کنفرانس بین المللی ماشین و محرکه های الکتریکی

| ورود به سامانه | ثبت نام

صفحه اصلی / icemd2024

Minimizing Torque Ripple in Synchronous Reluctance Motors Through Rotor Shape Optimization with Particle Swarm Algorithm

نویسندگان :

Mohammadreza Naeimi¹ Karim Abbaszadeh²

1- Department of Electrical Engineering K. N. Toosi University of Technology 2- Department of Electrical Engineering K. N. Toosi University of Technology

کلمات کلیدی :

Particle Swarm Optimization (PSO)،Rotor Parameters،Flux Barriers،Torque Ripple،Synchronous Reluctance Motor (SynRM)

چکیده :

In this paper, the torque ripple of the synchronous reluctance motor (SynRM) is suppressed by optimizing the geometry of the rotor. A new method based on the particle swarm optimization (PSO) evolutionary algorithm is used to optimize highlighted rotor parameters, such as the size of iron parts and barrier widths along the d and q axes and the angle of the rotor end barriers. At the same time, the insulation factor and rib thickness remain the same during the optimization. The main goal of optimization is to get a pure sinusoidal airgap flux density by manipulating the rotor parameters, resulting in reducing the torque ripple. The Finite element analysis (FEA) and comparative study are conducted for conventional and optimization design to reveal the optimization effect on the motor characteristics such as average torque, torque ripple, and flux density distribution. The results indicated that the torque ripple of the optimized rotor is reduced from 21.81% to 5.02% compared to the conventional design, while the average torque is improved by 0.45 N.m. By considering the identical stator structure for the induction motor (IM) and SynRM, the SynRM with the optimized rotor is fabricated by utilizing the stator of the 1-hp IM motor. Then, the prototype is tested, and experimental results are derived to verify the simulation results. The results indicated a strong correlation between the simulation results and the experimental test results.

لیست مقالات

لیست مقالات بایگانی شده

A Multi-objective and Multi level Optimization of IPMSM Case Study Dynamometer

Ali Amini - MohammadSadegh KhajueeZadeh - Abolfazl Vahedi

Transformative Control Optimization in PMSG-Based Wind Energy Systems: A Deep Reinforcement Learning Approach

Bagher Khadem Hamedani - Masoud Izadi - Nahid Izadi - Amin Azarshab - Ali Najari - Behnam Zaker

A Novel Analytical-Numerical Approach Based on Air-Gap Flux Density Distribution Function for Optimal Design of Permanent Magnet Linear Synchronous Generator

Ehsan Akbari - Milad Samady Shadlu

Design of Axial-Field Flux-Switching PM Modular- Machine by The Approach of Identifying Suppressing Cogging Torque

Fariba Farrokh - Abolfazl Vahedi - Hossein Torkaman - Vahid Zamani Faradonbeh - Mohammad Sadegh Naghash - Mahdi Banejad

Reverse Rotor Pole Construction in Axial-Field Flux-Switchnig PM Machine with High-Torque and Low-Cogging Torque

Hamid Ebrahimi - Hossein Torkaman - Alireza Sohrabzadeh - Alireza Jaferian-Fini - Hamid Javadi

Advancements in Electric Vehicle Charging Optimization: A Survey of Reinforcement Learning Approaches

Mehrshad Shokati - Parisa Mohammadi - Atoosa Amirinian

Thermal Behavior-Informed Inter-Turn Fault Detection of PMSMs using Explainable AI in an Attention-Based Deep Learning Framework

Amir Hossein Baharvand - Sina Hossein Beigi Fard - Amir Hossein Poursaeed - Behrooz Rezaeealam - Meysam Doostizadeh

Modeling and Simulation of a Surface-Mounted Permanent Magnet Motor with Curved-shape Magnet Using Conformal Mapping

Hessam Shafiei Khouzani - Javad Shokrollaho Moghani

A Novel Solid-State Fault Current Limiter Based on AC and DC Reactors for Using in Microgrids

Mehdi Firouzi - Morteza Hesami

A Novel Dual-PM Flux Reversal Machine With Halbach Array Magnets in Stator Slots

Behzad Aslani - Seyed Ehsan Abdollahi - Seyed Asghar Gholamian

ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 40.4.2