Experimental statistical method predicting AC losses on random windings and PWM effect evaluation
Nowadays, one of the challenges in transport electrification is the reduction of the components’ size and weight in order to improve the power density. This is often achieved by designing electrical machines with higher rotational speeds and excitation frequencies. In addition, the converter needs t...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/64166/ |
| _version_ | 1848800096738607104 |
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| author | Preci, Eraldo Valente, Giorgio Galassini, Alessandro Yuan, Xin Degano, Michele Gerada, David Buticchi, Giampaolo Gerada, Chris |
| author_facet | Preci, Eraldo Valente, Giorgio Galassini, Alessandro Yuan, Xin Degano, Michele Gerada, David Buticchi, Giampaolo Gerada, Chris |
| author_sort | Preci, Eraldo |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Nowadays, one of the challenges in transport electrification is the reduction of the components’ size and weight in order to improve the power density. This is often achieved by designing electrical machines with higher rotational speeds and excitation frequencies. In addition, the converter needs to control the machine over a wide speed range given by the mission profile. Therefore, copper losses can significantly increase due to the combination of high frequency excitation and the harmonics introduced by the converter .The winding arrangement design plays a key role in the minimization of the copper losses. This paper presents an in depth study on AC losses in random windings for high frequency motor applications. An analytical method is compared against 2-D Finite Element (FE) simulation results. These are then compared to experimental measurements taken on a custom motorette. Importantly, in order to take into account the random positions of each strand within the machine slots, an Experimental Statistic Method (ESM) is proposed. The ESM allows to define the probability distribution which is useful to evaluate the winding copper losses at the design stage. The contribution of the Pulse Width Modulation (PWM) effect is also considered and experimentally evaluated. IEEE |
| first_indexed | 2025-11-14T20:46:08Z |
| format | Article |
| id | nottingham-64166 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:46:08Z |
| publishDate | 2020 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-641662020-12-28T08:07:26Z https://eprints.nottingham.ac.uk/64166/ Experimental statistical method predicting AC losses on random windings and PWM effect evaluation Preci, Eraldo Valente, Giorgio Galassini, Alessandro Yuan, Xin Degano, Michele Gerada, David Buticchi, Giampaolo Gerada, Chris Nowadays, one of the challenges in transport electrification is the reduction of the components’ size and weight in order to improve the power density. This is often achieved by designing electrical machines with higher rotational speeds and excitation frequencies. In addition, the converter needs to control the machine over a wide speed range given by the mission profile. Therefore, copper losses can significantly increase due to the combination of high frequency excitation and the harmonics introduced by the converter .The winding arrangement design plays a key role in the minimization of the copper losses. This paper presents an in depth study on AC losses in random windings for high frequency motor applications. An analytical method is compared against 2-D Finite Element (FE) simulation results. These are then compared to experimental measurements taken on a custom motorette. Importantly, in order to take into account the random positions of each strand within the machine slots, an Experimental Statistic Method (ESM) is proposed. The ESM allows to define the probability distribution which is useful to evaluate the winding copper losses at the design stage. The contribution of the Pulse Width Modulation (PWM) effect is also considered and experimentally evaluated. IEEE 2020-11-24 Article PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/64166/1/ilovepdf_merged%20%284%29.pdf Preci, Eraldo, Valente, Giorgio, Galassini, Alessandro, Yuan, Xin, Degano, Michele, Gerada, David, Buticchi, Giampaolo and Gerada, Chris (2020) Experimental statistical method predicting AC losses on random windings and PWM effect evaluation. IEEE Transactions on Energy Conversion . p. 1. ISSN 0885-8969 Random windings; AC losses evaluation; high frequency; PWM effects; Electrical Machines. http://dx.doi.org/10.1109/TEC.2020.3040265 doi:10.1109/TEC.2020.3040265 doi:10.1109/TEC.2020.3040265 |
| spellingShingle | Random windings; AC losses evaluation; high frequency; PWM effects; Electrical Machines. Preci, Eraldo Valente, Giorgio Galassini, Alessandro Yuan, Xin Degano, Michele Gerada, David Buticchi, Giampaolo Gerada, Chris Experimental statistical method predicting AC losses on random windings and PWM effect evaluation |
| title | Experimental statistical method predicting AC losses on random windings and PWM effect evaluation |
| title_full | Experimental statistical method predicting AC losses on random windings and PWM effect evaluation |
| title_fullStr | Experimental statistical method predicting AC losses on random windings and PWM effect evaluation |
| title_full_unstemmed | Experimental statistical method predicting AC losses on random windings and PWM effect evaluation |
| title_short | Experimental statistical method predicting AC losses on random windings and PWM effect evaluation |
| title_sort | experimental statistical method predicting ac losses on random windings and pwm effect evaluation |
| topic | Random windings; AC losses evaluation; high frequency; PWM effects; Electrical Machines. |
| url | https://eprints.nottingham.ac.uk/64166/ https://eprints.nottingham.ac.uk/64166/ https://eprints.nottingham.ac.uk/64166/ |