{"id":5435,"date":"2023-11-22T13:53:52","date_gmt":"2023-11-22T11:53:52","guid":{"rendered":"https:\/\/howlab-dev.i3a.es\/?p=5435"},"modified":"2023-11-22T13:53:53","modified_gmt":"2023-11-22T11:53:53","slug":"bonifacio-martin-del-brio","status":"publish","type":"post","link":"https:\/\/howlab.i3a.es\/es\/bonifacio-martin-del-brio\/","title":{"rendered":"Bonifacio Mart\u00edn del Br\u00edo"},"content":{"rendered":"<div id=\"pl-gb5435-69dedcc39ee78\"  class=\"panel-layout\" ><div id=\"pg-gb5435-69dedcc39ee78-0\"  class=\"panel-grid panel-has-style\" ><div class=\"siteorigin-panels-stretch panel-row-style panel-row-style-for-gb5435-69dedcc39ee78-0\" data-stretch-type=\"full-width-stretch\" ><div id=\"pgc-gb5435-69dedcc39ee78-0-0\"  class=\"panel-grid-cell\" ><div id=\"panel-gb5435-69dedcc39ee78-0-0-0\" class=\"so-panel widget widget_sow-hero panel-first-child panel-last-child\" data-index=\"0\" ><div\n\t\t\t\n\t\t\tclass=\"so-widget-sow-hero so-widget-sow-hero-default-93415d0e2dbf-5435 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href=\"..\/team\/\">Investigadores<\/a><\/h3>\n<h1 style=\"text-align: center\"><strong>Bonifacio Mart\u00edn del Br\u00edo<\/strong><\/h1>\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<\/li>\n\t\t<\/ul>\t\t\t\t<ol class=\"sow-slider-pagination\">\n\t\t\t\t\t\t\t\t\t\t\t<li><a href=\"#\" data-goto=\"0\" aria-label=\"mostrar diapositiva 1\"><\/a><\/li>\n\t\t\t\t\t\t\t\t\t<\/ol>\n\n\t\t\t\t<div class=\"sow-slide-nav sow-slide-nav-next\">\n\t\t\t\t\t<a href=\"#\" data-goto=\"next\" aria-label=\"diapositiva siguiente\" data-action=\"next\">\n\t\t\t\t\t\t<em class=\"sow-sld-icon-thin-right\"><\/em>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\n\t\t\t\t<div class=\"sow-slide-nav sow-slide-nav-prev\">\n\t\t\t\t\t<a href=\"#\" data-goto=\"previous\" aria-label=\"diapositiva anterior\" data-action=\"prev\">\n\t\t\t\t\t\t<em class=\"sow-sld-icon-thin-left\"><\/em>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div><\/div><\/div><\/div><\/div><\/div><\/div>\n\n<div id=\"pl-gb5435-69dedcc39fca1\"  class=\"panel-layout\" ><div id=\"pg-gb5435-69dedcc39fca1-0\"  class=\"panel-grid panel-no-style\" ><div id=\"pgc-gb5435-69dedcc39fca1-0-0\"  class=\"panel-grid-cell\" ><div id=\"panel-gb5435-69dedcc39fca1-0-0-0\" class=\"so-panel widget widget_sow-image panel-first-child\" data-index=\"0\" ><div\n\t\t\t\n\t\t\tclass=\"so-widget-sow-image so-widget-sow-image-default-8b5b6f678277-5435\"\n\t\t\t\n\t\t>\n<div class=\"sow-image-container\">\n\t\t<img \n\tsrc=\"https:\/\/howlab.i3a.es\/wp-content\/uploads\/2022\/03\/team-300x300.png\" width=\"300\" height=\"300\" srcset=\"https:\/\/howlab.i3a.es\/wp-content\/uploads\/2022\/03\/team-300x300.png 300w, https:\/\/howlab.i3a.es\/wp-content\/uploads\/2022\/03\/team-150x150.png 150w, https:\/\/howlab.i3a.es\/wp-content\/uploads\/2022\/03\/team-12x12.png 12w, https:\/\/howlab.i3a.es\/wp-content\/uploads\/2022\/03\/team.png 512w\" sizes=\"(max-width: 300px) 100vw, 300px\" alt=\"team\" \t\tclass=\"so-widget-image\"\/>\n\t<\/div>\n\n<\/div><\/div><div 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https:\/\/howlab.i3a.es\/wp-content\/uploads\/2020\/10\/linkedin-12x12.png 12w\" sizes=\"auto, (max-width: 37px) 100vw, 37px\" \/>\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"sow-image-grid-image\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"#\"\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\ttarget=\"_blank\" \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\trel=\"noopener noreferrer\" \t\t\t\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"37\" height=\"37\" src=\"https:\/\/howlab.i3a.es\/wp-content\/uploads\/2020\/10\/website.png\" class=\"sow-image-grid-image_html\" alt=\"\" title=\"\" srcset=\"https:\/\/howlab.i3a.es\/wp-content\/uploads\/2020\/10\/website.png 