15 full time employed in teaching and labs Mechatronic profile at UiA characterized by High power Power Mechatronics Dynamic systems Off Shore applications Mechatronic profile at UiA programmes ID: 278537
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Mechatronic group at UiA
15 full
time
employed in teaching and labs.
Mechatronic profile at UiA characterized by:
High power / Power Mechatronics
Dynamic systems
Off Shore applications
Mechatronic profile at UiA, programmes:
3 years B.Sc., since 1988
2 years M.Sc., since 2008
3 years Ph.D., since 2010
Agenda:
- Background
- Modeling and simulation at UiA engng.
- Mathematical challenges
- Conclusions
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14Slide3
Modeling and Simulation at the Engineering MSc educations at UiA
Mechatronics and Renewable Energy
Dedicated course (10SP)
Used in subsequent courses on mechanics, hydraulics, electrical drives, control, instrumentation, industrial information technology, product development.
Used in multidisciplinar project works (across individual courses)
Used extensively in graduate projects
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14Slide4
Simulation
Mainly
time domain simulation
and
numerical methods
Why time domain simulation ?
- Investigate dynamic characteristics
- Avoid or minimize physical testing
- Gain insight into non-linear behavior
- Gain insight into parameters that are difficult to measure physically
- Extensively used in industry to predict and verify design
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14Slide5
Simulation
Mainly
time domain simulation
and
numerical methods
Why time domain simulation ?
- Investigate dynamic characteristics
- Avoid or minimize physical testing
Simulation
- Gain insight into non-linear behavior
- Gain insight into parameters that are difficult to measure physically
- Extensively used in industry to predict and verify design
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14Slide6
Simulation
Mainly time domain simulation and numerical methods
Why numerical methods ?
- Practical problems typically outside the scope of analytical solutions
- Allows for the handling of large scale problems
- Allows for design optimization
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14Slide7
Simple system with no analytical solution
Simple system with no analytical solution
MATHEMATICAL CHALLENGES:
- WHITE BOX MODELING, DIFFERENTIAL EQUATION OF MOTION
- GRAY BOX MODELING, IMPACT WITH WALL
- NUMERICAL SOLUTION, TIME INTEGRATION
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14Slide8
FURTHER MATHEMATICAL CHALLENGES:
- TRIGONOMETRY.
- BLACK BOX MODELING, TIRE MODEL, BUMP IN ROAD.
Simple system with no analytical solution
Simple system with no analytical solution
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14Slide9
MATHEMATICAL CHALLENGE:
FORMULATE DESIGN PROBLEM (INVERSE ANALYSIS)
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14Slide10
MAIN MATHEMATICAL CHALLENGES:
- WHITE BOX MODELING, PURELY PHYSICAL (Newtons 2nd law, Ohms law).
- GRAY BOX MODELING, PARTLY PHYSICAL - PARTLY EMPIRICAL (Parameter identification, friction, impact, damping).
- BLACK BOX MODELING
,
PURELY EMPIRICAL RELATIONSHIPS (Forcing mathematical expressions on observations, measurements, or assumed dependencies).
- SETTING UP NUMERICAL SOLUTIONS (Time integration, nonlinear equations, optimization).
- TRIGONOMETRY.
IN CONCLUSION
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14