The magnetorheological (MR) control valve is a major component in MR fluid systems to achieve controllable pressure drop or damping characteristics in practice. However, the optimal design of MR control valve is fairly complex due to large extent of design parameters from both magnetic flux generation and mechanical flow characteristics, as well as different requirements or constraints in practical applications. In this paper, the analytical electro-mechanic-magnetic coupling model of the MR control valve with annular-radial flow path is firstly investigated to quantitatively predict the relationship between design parameters and achievable performances such as pressure drop and dynamic range etc.. And then comparison results based on analytical analysis and finite element method are presented to validate the effect model utilized in MR valves. Consequently, a performance-oriented optimization of MR control valves with annular-radial flow path in a non-dimensional design concept is developed through minimizing reciprocal of dynamic range and identifying several optimal internal design parameters subject to predefined constraints under fairly less quantity of combined external design parameters.Finally, the inherent sensitivity of achievable performances with respect to external design parameters is analyzed to provide practical instructions for appropriate specification of the MR control valve.
- Dynamic Systems and Control Division
Model Analysis and Parameters Optimization of Magnetorheological Control Valves
- Views Icon Views
- Share Icon Share
- Search Site
Tang, J, Zhu, X, Yao, B, Wang, Q, & Cao, J. "Model Analysis and Parameters Optimization of Magnetorheological Control Valves." Proceedings of the ASME 2014 Dynamic Systems and Control Conference. Volume 1: Active Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems. San Antonio, Texas, USA. October 22–24, 2014. V001T12A001. ASME. https://doi.org/10.1115/DSCC2014-6104
Download citation file: