Integrated Taguchi method‐assisted polynomial Metamodelling & Genetic Algorithm based optimisation of a surface inset permanent synchronous motor for performance improvement
Abstract In this study, an Integrated Taguchi method‐assisted polynomial Metamodelling & Genetic Algorithm (ITM&GA)‐based optimisation technique is implemented for design optimisation of a surface inset permanent magnet synchronous motor (SIPMSM). The motor geometry is analysed by implementi...
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| Format: | Article |
| Language: | English |
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Wiley
2022-03-01
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| Series: | IET Electrical Systems in Transportation |
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| Online Access: | https://doi.org/10.1049/els2.12035 |
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| author | Monika Verma Madhusudan Singh Mini Sreejeth |
| author_facet | Monika Verma Madhusudan Singh Mini Sreejeth |
| author_sort | Monika Verma |
| collection | DOAJ |
| description | Abstract In this study, an Integrated Taguchi method‐assisted polynomial Metamodelling & Genetic Algorithm (ITM&GA)‐based optimisation technique is implemented for design optimisation of a surface inset permanent magnet synchronous motor (SIPMSM). The motor geometry is analysed by implementing the finite element method for application of the motor in electric compressors of the cooling system of an electric vehicle (EV). The polynomial surrogate model is computed with the help of Taguchi experiments to eliminate the redesigning process of models to reach the optimum values of design parameters and reduce the ambiguity to select the best optimum solution in Traditional Taguchi Method. The root‐mean‐square error test is performed to validate the accuracy of metamodels. The optimum solutions are then converged using the GA technique. The optimum results are compared and presented. Using the ITM&GA technique, the reduction in unwanted ripples in torque and cogging torque along with the improved torque performance of the motor is achieved successfully. The proposed mechanism is effective in obtaining quick and accurate solutions for preliminary designs of the SIPMSM for the electric compressor application in EVs. |
| format | Article |
| id | doaj-art-351c1a8724904212b060ea586d266929 |
| institution | Kabale University |
| issn | 2042-9738 2042-9746 |
| language | English |
| publishDate | 2022-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Electrical Systems in Transportation |
| spelling | doaj-art-351c1a8724904212b060ea586d2669292025-02-03T06:47:34ZengWileyIET Electrical Systems in Transportation2042-97382042-97462022-03-01121263510.1049/els2.12035Integrated Taguchi method‐assisted polynomial Metamodelling & Genetic Algorithm based optimisation of a surface inset permanent synchronous motor for performance improvementMonika Verma0Madhusudan Singh1Mini Sreejeth2Electrical Engineering Department Delhi Technological University New Delhi IndiaElectrical Engineering Department Delhi Technological University New Delhi IndiaElectrical Engineering Department Delhi Technological University New Delhi IndiaAbstract In this study, an Integrated Taguchi method‐assisted polynomial Metamodelling & Genetic Algorithm (ITM&GA)‐based optimisation technique is implemented for design optimisation of a surface inset permanent magnet synchronous motor (SIPMSM). The motor geometry is analysed by implementing the finite element method for application of the motor in electric compressors of the cooling system of an electric vehicle (EV). The polynomial surrogate model is computed with the help of Taguchi experiments to eliminate the redesigning process of models to reach the optimum values of design parameters and reduce the ambiguity to select the best optimum solution in Traditional Taguchi Method. The root‐mean‐square error test is performed to validate the accuracy of metamodels. The optimum solutions are then converged using the GA technique. The optimum results are compared and presented. Using the ITM&GA technique, the reduction in unwanted ripples in torque and cogging torque along with the improved torque performance of the motor is achieved successfully. The proposed mechanism is effective in obtaining quick and accurate solutions for preliminary designs of the SIPMSM for the electric compressor application in EVs.https://doi.org/10.1049/els2.12035electric machinesfinite element analysisgenetic algorithmsoptimisationpermanent magnet motorstorque |
| spellingShingle | Monika Verma Madhusudan Singh Mini Sreejeth Integrated Taguchi method‐assisted polynomial Metamodelling & Genetic Algorithm based optimisation of a surface inset permanent synchronous motor for performance improvement IET Electrical Systems in Transportation electric machines finite element analysis genetic algorithms optimisation permanent magnet motors torque |
| title | Integrated Taguchi method‐assisted polynomial Metamodelling & Genetic Algorithm based optimisation of a surface inset permanent synchronous motor for performance improvement |
| title_full | Integrated Taguchi method‐assisted polynomial Metamodelling & Genetic Algorithm based optimisation of a surface inset permanent synchronous motor for performance improvement |
| title_fullStr | Integrated Taguchi method‐assisted polynomial Metamodelling & Genetic Algorithm based optimisation of a surface inset permanent synchronous motor for performance improvement |
| title_full_unstemmed | Integrated Taguchi method‐assisted polynomial Metamodelling & Genetic Algorithm based optimisation of a surface inset permanent synchronous motor for performance improvement |
| title_short | Integrated Taguchi method‐assisted polynomial Metamodelling & Genetic Algorithm based optimisation of a surface inset permanent synchronous motor for performance improvement |
| title_sort | integrated taguchi method assisted polynomial metamodelling genetic algorithm based optimisation of a surface inset permanent synchronous motor for performance improvement |
| topic | electric machines finite element analysis genetic algorithms optimisation permanent magnet motors torque |
| url | https://doi.org/10.1049/els2.12035 |
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