Fatigue Based Optimization of Cast Iron Bracket Depending On Proving Ground Data

2014-01-2309

09/30/2014

Event
SAE 2014 Commercial Vehicle Engineering Congress
Authors Abstract
Content
Nowadays, a lightweight component design plays a significant role in both cost of a vehicle and fuel economy in competitive heavy duty truck industry. This paper describes the optimization study of an Anti-Roll Bar (ARB) bracket used in a heavy duty truck. ARB system is used to avoid rolling of a vehicle. In order to measure real forces acting on ARB links, calibration study is performed in laboratory conditions. According to this study, measured strains are correlated with theoretical strain-force curve. After the correlation study, fatigue based topology optimization is made on ARB cast iron bracket according to correlated Road Load Data (RLD) which is performed at Proving Ground. Most of the optimization studies in the literature depend on maximum static loading condition. However, many components or structures in the industry subjected to fluctuating loads when they are in service condition. Small loads in a fluctuating load domain may cause potential danger in the design because there will be damage accumulation on the part when those loads are repeated. The failure of components under cyclic load is called fatigue which plays important role in the design. In this study packaging volume, different road profiles, fatigue cycle limits, material of bracket and manufacturing constraints are taken into consideration. Compared with initial design, the weight of ARB bracket is reduced by 25% while keeping the fatigue life in an acceptable level.
Meta TagsDetails
DOI
https://doi.org/10.4271/2014-01-2309
Pages
8
Citation
Kosar, F., Yegin, M., Dogru, O., and Akarsu, C., "Fatigue Based Optimization of Cast Iron Bracket Depending On Proving Ground Data," SAE Technical Paper 2014-01-2309, 2014, https://doi.org/10.4271/2014-01-2309.
Additional Details
Publisher
Published
Sep 30, 2014
Product Code
2014-01-2309
Content Type
Technical Paper
Language
English