37w, https:\/\/howlab.i3a.es\/wp-content\/uploads\/2020\/10\/website-12x12.png 12w\" sizes=\"auto, (max-width: 37px) 100vw, 37px\" \/>\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"sow-image-grid-image\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"#\"\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\ttarget=\"_blank\" \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\trel=\"noopener noreferrer\" \t\t\t\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"37\" height=\"37\" src=\"https:\/\/howlab.i3a.es\/wp-content\/uploads\/2020\/10\/google-scholar.png\" class=\"sow-image-grid-image_html\" alt=\"\" title=\"\" srcset=\"https:\/\/howlab.i3a.es\/wp-content\/uploads\/2020\/10\/google-scholar.png 37w, https:\/\/howlab.i3a.es\/wp-content\/uploads\/2020\/10\/google-scholar-12x12.png 12w\" sizes=\"auto, (max-width: 37px) 100vw, 37px\" \/>\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n<\/div><\/div><\/div><\/div><div id=\"pgc-gb5435-69dedcc39fca1-0-1\"  class=\"panel-grid-cell\" ><div id=\"panel-gb5435-69dedcc39fca1-0-1-0\" class=\"so-panel widget widget_sow-editor panel-first-child panel-last-child\" data-index=\"2\" ><div\n\t\t\t\n\t\t\tclass=\"so-widget-sow-editor so-widget-sow-editor-base\"\n\t\t\t\n\t\t>\n<div class=\"siteorigin-widget-tinymce textwidget\">\n\t<blockquote>\n<p><em>Professor<\/em><\/p>\n<p><strong>Tel\u00e9fono:<\/strong> +34\u00a0976 762 366<\/p>\n<p><strong>Email:<\/strong> bmb@unizar.es<\/p>\n<p><strong>Address:<\/strong> Dpto. IEC, Edif. Ada Byron, C\/ Mar\u00eda de Luna, 1 50018 (Zaragoza, Spain)<\/p>\n<\/blockquote>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>\n\n<div id=\"pl-gb5435-69dedcc3a18ae\"  class=\"panel-layout\" ><div id=\"pg-gb5435-69dedcc3a18ae-0\"  class=\"panel-grid panel-has-style\" ><div class=\"panel-row-style panel-row-style-for-gb5435-69dedcc3a18ae-0\" ><div id=\"pgc-gb5435-69dedcc3a18ae-0-0\"  class=\"panel-grid-cell\" ><div id=\"panel-gb5435-69dedcc3a18ae-0-0-0\" class=\"so-panel widget widget_sow-headline panel-first-child\" data-index=\"0\" ><div\n\t\t\t\n\t\t\tclass=\"so-widget-sow-headline so-widget-sow-headline-default-c1f9b4bab95c-5435\"\n\t\t\t\n\t\t><div class=\"sow-headline-container\">\n\t\t\t\t\t\t\t<h5 class=\"sow-headline\">\n\t\t\t\t\t\tABOUT ME\t\t\t\t\t\t<\/h5>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"decoration\">\n\t\t\t\t\t\t<div class=\"decoration-inside\"><\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n<\/div><\/div><div id=\"panel-gb5435-69dedcc3a18ae-0-0-1\" class=\"so-panel widget widget_sow-editor panel-last-child\" data-index=\"1\" ><div\n\t\t\t\n\t\t\tclass=\"so-widget-sow-editor so-widget-sow-editor-base\"\n\t\t\t\n\t\t>\n<div class=\"siteorigin-widget-tinymce textwidget\">\n\t<p>Bonifacio Mart\u00edn-del-Br\u00edo es Profesor Titular de Universidad desde 2007. Pertenece al Departamento de Ingenier\u00eda y Comunicaciones de la Universidad de Zaragoza. Ha trabajado siempre en temas relacionados con el procesamiento inteligente de datos, participando en m\u00faltiples proyectos multidisciplinares, aportando en ellos sus conocimientos sobre redes neuronales y machine learning.<\/p>\n<p>Licenciado en Ciencias F\u00edsicas (1989), realiz\u00f3 su doctorado en Ingenier\u00eda Electr\u00f3nica (1994), recibiendo el Premio extraordinario de doctorado de la Universidad de Zaragoza (1995). Para realizar la Tesis doctoral recibi\u00f3 una beca de investigaci\u00f3n competitiva del Gobierno de Arag\u00f3n.<\/p>\n<p>En 1999 consigui\u00f3 una plaza de Profesor Titular de Escuela Universitaria y en 2007 de Profesor Titular de Universidad.