Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2020 IEEE International Conference on Mechatronics and Automation |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 990-995 |
| Number of pages | 6 |
| ISBN (electronic) | 978-1-7281-6416-8 |
| ISBN (print) | 978-1-7281-6417-5 |
| Publication status | Published - 2020 |
| Event | 17th IEEE International Conference on Mechatronics and Automation, ICMA 2020 - Beijing, China Duration: 13 Oct 2020 → 16 Oct 2020 |
Publication series
| Name | IEEE International Conference on Mechatronics and Automation |
|---|---|
| ISSN (Print) | 2152-7431 |
| ISSN (electronic) | 2152-744X |
Abstract
Thermal modeling using finite element analysis with spatially fine discretization frequently leads to large scaled state space systems of differential equations. Hence, model order reduction can be inevitable to meet real-time requirements e.g. in model-based process control. In addition to large system orders, dealing with temperature-dependent boundary conditions, including convection and thermal radiation, when reducing the model order is challenging, since classical projection based reduction approaches are merely applicable for linear systems. Thus, the system description is divided into a dominant linear part and an additive piece-wise constant function, which is frequently updated. Reduction methods are compared regarding considered cooling model whereby discrepancies between the approximation of transmission behaviour and overall state reconstruction of initial and forced dynamic are elaborated. Finally suitable reduction strategies facing corresponding purposes are proposed. For a good approximation in transfer behaviour, Iterative Rational Krylov Algorithm for initial dynamic and Balanced Truncation for external load dynamic are proper choices. If an overall state reconstruction is required, Tangential Interpolation and Rational Krylov are favourable.
Keywords
- LPV-Systems, Model Order Reduction, State-Dependent Boundary Conditions, Thermal Systems
ASJC Scopus subject areas
- Computer Science(all)
- Artificial Intelligence
- Computer Science(all)
- Computer Networks and Communications
- Computer Science(all)
- Computer Science Applications
- Engineering(all)
- Electrical and Electronic Engineering
- Engineering(all)
- Mechanical Engineering
- Mathematics(all)
- Control and Optimization
Cite this
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- Apa
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- BibTeX
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Proceedings of 2020 IEEE International Conference on Mechatronics and Automation. Institute of Electrical and Electronics Engineers Inc., 2020. p. 990-995 (IEEE International Conference on Mechatronics and Automation).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Comparative Study of Model Order Reduction for Linear Parameter-Variant Thermal Systems
AU - Zeipel, Henrik
AU - Frank, Tobias
AU - Wielitzka, Mark
AU - Ortmaier, Tobias
PY - 2020
Y1 - 2020
N2 - Thermal modeling using finite element analysis with spatially fine discretization frequently leads to large scaled state space systems of differential equations. Hence, model order reduction can be inevitable to meet real-time requirements e.g. in model-based process control. In addition to large system orders, dealing with temperature-dependent boundary conditions, including convection and thermal radiation, when reducing the model order is challenging, since classical projection based reduction approaches are merely applicable for linear systems. Thus, the system description is divided into a dominant linear part and an additive piece-wise constant function, which is frequently updated. Reduction methods are compared regarding considered cooling model whereby discrepancies between the approximation of transmission behaviour and overall state reconstruction of initial and forced dynamic are elaborated. Finally suitable reduction strategies facing corresponding purposes are proposed. For a good approximation in transfer behaviour, Iterative Rational Krylov Algorithm for initial dynamic and Balanced Truncation for external load dynamic are proper choices. If an overall state reconstruction is required, Tangential Interpolation and Rational Krylov are favourable.
AB - Thermal modeling using finite element analysis with spatially fine discretization frequently leads to large scaled state space systems of differential equations. Hence, model order reduction can be inevitable to meet real-time requirements e.g. in model-based process control. In addition to large system orders, dealing with temperature-dependent boundary conditions, including convection and thermal radiation, when reducing the model order is challenging, since classical projection based reduction approaches are merely applicable for linear systems. Thus, the system description is divided into a dominant linear part and an additive piece-wise constant function, which is frequently updated. Reduction methods are compared regarding considered cooling model whereby discrepancies between the approximation of transmission behaviour and overall state reconstruction of initial and forced dynamic are elaborated. Finally suitable reduction strategies facing corresponding purposes are proposed. For a good approximation in transfer behaviour, Iterative Rational Krylov Algorithm for initial dynamic and Balanced Truncation for external load dynamic are proper choices. If an overall state reconstruction is required, Tangential Interpolation and Rational Krylov are favourable.
KW - LPV-Systems
KW - Model Order Reduction
KW - State-Dependent Boundary Conditions
KW - Thermal Systems
UR - http://www.scopus.com/inward/record.url?scp=85096522073&partnerID=8YFLogxK
U2 - 10.1109/ICMA49215.2020.9233541
DO - 10.1109/ICMA49215.2020.9233541
M3 - Conference contribution
AN - SCOPUS:85096522073
SN - 978-1-7281-6417-5
T3 - IEEE International Conference on Mechatronics and Automation
SP - 990
EP - 995
BT - Proceedings of 2020 IEEE International Conference on Mechatronics and Automation
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th IEEE International Conference on Mechatronics and Automation, ICMA 2020
Y2 - 13 October 2020 through 16 October 2020
ER -