Abstract

Two different alternatives over conventional leaf spring are developed in this work, such as composite and hybrid composite-based leaf springs. In composite type, carbon-epoxy based multi-leaf springs are used and the combination of metal and carbon fiber material is used to develop hybrid composite leaf springs. The outputs namely deflection, maximum stress, and fatigue tests are determined using the finite element analysis approach. Besides, the optimal outcomes are set as the target for hybrid deep neural network-rat swarm optimization based prediction. The findings shows that the hybrid composite leaf spring provides better and enhanced results than the composite leaf spring.

摘要

这项工作开发了两种传统板簧的不同替代方案，例如复合材料板簧和混合复合材料板簧。在复合材料类型中，采用碳-环氧树脂基多片弹簧，并采用金属和碳纤维材料的组合来开发混合复合材料片弹簧。使用有限元分析方法确定输出，即挠度、最大应力和疲劳测试。此外，最优结果被设置为基于混合深度神经网络-大鼠群优化的预测的目标。研究结果表明，混合复合材料板簧比复合材料板簧提供更好且增强的结果。