<\/p>\n<p>Tiene en la actualidad tres sexenios de investigaci\u00f3n. Ha realizado estancias docentes y de investigaci\u00f3n en la Universidad de Malm\u00f6 (Suecia) y en el Centro de Investigaciones Energ\u00e9ticas, Medioambientales y Tecnol\u00f3gicas CIEMAT (Madrid).<\/p>\n<p>Tiene m\u00e1s de 100 publicaciones en revistas y congresos. Art\u00edculos indexados: 6 Q1, 4 Q2, 3 Q3, 4 Q4, algunas en revistas tan relevantes como IEEE Transactions on Industrial Electronics.<\/p>\n<p>Ha dirigido tres Tesis doctorales.<\/p>\n<p>Ha desarrollado diversas tareas de gesti\u00f3n universitaria, como por ejemplo miembro del Claustro de la Universidad de Zaragoza, Coordinador de \u00c1rea y miembro de la direcci\u00f3n de la Escuela de Ingenier\u00eda y Arquitectura (Coordinador de Grado), entre otras.<\/p>\n<p>Hitos destacables:<\/p>\n<ul>\n<li>Es autor del libro \u201cRedes neuronales y sistemas borrosos&#8221;, que fue prologado por el catedr\u00e1tico de la Universidad de Berkeley Lofti Zadeh, padre de la l\u00f3gica borrosa; editado en Madrid y M\u00e9xico (1997, 2000 y 2006), tiene cientos de citas.<\/li>\n<li>Ha aportado sus conocimientos en machine learning en proyectos relacionados con temas diversos, como la predicci\u00f3n de demanda el\u00e9ctrica (colaboraci\u00f3n con ENDESA), estimaci\u00f3n de oleaje (colaboraci\u00f3n con Puertos del Estado, Intel y Nologin),<\/li>\n<li>Su trabajo pionero (1990\u2019s) de la aplicaci\u00f3n de redes neuronales a la predicci\u00f3n de quiebras bancarias, en colaboraci\u00f3n con el Depto. de Contabilidad y Finanzas de la UZ, cuenta con m\u00e1s de 300 citas (incluyendo el Banco Mundial).<\/li>\n<li>Su trabajo relativo a incluir inteligencia en cocinas de inducci\u00f3n ha sido premiado por el grupo Bosh-Siemens Homeappliances, BSH, y patentado por BSH (world patent 2014P01387ES).<\/li>\n<\/ul>\n<p>Otros m\u00e9ritos relevantes:<\/p>\n<ul>\n<li>Desde 2018 es Director de la C\u00e1tedra SICE de la Universidad de Zaragoza.<\/li>\n<li>2013 Best paper award by the IEEE Industrial Electronics Society (Electrical Machine Technical Committee)<\/li>\n<li>2012 Premio de la C\u00e1tedra BSH.<\/li>\n<li>2001 Premio de la Fundaci\u00f3n 3M \u2013 IV Innovation Awards (\u201cSystem for moving patterns identification&#8221;).<\/li>\n<li>1995 Premio Extraordinario de Doctorado (\u00c1reas T\u00e9cnicas), UZ.<\/li>\n<li>1993 Premio del Seminario Interdisciplinar de la UZ<\/li>\n<li>Miembro permanente de Comit\u00e9s de Congresos: International Work-Conference on Artificial Neural Networks IWANN, TAEE (Tecnolog\u00edas para Ense\u00f1anza de la Electr\u00f3nica) and SAAEI (Seminario Anual Autom\u00e1tica y Electr\u00f3nica Industrial).<\/li>\n<li>Revisor de diversas revistas internacionales.<\/li>\n<\/ul>\n<p><a href=\"https:\/\/janovas.unizar.es\/sideral\/CV\/bonifacio-martin-del-brio\">CV Universidad de Zaragoza<\/a><\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div><div id=\"pg-gb5435-69dedcc3a18ae-1\"  class=\"panel-grid panel-has-style\" ><div class=\"panel-row-style panel-row-style-for-gb5435-69dedcc3a18ae-1\" ><div id=\"pgc-gb5435-69dedcc3a18ae-1-0\"  class=\"panel-grid-cell\" ><div id=\"panel-gb5435-69dedcc3a18ae-1-0-0\" class=\"so-panel widget widget_sow-headline panel-first-child\" data-index=\"2\" 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class=\"teachpress_publication_list\"><h3 class=\"tp_h3\" id=\"tp_h3_2020\">2020<\/h3><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Guill\u00e9n-Asensio, A;  Sanz-Gorrachategui, I;  Pastor-Flores, P;  Artal-Sevil, J S;  Bono, Antonio;  Br\u00edo, Bonifacio Mart\u00edn;  Bernal-Ruiz, C<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('417','tp_links')\" style=\"cursor:pointer;\">Battery state prediction in photovoltaic standalone installations<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">En: <\/span><span