DESIRED MECHATRONIC PROFILE

MODELINGVIRTUAL PROTOTYPING

EXPERIMENTALWORK

MEHCATRONIC DESIGN

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

Campus Kristiansand

Campus Grimstad

Kristiansand

Grimstad

Agenda:

- Background

- Modeling and simulation at UiA engng.

- Mathematical challenges

- Conclusions

Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14

Modeling and Simulation at the Engineering MSc educations at UiAMechatronics 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 27/5-14

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 27/5-14

University of Agder - Model based analysis and optimization - competencies

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 27/5-14

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 27/5-14

L

m

sinL

g

Simple system with no analytical solution

L

m

sinL

g

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 27/5-14

FURTHER MATHEMATICAL CHALLENGES:- TRIGONOMETRY.- BLACK BOX MODELING, TIRE MODEL, BUMP IN ROAD.

x

20

y

y( t 0 ) 1.2 m x

0x

y

sh

A B

L

Simple system with no analytical solution Simple system with no analytical solution

0

0 0 0

0

0

2( ) 1 sin

2 4

0

s

x x

h Lh x x x x x x L

L

x x L

Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14

MATHEMATICAL CHALLENGE:FORMULATE DESIGN PROBLEM (INVERSE ANALYSIS)

Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14

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