Mohd Azraai, M. Razman and Priyandoko, Gigih and A. R., Yusoff and M. F. F., Ab Rashid (2014) Optimizing Hysteresis Parameters Of Magneto-Rheological Fluid Damper Using Particle Swarm Optimization. In: Proceedings of the 1st International Conference on Automotive Innovation and Green Energy Vehicle (AiGEV 2014) , 26-27 August 2014 , Swiss Garden Resort & Spa, Kuantan, Pahang. pp. 1-10.. (Unpublished)
PDF
fkm-2014-gigih-OptimizinG_hysteresis_parameters.pdf Restricted to Repository staff only Download (956kB) | Request a copy |
Abstract
Magneto-rheological (MR) fluid has been used in various application as it seen to increase performance from a basic machine into high performance robust machine. A damper that is partnered with MR fluid can increase the operation of vibration suppression in a bigger range compared to a passive shock absorber. MR fluid damper has the property of engaging prediction not just forthcoming behaviour but retracting the preceding measurement. With suitable parameters projected to the hysteresis model, the trajectory for MR fluid damper model can be realize and attain required absorber performance. This study target on implementing Particle Swarm Optimization (PSO) to in searching the optimum parameters value of the hysteresis model for MR fluid damper. Validation by physical experiment and simulation was conducted to enhance the justification of the present model. These performances are measure in force against displacement and force against velocity for the hysteresis model to depict MR fluid damper behaviour. The average marginal error was presented to strengthen the model along with analysis and discussion in deliberating the outcome.
Item Type: | Conference or Workshop Item (Speech) |
---|---|
Subjects: | T Technology > TS Manufactures |
Faculty/Division: | Faculty of Manufacturing Engineering Faculty of Mechanical Engineering |
Depositing User: | Noorul Farina Arifin |
Date Deposited: | 15 Dec 2014 07:08 |
Last Modified: | 27 Jul 2018 02:13 |
URI: | http://umpir.ump.edu.my/id/eprint/7718 |
Download Statistic: | View Download Statistics |
Actions (login required)
View Item |