class=\"tp_pub_additional_booktitle\">2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER), <\/span><span class=\"tp_pub_additional_pages\">pp. 1-6, <\/span><span class=\"tp_pub_additional_year\">2020<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_417\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('417','tp_abstract')\" title=\"Mostrar resumen\" style=\"cursor:pointer;\">Resumen<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_417\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('417','tp_links')\" title=\"Mostrar enlaces y recursos\" style=\"cursor:pointer;\">Enlaces<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_417\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('417','tp_bibtex')\" title=\"Mostrar entrada BibTeX \" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_417\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{9243111,<br \/>\r\ntitle = {Battery state prediction in photovoltaic standalone installations},<br \/>\r\nauthor = {A Guill\u00e9n-Asensio and I Sanz-Gorrachategui and P Pastor-Flores and J S Artal-Sevil and Antonio Bono and Bonifacio Mart\u00edn Br\u00edo and C Bernal-Ruiz},<br \/>\r\ndoi = {10.1109\/EVER48776.2020.9243111},<br \/>\r\nyear  = {2020},<br \/>\r\ndate = {2020-09-01},<br \/>\r\nbooktitle = {2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)},<br \/>\r\npages = {1-6},<br \/>\r\nabstract = {Effective energy treatment is one of the challenges to which scientists are devoting more interest and resources. Currently, there is a need to optimize the generation of energy by renewable methods and to improve the storage and management of battery cells. One of these emerging lines aims to face the problem of uncertainty that exists in the generation of energy in photovoltaic installations. In this paper, we proposed to use machine learning methods to predict the state (voltage) of the batteries at several days into the future. The results obtained from two recurrent neural networks such as NARX and LSTM are compared, getting good results with both. Two approaches are considered: sample-based prediction and pattern-based forecasting.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('417','tp_bibtex')\">Cerrar<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_417\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Effective energy treatment is one of the challenges to which scientists are devoting more interest and resources. Currently, there is a need to optimize the generation of energy by renewable methods and to improve the storage and management of battery cells. One of these emerging lines aims to face the problem of uncertainty that exists in the generation of energy in photovoltaic installations. In this paper, we proposed to use machine learning methods to predict the state (voltage) of the batteries at several days into the future. The results obtained from two recurrent neural networks such as NARX and LSTM are compared, getting good results with both. Two approaches are considered: sample-based prediction and pattern-based forecasting.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('417','tp_abstract')\">Cerrar<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_417\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1109\/EVER48776.2020.9243111\" title=\"DOI de seguimiento:10.1109\/EVER48776.2020.9243111\" target=\"_blank\">doi:10.1109\/EVER48776.2020.9243111<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('417','tp_links')\">Cerrar<\/a><\/p><\/div><\/div><\/div><h3 class=\"tp_h3\" id=\"tp_h3_2019\">2019<\/h3><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> P\u00e9rez-Cebolla, Francisco Jose;  Martinez-Iturbe, Abelardo;  Br\u00edo, Bonifacio Mart\u00edn;  Bernal-Ruiz, Carlos;  Artal-Sevil, Jes\u00fas