Details
Originalsprache | Englisch |
---|---|
Titel des Sammelwerks | Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015 |
Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
Seiten | 518-525 |
Seitenumfang | 8 |
ISBN (elektronisch) | 9781467373173 |
Publikationsstatus | Veröffentlicht - 20 Nov. 2015 |
Veranstaltung | 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015 - Auckland, Neuseeland Dauer: 15 Juni 2015 → 17 Juni 2015 |
Abstract
Positioning tasks of multi-axis servo drive mechanisms typically lead to high energy demands, especially if lossy operating points are applied and/or recuperated break energy, e. g. during deceleration phases, is not effectively reused. A trajectory optimization approach based on the particle swarm algorithm is presented for the adaption of multi-axis positioning tasks during system run-time. Established path planning methods (including the possibility of minimum time motion) are applied, that are adapted by only two parameters per axis and positioning task. In this manner, idle-times that often exist between the motion cycles and/or energy exchange via coupled inverter DC-links are utilized to reduce energy demands and improve system efficiency. In contrast to existing offline trajectory optimization procedures, the method is able to adapt changing motion tasks during system run-time within only few movement cycles. Experimental results prove that, depending on the use case and the chosen optimization constraints, energy losses are effectively reduced, brake chopper dissipation often is even completely avoidable and, hence, total energy demands are distinctly reduced. The approach is applicable to different multi-axis configurations and enables to considerable energy savings without additional hardware invest.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Wirtschaftsingenieurwesen und Fertigungstechnik
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
Ziele für nachhaltige Entwicklung
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Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015. Institute of Electrical and Electronics Engineers Inc., 2015. S. 518-525 7334167.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Concurrent energy efficiency optimization of multi-axis positioning tasks
AU - Hansen, Christian
AU - Eggers, Kai
AU - Kotlarski, Jens
AU - Ortmaier, Tobias
PY - 2015/11/20
Y1 - 2015/11/20
N2 - Positioning tasks of multi-axis servo drive mechanisms typically lead to high energy demands, especially if lossy operating points are applied and/or recuperated break energy, e. g. during deceleration phases, is not effectively reused. A trajectory optimization approach based on the particle swarm algorithm is presented for the adaption of multi-axis positioning tasks during system run-time. Established path planning methods (including the possibility of minimum time motion) are applied, that are adapted by only two parameters per axis and positioning task. In this manner, idle-times that often exist between the motion cycles and/or energy exchange via coupled inverter DC-links are utilized to reduce energy demands and improve system efficiency. In contrast to existing offline trajectory optimization procedures, the method is able to adapt changing motion tasks during system run-time within only few movement cycles. Experimental results prove that, depending on the use case and the chosen optimization constraints, energy losses are effectively reduced, brake chopper dissipation often is even completely avoidable and, hence, total energy demands are distinctly reduced. The approach is applicable to different multi-axis configurations and enables to considerable energy savings without additional hardware invest.
AB - Positioning tasks of multi-axis servo drive mechanisms typically lead to high energy demands, especially if lossy operating points are applied and/or recuperated break energy, e. g. during deceleration phases, is not effectively reused. A trajectory optimization approach based on the particle swarm algorithm is presented for the adaption of multi-axis positioning tasks during system run-time. Established path planning methods (including the possibility of minimum time motion) are applied, that are adapted by only two parameters per axis and positioning task. In this manner, idle-times that often exist between the motion cycles and/or energy exchange via coupled inverter DC-links are utilized to reduce energy demands and improve system efficiency. In contrast to existing offline trajectory optimization procedures, the method is able to adapt changing motion tasks during system run-time within only few movement cycles. Experimental results prove that, depending on the use case and the chosen optimization constraints, energy losses are effectively reduced, brake chopper dissipation often is even completely avoidable and, hence, total energy demands are distinctly reduced. The approach is applicable to different multi-axis configurations and enables to considerable energy savings without additional hardware invest.
UR - http://www.scopus.com/inward/record.url?scp=84960897245&partnerID=8YFLogxK
U2 - 10.1109/iciea.2015.7334167
DO - 10.1109/iciea.2015.7334167
M3 - Conference contribution
AN - SCOPUS:84960897245
SP - 518
EP - 525
BT - Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
Y2 - 15 June 2015 through 17 June 2015
ER -