Physical testing as a technique for validation of engineering design methods can be a valuable source of insights not available through simulation alone. Physical testing also helps to ensure that design methods are suitable for design problems with a practical level of detail, and can reveal issues related to interactions not captured by physics-based computer models. Construction of physical and testing of physical prototypes, however, is costly and time consuming so it is not often used when investigating new design methods for complex systems. This gap is addressed through an innovative testbed presented here that can be reconfigured to achieve a range of different prototype design properties, including kinematic behavior and different control system architectures. Thus, a single testbed can be used for validation of numerous design geometries and control system architectures. The testbed presented here is a mechanically and electronically reconfigurable quarter-car suspension testbed with nonlinear elements that is capable of testing a wide range of both optimal and sub-optimal design prototypes using a single piece of equipment. Kinematic suspension properties can be changed in an automated way to reflect different suspension linkage designs, spring and damper properties can be adjusted in real time, and control system design can be changed easily through streamlined software modifications. While the specific case study is focused on development of a reconfigurable system for validation of co-design methods, the concept extends to physical validation using reconfigurable systems for other classes of design methods.
Skip Nav Destination
ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
August 6–9, 2017
Cleveland, Ohio, USA
Conference Sponsors:
- Design Engineering Division
- Computers and Information in Engineering Division
ISBN:
978-0-7918-5812-7
PROCEEDINGS PAPER
Design of a Reconfigurable Dynamic Testbed for Co-Design Method Validation Available to Purchase
Anand P. Deshmukh,
Anand P. Deshmukh
University of Illinois at Urbana-Champaign, Urbana, IL
Search for other works by this author on:
Danny J. Lohan,
Danny J. Lohan
University of Illinois at Urbana-Champaign, Urbana, IL
Search for other works by this author on:
James T. Allison
James T. Allison
University of Illinois at Urbana-Champaign, Urbana, IL
Search for other works by this author on:
Anand P. Deshmukh
University of Illinois at Urbana-Champaign, Urbana, IL
Danny J. Lohan
University of Illinois at Urbana-Champaign, Urbana, IL
James T. Allison
University of Illinois at Urbana-Champaign, Urbana, IL
Paper No:
DETC2017-67319, V02AT03A001; 13 pages
Published Online:
November 3, 2017
Citation
Deshmukh, AP, Lohan, DJ, & Allison, JT. "Design of a Reconfigurable Dynamic Testbed for Co-Design Method Validation." Proceedings of the ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 2A: 43rd Design Automation Conference. Cleveland, Ohio, USA. August 6–9, 2017. V02AT03A001. ASME. https://doi.org/10.1115/DETC2017-67319
Download citation file:
41
Views
Related Proceedings Papers
Exploring Partitioning in Subsystem Prototyping
IDETC-CIE2022
Related Articles
A Novel Transformable Structural Mechanism for Doubly Ruled Hypar Surfaces
J. Mech. Des (March,2015)
Nonlinear Gear-Spring Design for Gravity Balancing of Robotic Manipulators with Variable Payloads: Methods and Comparison
J. Mechanisms Robotics (January,0001)
A Sketch-Based Tool for Analyzing Vibratory Mechanical Systems
J. Mech. Des (October,2008)
Related Chapters
Research and Implementation of Collaborative Development Platform for Complex System
Proceedings of the 2010 International Conference on Mechanical, Industrial, and Manufacturing Technologies (MIMT 2010)
Engineering Design about Electro-Hydraulic Intelligent Control System of Multi Axle Vehicle Suspension
International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)
Hybrid Evolutionary Code Generation Optimizing Both Functional Form and Parameter Values
Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17