Details
| Original language | English |
|---|---|
| Article number | 1256 |
| Journal | Applied Sciences (Switzerland) |
| Volume | 8 |
| Issue number | 8 |
| Early online date | 30 Jul 2018 |
| Publication status | Published - Aug 2018 |
Abstract
A multi-objective optimization strategy to find optimal designs of composite multi-rim flywheel rotors is presented. Flywheel energy storage systems have been expanding into applications such as rail and automotive transportation, where the construction volume is limited. Common flywheel rotor optimization approaches for these applications are single-objective, aiming to increase the stored energy or stored energy density. The proposed multi-objective optimization offers more information for decision-makers optimizing three objectives separately: stored energy, cost and productivity. A novel approach to model the manufacturing of multi-rim composite rotors facilitates the consideration of manufacturing cost and time within the optimization. An analytical stress calculation for multi-rim rotors is used, which also takes interference fits and residual stresses into account. Constrained by a failure prediction based on the Maximum Strength, Maximum Strain and Tsai-Wu criterion, the discrete and nonlinear optimization was solved. A hybrid optimization strategy is presented that combines a genetic algorithm with a local improvement executed by a sequential quadratic program. The problem was solved for two rotor geometries used for light rail transit applications showing similar design results as in industry.
Keywords
- Composite rotor, Flywheel energy storage, Manufacturing, Multi-objective optimization
ASJC Scopus subject areas
- Materials Science(all)
- General Materials Science
- Physics and Astronomy(all)
- Instrumentation
- Engineering(all)
- General Engineering
- Chemical Engineering(all)
- Process Chemistry and Technology
- Computer Science(all)
- Computer Science Applications
- Chemical Engineering(all)
- Fluid Flow and Transfer Processes
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In: Applied Sciences (Switzerland), Vol. 8, No. 8, 1256, 08.2018.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Design and Multi-Objective Optimization of Fiber-Reinforced Polymer Composite Flywheel Rotors
AU - Mittelstedt, Marvin
AU - Hansen, Christian
AU - Mertiny, Pierre
N1 - Funding: As a part of the University of Alberta’s Future Energy Systems research initiative, this research was funded in part by the Canada First Research Excellence Fund. Further funding was received from the Jürgen and Irmgard Ulderup Foundation.
PY - 2018/8
Y1 - 2018/8
N2 - A multi-objective optimization strategy to find optimal designs of composite multi-rim flywheel rotors is presented. Flywheel energy storage systems have been expanding into applications such as rail and automotive transportation, where the construction volume is limited. Common flywheel rotor optimization approaches for these applications are single-objective, aiming to increase the stored energy or stored energy density. The proposed multi-objective optimization offers more information for decision-makers optimizing three objectives separately: stored energy, cost and productivity. A novel approach to model the manufacturing of multi-rim composite rotors facilitates the consideration of manufacturing cost and time within the optimization. An analytical stress calculation for multi-rim rotors is used, which also takes interference fits and residual stresses into account. Constrained by a failure prediction based on the Maximum Strength, Maximum Strain and Tsai-Wu criterion, the discrete and nonlinear optimization was solved. A hybrid optimization strategy is presented that combines a genetic algorithm with a local improvement executed by a sequential quadratic program. The problem was solved for two rotor geometries used for light rail transit applications showing similar design results as in industry.
AB - A multi-objective optimization strategy to find optimal designs of composite multi-rim flywheel rotors is presented. Flywheel energy storage systems have been expanding into applications such as rail and automotive transportation, where the construction volume is limited. Common flywheel rotor optimization approaches for these applications are single-objective, aiming to increase the stored energy or stored energy density. The proposed multi-objective optimization offers more information for decision-makers optimizing three objectives separately: stored energy, cost and productivity. A novel approach to model the manufacturing of multi-rim composite rotors facilitates the consideration of manufacturing cost and time within the optimization. An analytical stress calculation for multi-rim rotors is used, which also takes interference fits and residual stresses into account. Constrained by a failure prediction based on the Maximum Strength, Maximum Strain and Tsai-Wu criterion, the discrete and nonlinear optimization was solved. A hybrid optimization strategy is presented that combines a genetic algorithm with a local improvement executed by a sequential quadratic program. The problem was solved for two rotor geometries used for light rail transit applications showing similar design results as in industry.
KW - Composite rotor
KW - Flywheel energy storage
KW - Manufacturing
KW - Multi-objective optimization
UR - http://www.scopus.com/inward/record.url?scp=85051078926&partnerID=8YFLogxK
U2 - 10.3390/app8081256
DO - 10.3390/app8081256
M3 - Article
AN - SCOPUS:85051078926
VL - 8
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
SN - 2076-3417
IS - 8
M1 - 1256
ER -