Sergio;  Pastor-Flores, Pablo<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('423','tp_links')\" style=\"cursor:pointer;\">Nonlinear Dynamic Equivalent Circuit of a Switched Reluctance Motor Considering Core Losses and Leakage Inductance<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">En: <\/span><span class=\"tp_pub_additional_booktitle\">IECON 2019 &#8211; 45th Annual Conference of the IEEE Industrial Electronics Society, <\/span><span class=\"tp_pub_additional_pages\">pp. 1222-1227, <\/span><span class=\"tp_pub_additional_year\">2019<\/span>, <span class=\"tp_pub_additional_issn\">ISSN: 2577-1647<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_423\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('423','tp_abstract')\" title=\"Mostrar resumen\" style=\"cursor:pointer;\">Resumen<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_423\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('423','tp_links')\" title=\"Mostrar enlaces y recursos\" style=\"cursor:pointer;\">Enlaces<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_423\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('423','tp_bibtex')\" title=\"Mostrar entrada BibTeX \" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_423\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{8927236,<br \/>\r\ntitle = {Nonlinear Dynamic Equivalent Circuit of a Switched Reluctance Motor Considering Core Losses and Leakage Inductance},<br \/>\r\nauthor = {Francisco Jose P\u00e9rez-Cebolla and Abelardo Martinez-Iturbe and Bonifacio Mart\u00edn Br\u00edo and Carlos Bernal-Ruiz and Jes\u00fas Sergio Artal-Sevil and Pablo Pastor-Flores},<br \/>\r\ndoi = {10.1109\/IECON.2019.8927236},<br \/>\r\nissn = {2577-1647},<br \/>\r\nyear  = {2019},<br \/>\r\ndate = {2019-10-01},<br \/>\r\nbooktitle = {IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society},<br \/>\r\nvolume = {1},<br \/>\r\npages = {1222-1227},<br \/>\r\nabstract = {In this paper a nonlinear dynamic lumped circuit model of a switched reluctance motor is proposed. This model includes the effect of core losses and leakage inductance. The parameters of the nonlinear circuit are identified from the experimental flux linkage and phase current. The proposed model, compared to other available static models, allows the coupling between electrical and mechanical phenomena and, therefore, it is suitable for the characterization of the full rotating behaviour of the motor. This nonlinear model is based on the space-state framework and it is implemented in Matlab-Simulink. Model accuracy has been verified at both, constant speed and accelerating; the correct fit between the model and a real switched reluctance machine is shown. The accurate fit of the stator waveform obtained in model simulations with experimental measurements proves both, the accuracy of the proposed model and the correct estimation of its components. All these parameters are non-linearly dependent on the current and the actual rotor position.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('423','tp_bibtex')\">Cerrar<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_423\" style=\"display:none;\"><div class=\"tp_abstract_entry\">In this paper a nonlinear dynamic lumped circuit model of a switched reluctance motor is proposed. This model includes the effect of core losses and leakage inductance. The parameters of the nonlinear circuit are identified from the experimental flux linkage and phase current. The proposed model, compared to other available static models, allows the coupling between electrical and mechanical phenomena and, therefore, it is suitable for the characterization of the full rotating behaviour of the motor. This nonlinear model is based on the space-state framework and it is implemented in Matlab-Simulink. Model accuracy has been verified at both, constant speed and accelerating; the correct fit between the model and a real switched reluctance machine is shown. The accurate fit of the stator waveform obtained in model simulations with experimental measurements proves both, the accuracy of the proposed model and the correct estimation of its components. All these parameters are non-linearly dependent on the current and the actual rotor position.