In this webinar, MathWorks engineers demonstrate how to use optimization algorithms to tune parameters values of SimHydraulics valve models until the simulation results match specifications in manufacturer’s data sheets. Examples of matching flow rate, transient response, and frequency response characteristics will be shown. In addition, the proper structure of efficient valve models and the use of experimental data will be discussed.
This webinar will include demonstrations and explanations to show:
- How to model hydraulic valves in SimHydraulics
- How to parameterize valve models
- Setting up custom optimization problems to automate parameter tuning using Optimization Toolbox and Simulink Design Optimization
- Using experimental data to calculate parameter values
- Using Simulink Control Design to tune frequency response
Directional valves are present in most hydraulic power and control systems. Creating an accurate model of a directional valve often requires interpreting data sheets provided by valve manufacturers. This can be a difficult task, since the data provided by different manufacturers varies. A better understanding of proper model structure and available tools for automatically tuning parameters will help engineers create valve models that match the characteristics described in manufacturer’s data sheets.
The examples used in the webinar and additional examples explained in the white paper are available from the MATLAB Central submission, Hydraulic Valve Parameters From Data Sheets and Experimental Data
Presenter: Steve Miller
Presenter Bio: Steve is responsible for the technical marketing of the physical modeling tools at The MathWorks. Steve joined The MathWorks as an Application Engineer in 2005 and moved to the Design Automation Marketing group at The MathWorks in 2006. Prior to that, Steve worked at Delphi Automotive in Braking Control Systems and at MSC.Software as an Adams specialist, consulting in various capacities at Ford, GM, Hyundai, BMW, and Audi. Steve has a B.S. in Mechanical Engineering from Cornell University and an M.S. in Mechanical Engineering from Stanford University
