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Advanced Parametric Estimation Methods for Permanent Magnet BLDC Motor Under Uncertainties: Quantification of EV Dynamics

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Published in:IEEE Access
Format: Online Article RSS Article
Published: 2026
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container_title IEEE Access
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discipline_display Technology & Engineering
discipline_facet Technology & Engineering
format Online Article
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genre Journal Article
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journal_source_facet IEEE Access
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Advanced Parametric Estimation Methods for Permanent Magnet BLDC Motor Under Uncertainties: Quantification of EV Dynamics
Computer Sciience
Technology & Engineering — Computing
Technology & Engineering
sub_discipline_display Technology & Engineering — Computing
sub_discipline_facet Technology & Engineering — Computing
subject_display Computer Sciience
Technology & Engineering — Computing
Technology & Engineering
Computer Sciience
Technology & Engineering — Computing
Technology & Engineering
subject_facet Computer Sciience
Technology & Engineering — Computing
Technology & Engineering
title Advanced Parametric Estimation Methods for Permanent Magnet BLDC Motor Under Uncertainties: Quantification of EV Dynamics
title_auth Advanced Parametric Estimation Methods for Permanent Magnet BLDC Motor Under Uncertainties: Quantification of EV Dynamics
title_full Advanced Parametric Estimation Methods for Permanent Magnet BLDC Motor Under Uncertainties: Quantification of EV Dynamics
title_fullStr Advanced Parametric Estimation Methods for Permanent Magnet BLDC Motor Under Uncertainties: Quantification of EV Dynamics
title_full_unstemmed Advanced Parametric Estimation Methods for Permanent Magnet BLDC Motor Under Uncertainties: Quantification of EV Dynamics
title_short Advanced Parametric Estimation Methods for Permanent Magnet BLDC Motor Under Uncertainties: Quantification of EV Dynamics
title_sort advanced parametric estimation methods for permanent magnet bldc motor under uncertainties: quantification of ev dynamics
topic Computer Sciience
Technology & Engineering — Computing
Technology & Engineering
url http://ieeexplore.ieee.org/document/11479306