研究中,从每个类别中选择一个优化设计,并通过三维有限元模拟验证其性能。研究发现,所建议的拓扑优化方法可以有效地生成具有±30%刚度的UPTIS辐条设计,与初始参考设计相比,其抗损伤性能提高了17%、40%和56%。
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Topological Optimization of Non-Pneumatic Unique Puncture-Proof Tire System Spoke Design for Tire Performance
Non-pneumatic tires (NPTs) have been widely used due to their advantages of no occurrence of puncture-related problems, no need of air maintenance, low rolling resistance, and improvement of passenger comfort due to its better shock absorption. It has a variety of applications as in earthmovers, planetary rover, stair-climbing vehicles, and the like. Recently, the unique puncture-proof tire system (UPTIS) NPT has been introduced for passenger vehicles segment. The spoke design of NPT-UPTIS has a significant effect on the overall working performance of tire. Optimized tire performance is a crucial factor for consumers and original equipment manufacturers (OEMs). Hence to optimize the spoke design of NPT-UPTIS spoke, the top and bottom curve of spoke profile have been described in the form of analytical equations. A generative design concept has been introduced to create around 50,000 spoke profiles. Finite element model (FEM) model is developed to evaluate the stiffness and damage-resisting performance of NPT-UPTIS spoke. The FEM methodology has also been validated with average accuracy of more than 95% for experimental vertical stiffness for commercial NPT-Tweel. The stiffness and damage-resisting performance of generated designs have been predicted with the help of machine learning regression models, which were trained on the FEM results of 200 such designs. These 50,000 generated designs have been categorized in four different categories based on different level of stiffness and damage resistance performance. In this study, one optimized design from each category has been selected and their performance have been validated with 3D FEM simulation. It has been found that the suggested topology optimization approach is efficient to generate UPTIS spoke designs with having ±30% stiffness with 17%, 40%, and 56% more damage resistance performances with respect to the starting reference design.
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