Use este identificador para citar ou linkar para este item:
http://repositorio.ufc.br/handle/riufc/68319
Tipo: | Artigo de Periódico |
Título: | Automatic characterization system of switched reluctance machines and nonlinear modeling by interpolation using smoothing splines |
Autor(es): | Barros, Tárcio André dos Santos Santos Neto, Pedro José dos Paula, Marcelo Vinicius de Moreira, Adson Bezerra Nascimento Filho, Paulo Sérgio Ruppert Filho, Ernesto |
Palavras-chave: | Switched reluctance machine;Magnetization curves;Smoothing splines |
Data do documento: | 2018 |
Instituição/Editor/Publicador: | IEEE access |
Citação: | MOREIRA, A. B. et al. Automatic characterization system of switched reluctance machines and nonlinear modeling by interpolation using smoothing splines. IEEE access, vol. 6, 2018. DOI: 10.1109/ACCESS.2018.2825607 |
Abstract: | This paper presents a high resolution automatic system capable of performing magnetic characterization tests and obtaining the data needed to conduct reliable models for switched reluctance machines (SRM). In addition, the detailed description of the instrumentation system performed in this paper has as contribution the study of mathematical interpolation techniques for the treatment process of test data to obtain a nonlinear model based on lookup tables. It was observed that the commonly used polynomial regressions may cause inaccuracies in the final characteristics of the model data. Thereat, smoothing splines were applied, which results in more accurate and consistent results for the SRMs operation. Thus, it is possible to obtain control projects, optimization systems and advanced studies through computer simulations. Simulation and experimental results have proved the efficiency of the system and have confirmed the importance of achieving real curves when accurate models of a SRM are needed. |
URI: | http://www.repositorio.ufc.br/handle/riufc/68319 |
ISSN: | 2169-3536 |
Tipo de Acesso: | Acesso Aberto |
Aparece nas coleções: | DEEL - Artigos publicados em revista científica |
Arquivos associados a este item:
Arquivo | Descrição | Tamanho | Formato | |
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2018_art_abmoreira.pdf | 2,7 MB | Adobe PDF | Visualizar/Abrir |
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