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('423','tp_abstract')\">Cerrar<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_423\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1109\/IECON.2019.8927236\" title=\"DOI de seguimiento:10.1109\/IECON.2019.8927236\" target=\"_blank\">doi:10.1109\/IECON.2019.8927236<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('423','tp_links')\">Cerrar<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Pastor-Flores, Pablo;  Bernal-Ruiz, Carlos;  Sanz-Gorrachategui, Iv\u00e1n;  Bono, Antonio;  Br\u00edo, Bonifacio Mart\u00edn;  Artal-Sevil, Jes\u00fas Sergio;  Perez-Cebolla, Francisco J<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('424','tp_links')\" style=\"cursor:pointer;\">Analysis of Li-ion battery degradation using self-organizing maps<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">En: <\/span><span class=\"tp_pub_additional_booktitle\">IECON 2019 &#8211; 45th Annual Conference of the IEEE Industrial Electronics Society, <\/span><span class=\"tp_pub_additional_pages\">pp. 4525-4530, <\/span><span class=\"tp_pub_additional_year\">2019<\/span>, <span class=\"tp_pub_additional_issn\">ISSN: 2577-1647<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_424\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('424','tp_abstract')\" title=\"Mostrar resumen\" style=\"cursor:pointer;\">Resumen<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_424\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('424','tp_links')\" title=\"Mostrar enlaces y recursos\" style=\"cursor:pointer;\">Enlaces<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_424\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('424','tp_bibtex')\" title=\"Mostrar entrada BibTeX \" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_424\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{8926907,<br \/>\r\ntitle = {Analysis of Li-ion battery degradation using self-organizing maps},<br \/>\r\nauthor = {Pablo Pastor-Flores and Carlos Bernal-Ruiz and Iv\u00e1n Sanz-Gorrachategui and Antonio Bono and Bonifacio Mart\u00edn Br\u00edo and Jes\u00fas Sergio Artal-Sevil and Francisco J Perez-Cebolla},<br \/>\r\ndoi = {10.1109\/IECON.2019.8926907},<br \/>\r\nissn = {2577-1647},<br \/>\r\nyear  = {2019},<br \/>\r\ndate = {2019-10-01},<br \/>\r\nbooktitle = {IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society},<br \/>\r\nvolume = {1},<br \/>\r\npages = {4525-4530},<br \/>\r\nabstract = {This paper proposes a new methodology to identify the different degradation processes of Li-Ion battery cells. The goal of this study is to determine if different degradation factors can be separated by waveform analysis from aged cells with similar remaining capacity. In contrast to other works, the proposed method identifies the past operating conditions in the cell, regardless of the actual State of Health. The methodology is based on a data-driven approach by using a SOM (Self-organizing map), an unsupervised neural network. To verify the hypothesis a SOM has been trained with laboratory data from whole data cycles, to classify cells concerning their degradation path and according to their discharge voltage patterns. Additionally, this new methodology based on the SOM allows discriminating groups of cells with different cycling conditions (based on depth of discharge, ambient temperature and discharge current). This research line is very promising for classification of used cells, not only depending on their current static parameters (capacity, impedance), but also the battery use in their past life. This will allow making predictions of the Remaining Useful Life (RUL) of a battery with greater precision.