Optimal design of squirrel cage induction motor using multi-objective Salp Swarm Algorith

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Mousavi Aghdam Seyed Reza; Mansoori Saeede

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF ENERGY MANAGEMENT Year:2019 | Volume:9 | Issue:2 Page(s): 2-17

Download Full-Text

Persian Verion

View:

606

Download:

Cites:

Information Journal Paper

Title

Optimal design of squirrel cage induction motor using multi-objective Salp Swarm Algorith

Author(s)

Mousavi Aghdam Seyed Reza | Mansoori Saeede | Issue Writer Certificate

Keywords

Optimal designQ1

Squirrel cage induction motorQ1

Optimization algorithmQ2

multi-objective Salp swarm algorithmQ1

Abstract

The design of three-phase induction motors is a challenge in electrical engineering. Therefore, new design techniques are continuously provided. Since the design of the induction motors is carried out for different purposes, it is difficult to find a method that can addresses all the targets. Nowadays, the normal methods used to solve multi-objective problems are the optimization strategies. In this paper, the meta-heuristic optimization method has been used to design the Squirrel cage induction motors with the aim of increasing efficiency and reducing costs. In this way, modeling of induction motor is done accurately and to solve this optimization problem, a new method of Multi-objective optimization of the Salp Swarm Algorithm (MSSA) has been provided. This algorithm is inspired by the social behavior of Salps. The proposed method is applied to the data of an induction motor of 2. 5 KW with IE2 efficiency. The results of single-objective and multi-objective optimization exhibit that the design of an induction motor with two objective functions increases the efficiency and reduces the cost. Additionally, the MSSA algorithm is compared with the methods of genetic algorithms for indirect sorting (NSGA-II) and multi-object particle Optimization algorithms (MOPSO). The MSSA algorithm has a convergence rate and a set of optimal response sets which demonstrates a good performance in Optimal design of the induction motor to increase efficiency and reduce its costs.

Cites

No record.

References

No record.

Cite

APA: Copy

Mousavi Aghdam, Seyed Reza, & Mansoori, Saeede. (2019). Optimal design of squirrel cage induction motor using multi-objective Salp Swarm Algorith. JOURNAL OF ENERGY MANAGEMENT, 9(2 ), 2-17. SID. https://sid.ir/paper/223847/en

Vancouver: Copy

Mousavi Aghdam Seyed Reza, Mansoori Saeede. Optimal design of squirrel cage induction motor using multi-objective Salp Swarm Algorith. JOURNAL OF ENERGY MANAGEMENT[Internet]. 2019;9(2 ):2-17. Available from: https://sid.ir/paper/223847/en

IEEE: Copy

Seyed Reza Mousavi Aghdam, and Saeede Mansoori, “Optimal design of squirrel cage induction motor using multi-objective Salp Swarm Algorith,” JOURNAL OF ENERGY MANAGEMENT, vol. 9, no. 2 , pp. 2–17, 2019, [Online]. Available: https://sid.ir/paper/223847/en

Related Journal Papers