| Naslov: | Computationally efficient multi-objective optimization of an interior permanent magnet synchronous machine using neural networks |
|---|
| Avtorji: | ID Garmut, Mitja (Avtor)
ID Steentjes, Simon (Avtor)
ID Petrun, Martin (Avtor) |
|---|
| Datoteke: |  1-s2.0-S0952197625017555-main.pdf (2,87 MB)
MD5: 7C98EC9FF2E83BCEFDA518A48D63F8B1
|
|---|
| Jezik: | Angleški jezik |
|---|
| Vrsta gradiva: | Članek v reviji |
|---|
| Tipologija: | 1.01 - Izvirni znanstveni članek |
|---|
| Organizacija: | FERI - Fakulteta za elektrotehniko, računalništvo in informatiko
|
|---|
| Opis: | Improving the power density of an interior permanent magnet synchronous machine requires a complex and comprehensive approach that includes electromagnetic and thermal aspects. To achieve that, a multi-objective optimization of the machine’s geometry was performed according to selected key performance indicators by using numerical and analytical models. The primary objective of this research was to create a computationally efficient and accurate alternative to a direct finite element method-based optimization. By integrating artificial neural networks as meta-models, we aimed to demonstrate their performance in comparison to existing State-of-the-Art approaches. The artificial neural network approach achieved a nearly 20-fold reduction compared with the finite element method-based approach in computation time while maintaining accuracy, demonstrating its effectiveness as a computationally efficient alternative. The obtained artificial neural network can also be reused for different optimization scenarios and for iterative fine-tuning, further reducing the computation time. To highlight the advantages and limitations of the proposed approach, a multi-objective optimization scenario was performed, which increased the power-to-mass ratio by 16.5%. |
|---|
| Ključne besede: | interior permanent magnet synchronous machine, artificial neural network, metamodel, multi-objective optimization, finite element method |
|---|
| Status publikacije: | Objavljeno |
|---|
| Verzija publikacije: | Objavljena publikacija |
|---|
| Poslano v recenzijo: | 15.05.2025 |
|---|
| Datum sprejetja članka: | 08.07.2025 |
|---|
| Datum objave: | 25.07.2025 |
|---|
| Založnik: | Elsevier Science |
|---|
| Leto izida: | 2025 |
|---|
| Št. strani: | 15 str. |
|---|
| Številčenje: | vol. 160, [article no.] 111753 |
|---|
| PID: | 20.500.12556/DKUM-94206  |
|---|
| UDK: | 621.31 |
|---|
| COBISS.SI-ID: | 244872195 |
|---|
| DOI: | 10.1016/j.engappai.2025.111753 |
|---|
| ISSN pri članku: | 1873-6769 |
|---|
| Avtorske pravice: | © 2025 The Authors |
|---|
| Datum objave v DKUM: | 08.08.2025 |
|---|
| Število ogledov: | 264 |
|---|
| Število prenosov: | 41 |
|---|
| Metapodatki: |    |
|---|
| Področja: | Ostalo
|
|---|
|
:
|
Kopiraj citat |
|---|
| | | | Skupna ocena: | (0 glasov) |
|---|
| Vaša ocena: | Ocenjevanje je dovoljeno samo prijavljenim uporabnikom. |
|---|
| Objavi na: |  |
|---|
Postavite miškin kazalec na naslov za izpis povzetka. Klik na naslov izpiše
podrobnosti ali sproži prenos. |
