Solving Maxwell Equations in Hybrid Electrical Vehicle to Optimal Design by Multi-Objective Optimization Algorithms

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10256264" target="_blank" >RIV/61989100:27240/24:10256264 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27730/24:10256264

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/10772457" target="_blank" >https://ieeexplore.ieee.org/document/10772457</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ACCESS.2024.3510537" target="_blank" >10.1109/ACCESS.2024.3510537</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Solving Maxwell Equations in Hybrid Electrical Vehicle to Optimal Design by Multi-Objective Optimization Algorithms

Popis výsledku v původním jazyce

Hybrid Electrical Vehicles (HEVs) have three magnetic field sources: armature winding currents; permanent magnets; and field winding current. To initiate the investigation, the magnetic field distributions due to those sources are obtained. First, Maxwell&apos;s equations need to be solved. Then, the machine is analyzed and the operational indices such as unbalanced magnetic force (UMF) in x- and y direction and instantaneous torque are calculated by using the magnetic flux density distribution. Next, various magnetization patterns, which are presented based on Fourier series, are considered to investigate their influences on the performance of the machine. It is assumed the volume of the machine is determined thanks to thermal considerations. As a result, it is constant so it is maximized average torque instead of torque per volume ratio. After that, the average and ripple of the instantaneous torque are expressed in terms of pole arc to pole pitch ratio by using curve fitting. Finally, the optimal value of average torque and torque ripple are also computed by multi-objective optimization algorithms.

Název v anglickém jazyce

Solving Maxwell Equations in Hybrid Electrical Vehicle to Optimal Design by Multi-Objective Optimization Algorithms

Popis výsledku anglicky

Hybrid Electrical Vehicles (HEVs) have three magnetic field sources: armature winding currents; permanent magnets; and field winding current. To initiate the investigation, the magnetic field distributions due to those sources are obtained. First, Maxwell&apos;s equations need to be solved. Then, the machine is analyzed and the operational indices such as unbalanced magnetic force (UMF) in x- and y direction and instantaneous torque are calculated by using the magnetic flux density distribution. Next, various magnetization patterns, which are presented based on Fourier series, are considered to investigate their influences on the performance of the machine. It is assumed the volume of the machine is determined thanks to thermal considerations. As a result, it is constant so it is maximized average torque instead of torque per volume ratio. After that, the average and ripple of the instantaneous torque are expressed in terms of pole arc to pole pitch ratio by using curve fitting. Finally, the optimal value of average torque and torque ripple are also computed by multi-objective optimization algorithms.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20200 - Electrical engineering, Electronic engineering, Information engineering

Projekt

<a href="/cs/project/TN02000025" target="_blank" >TN02000025: Národní centrum pro energetiku II</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Access

ISSN

2169-3536

e-ISSN

—

Svazek periodika

12

Číslo periodika v rámci svazku

VOLUME 12, 2024

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

8

Strana od-do

183743-183750

Kód UT WoS článku

001380709600045

EID výsledku v databázi Scopus

2-s2.0-85211445689