Application of Topology Optimization and Artificial Intelligence Based Evolutionary Algorithm to Minimize the Contribution of the Caliper in Brake Squeal Noise

2024-01-3039

To be published on 09/08/2024

Event
Brake Colloquium & Exhibition - 42nd Annual
Authors Abstract
Content
The squeal noise is one of the critical factors to qualify a disc brake design. It is imperative to be watchful of the unstable natural modes of the brake assembly which triggers squeal. Any design modification for reducing a part's contribution to targeted squeal mode can adversely affect and give rise to new squeal modes. Also, controlling conflicting requirements like mass, strength, and casting manufacturability, further adds up complexity, which increases design iterations and product cost. In view of these challenges, the application of the topological optimizations embedded under an artificial intelligence (AI) driven workflow is explored for a brake assembly. The scope of optimization is kept limited to only the caliper. A complex or unsymmetrical eigenvalue (EV) finite element analysis (FEA) of brake assembly is performed on the baseline design which predicts a squeal mode having 35% strain energy contribution from caliper. As commercial topological optimization tools do not support the unsymmetrical EV analysis, an integrated & automated workflow is developed. In this, the caliper geometry is first topologically optimized for mass, stiffness, casting filling and manufacturing constraints, followed by a complex EV analysis of the optimized geometry. A dummy thermal analysis is included in topology optimization, which equivalently simulates irrotational inviscid fluid flow to improve casting filling performance. The workflow is then parametrized to create several designs and exposed to AI based evolutionary multi-objective optimization algorithm, which facilitates of performing computer driven design iterations rather than human, with an objective of obtaining a caliper geometry having minimum mass, maximum strength, and constraint on caliper's strain energy contribution. The best candidate obtained from 269 design iterations exhibited a significant reduction in caliper's strain energy contribution to 9% in squeal modes, reduction in number of squeal modes while maintaining better strength as compared to baseline design with controlled weight addition.
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Citation
Kumar, D., Inoue, H., Yamamoto, M., Khare, P. et al., "Application of Topology Optimization and Artificial Intelligence Based Evolutionary Algorithm to Minimize the Contribution of the Caliper in Brake Squeal Noise," SAE Technical Paper 2024-01-3039, 2024, .
Additional Details
Publisher
Published
To be published on Sep 8, 2024
Product Code
2024-01-3039
Content Type
Technical Paper
Language
English