Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/92230
PIRA download icon_1.1View/Download Full Text
Title: Applications of adaptive differential evolution to optimize and identify the parameters of power electronics and electric machines
Authors: Yang, Y 
Mao, Y
Issue Date: 2020
Source: In VM Petrova (Ed), Advances in Engineering Research. Volume 33, chapter 2. New York : Nova Science Publishers, 2020.
Abstract: Adaptive Differential Evolution is a derivative of Differential Evolution with adaptive differential weight and crossover rate, which has been evaluated by various benchmark functions. The Adaptive Differential Evolution inherits the merits of conventional Differential Evolution to find global optimal solutions with a faster and smoother convergence than the conventional heuristic algorithm, e.g., conventional Genetic Algorithm. The Adaptive Differential Evolution can find the global optimal solutions more steadily regarding numerous single-objective and multi-objective systems, while the conventional Genetic Algorithm owns the risk of finding local optimal solutions. In this Chapter, the Adaptive Differential Evolution algorithms are compared with conventional Genetic Algorithm in optimizing and identifying the parameters of power electronics systems and electric drives. Simulation and experimental results validate that the Adaptive Differential Evolution can reduce the operating cost of a direct-current microgrid, optimize torque, energy efficiency and torque ripple of an electrical continuously variable transmission system, identify the parameters of a series-series compensated wireless power transfer system, and identify the d-axis inductance, the q-axis inductance and the stator resistance of a dual-rotor flux modulated machine.
Keywords: Adaptive differential evolution
Genetic algorithm
Direct-current microgrid
Electrical continuously variable transmission system
Series-series compensated wireless power transfer system
Dual-rotor flux modulated machine
Publisher: Nova Science Publishers
ISBN: 978-1-53617-002-3
Rights: Copyright © 2020 by Nova Science Publishers, Inc. All rights reserved.
The following publication Yang Y & Mao Y (2020). Applications of Adaptive Differential Evolution to Optimize and Identify the Parameters of Power Electronics and Electric Machines. In VM Petrova (Ed), Advances in Engineering Research. Volume 33, Chapter 2, pp 75-131; Nova Science Publishers. https://novapublishers.com/shop/advances-in-engineering-research-volume-33/
Appears in Collections:Book Chapter

Files in This Item:
File Description SizeFormat 
ChapterID_62547_6x9.pdf2.8 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

3
Citations as of Jun 26, 2022

Downloads

2
Citations as of Jun 26, 2022

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.