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('424','tp_bibtex')\">Cerrar<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_424\" style=\"display:none;\"><div class=\"tp_abstract_entry\">This paper proposes a new methodology to identify the different degradation processes of Li-Ion battery cells. The goal of this study is to determine if different degradation factors can be separated by waveform analysis from aged cells with similar remaining capacity. In contrast to other works, the proposed method identifies the past operating conditions in the cell, regardless of the actual State of Health. The methodology is based on a data-driven approach by using a SOM (Self-organizing map), an unsupervised neural network. To verify the hypothesis a SOM has been trained with laboratory data from whole data cycles, to classify cells concerning their degradation path and according to their discharge voltage patterns. Additionally, this new methodology based on the SOM allows discriminating groups of cells with different cycling conditions (based on depth of discharge, ambient temperature and discharge current). This research line is very promising for classification of used cells, not only depending on their current static parameters (capacity, impedance), but also the battery use in their past life. This will allow making predictions of the Remaining Useful Life (RUL) of a battery with greater precision.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('424','tp_abstract')\">Cerrar<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_424\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1109\/IECON.2019.8926907\" title=\"DOI de seguimiento:10.1109\/IECON.2019.8926907\" target=\"_blank\">doi:10.1109\/IECON.2019.8926907<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('424','tp_links')\">Cerrar<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Pastor-Flores, P;  Br\u00edo, Bonifacio Mart\u00edn;  Bono, Antonio;  Ruiz, C Bernal;  Gorrachategui, I Sanz;  P\u00e9rez-Cebolla, FJ<\/p><p class=\"tp_pub_title\">Clasificaci\u00f3n de patrones de envejecimiento en bater\u00edas mediante SOM <span class=\"tp_pub_type tp_  conference\">Conferencia<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_year\">2019<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_428\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('428','tp_bibtex')\" title=\"Mostrar entrada BibTeX \" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_428\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{pastorclasificacion,<br \/>\r\ntitle = {Clasificaci\u00f3n de patrones de envejecimiento en bater\u00edas mediante SOM},<br \/>\r\nauthor = {P Pastor-Flores and Bonifacio Mart\u00edn Br\u00edo and Antonio Bono and C Bernal Ruiz and I Sanz Gorrachategui and FJ P\u00e9rez-Cebolla},<br \/>\r\nyear  = {2019},<br \/>\r\ndate = {2019-07-03},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('428','tp_bibtex')\">Cerrar<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Gorrachategui, Iv\u00e1n Sanz;  Flores, Pablo Pastor;  Bono, Antonio;  Br\u00edo, Bonifacio Mart\u00edn;  Ruiz, Carlos Bernal<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('430','tp_links')\" style=\"cursor:pointer;\">Mapas Auto-Organizados (SOM) para la detecci\u00f3n de envejecimiento en bater\u00edas<\/a> <span class=\"tp_pub_type tp_  article\">Art\u00edculo de