Key research themes
1. How can electromagnetic principles be leveraged to design passive magnetic shock absorbers with enhanced damping performance?
This research area focuses on the development, analytical modeling, and experimental validation of shock absorbers that exploit electromagnetic phenomena such as eddy currents and magnetic spring effects. Leveraging permanent magnets and conductive elements, these designs seek to create self-powered, cost-effective dampers capable of variable damping forces without external power. This approach advances passive shock absorber technology by integrating magnetic and electromagnetic damping mechanisms, aiming for high-performance and maintenance-free systems suitable for various vibration isolation and vehicle suspension applications.
2. What are the effects of material selection and geometric optimization on the structural and dynamic performance of shock absorber springs in automotive suspension systems?
This theme investigates the design, finite element analysis (FEA), and material optimization of shock absorber springs, particularly helical springs, used in vehicle suspensions. It prioritizes comparative studies of different spring materials under varying load conditions (e.g., single and double riders, bike weight) coupled with modal and structural analyses to determine stress, displacement, and vibrational characteristics. The research aims to identify materials and geometric modifications that optimize strength, durability, and ride comfort while minimizing weight, contributing to safer and more efficient suspension design.
3. How can advanced modeling approaches integrate experimental data to accurately represent nonlinear and semi-active shock absorber behavior, particularly magneto-rheological (MR) dampers?
Research under this theme targets the formulation of precise mathematical and computational models for shock absorbers exhibiting nonlinear, hysteresis, and semi-active control characteristics. Using characteristic force-velocity and force-displacement diagrams derived from experimental test data, researchers develop modeling methodologies that generalize across technologies (passive, semi-active MR, electro-hydraulic). The models often incorporate physical parameters linked to system behavior, enabling high-precision predictions of damping forces influenced by control inputs. Such modeling supports optimized design and control strategies for intelligent suspension systems in automotive and aerospace contexts.