revista<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">En: <\/span><span class=\"tp_pub_additional_journal\">Jornada de J\u00f3venes Investigadores del I3A, <\/span><span class=\"tp_pub_additional_volume\">vol. 7, <\/span><span class=\"tp_pub_additional_year\">2019<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_resource_link\"><a id=\"tp_links_sh_430\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('430','tp_links')\" title=\"Mostrar enlaces y recursos\" style=\"cursor:pointer;\">Enlaces<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_430\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('430','tp_bibtex')\" title=\"Mostrar entrada BibTeX \" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_430\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{gorrachategui2019mapas,<br \/>\r\ntitle = {Mapas Auto-Organizados (SOM) para la detecci\u00f3n de envejecimiento en bater\u00edas},<br \/>\r\nauthor = {Iv\u00e1n Sanz Gorrachategui and Pablo Pastor Flores and Antonio Bono and Bonifacio Mart\u00edn Br\u00edo and Carlos Bernal Ruiz},<br \/>\r\ndoi = {10.26754\/jji-i3a.003609},<br \/>\r\nyear  = {2019},<br \/>\r\ndate = {2019-01-01},<br \/>\r\njournal = {Jornada de J\u00f3venes Investigadores del I3A},<br \/>\r\nvolume = {7},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('430','tp_bibtex')\">Cerrar<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_430\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.26754\/jji-i3a.003609\" title=\"DOI de seguimiento:10.26754\/jji-i3a.003609\" target=\"_blank\">doi:10.26754\/jji-i3a.003609<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('430','tp_links')\">Cerrar<\/a><\/p><\/div><\/div><\/div><\/div><div class=\"tablenav\"><div class=\"tablenav-pages\"><span class=\"displaying-num\">90 registros<\/span> <a class=\"page-numbers button disabled\">&laquo;<\/a> <a class=\"page-numbers button disabled\">&lsaquo;<\/a> 1 de 18 <a href=\"https:\/\/howlab.i3a.es\/es\/bonifacio-martin-del-brio\/?limit=2&amp;tgid=&amp;yr=&amp;type=&amp;usr=&amp;auth=&amp;tsr=#tppubs\" title=\"p\u00e1gina siguiente\" class=\"page-numbers button\">&rsaquo;<\/a> <a href=\"https:\/\/howlab.i3a.es\/es\/bonifacio-martin-del-brio\/?limit=18&amp;tgid=&amp;yr=&amp;type=&amp;usr=&amp;auth=&amp;tsr=#tppubs\" title=\"\u00faltima p\u00e1gina\" class=\"page-numbers button\">&raquo;<\/a> <\/div><\/div><\/div>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div>\n\n\n<p><\/p>","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":3600,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[238,239],"tags":[],"class_list":["post-5435","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-reseacher","category-team"],"_links":{"self":[{"href":"https:\/\/howlab.i3a.es\/es\/wp-json\/wp\/v2\/posts\/5435","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/howlab.i3a.es\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/howlab.i3a.es\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/howlab.i3a.es\/es\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/howlab.i3a.es\/es\/wp-json\/wp\/v2\/comments?post=5435"}],"version-history":[{"count":1,"href":"https:\/\/howlab.i3a.es\/es\/wp-json\/wp\/v2\/posts\/5435\/revisions"}],"predecessor-version":[{"id":5436,"href":"https:\/\/howlab.i3a.es\/es\/wp-json\/wp\/v2\/posts\/5435\/revisions\/5436"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/howlab.i3a.es\/es\/wp-json\/wp\/v2\/media\/3600"}],"wp:attachment":[{"href":"https:\/\/howlab.i3a.es\/es\/wp-json\/wp\/v2\/media?parent=5435"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/howlab.i3a.es\/es\/wp-json\/wp\/v2\/categories?post=5435"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/howlab.i3a.es\/es\/wp-json\/wp\/v2\/tags?post=5435"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}