{"id":219,"date":"2018-03-23T10:00:35","date_gmt":"2018-03-23T09:00:35","guid":{"rendered":"http:\/\/templategdr.dii.unipd.it\/?page_id=219"},"modified":"2022-01-11T08:50:29","modified_gmt":"2022-01-11T07:50:29","slug":"smarte-drives","status":"publish","type":"page","link":"https:\/\/research.dii.unipd.it\/edlab\/research\/smarte-drives\/","title":{"rendered":"Smart E-drives"},"content":{"rendered":"<div data-label=\"Content\" data-id=\"content--3\" data-export-id=\"content-7\" data-category=\"content\" class=\"content-7 content-section content-section-spacing\" id=\"content-3\"><div class=\"gridContainer\"> <div class=\"row middle-sm\"><div class=\"col-sm-6 space-bottom-xs\" data-type=\"column\"> <h2 class=\"\">Model Predictive Control<\/h2> <p class=\"\"><span style=\"font-family: Muli, arial, helvetica, sans-serif\">Model Predictive Control is an optimization based control method. It offers several benefits, including fast dynamic responses, straightforward handling of input and output constraints and high scalability to multiple-input multiple-output plants. Advanced computing and more powerful hardwares are quickly bridging the gap between academic research and industrial applications in embedded systems.<\/span><\/p> <a class=\"button color1 square\" href=\"https:\/\/ieeexplore.ieee.org\/search\/searchresult.jsp?queryText=model%20predictive%20control%20silverio%20bolognani&amp;highlight=true&amp;returnFacets=ALL&amp;returnType=SEARCH&amp;matchPubs=true&amp;refinements=Author%3ASilverio%20Bolognani\" target=\"_blank\" data-cp-link=\"1\" data-icon=\"\" rel=\"noopener\">LEARN MORE<\/a><\/div> <div class=\"col-sm-6\" data-type=\"column\"> <img decoding=\"async\" class=\"shadow-large\" src=\"https:\/\/research.dii.unipd.it\/edlab\/wp-content\/uploads\/sites\/29\/2021\/12\/cropped-MPCidea-5.png\" title=\"cropped-MPCidea-5.png\" alt=\"\"><\/div> <\/div><\/div> <\/div><div data-label=\"Content\" data-id=\"content--4\" data-export-id=\"content-8\" data-category=\"content\" class=\"content-8 content-section content-section-spacing\" id=\"content-4\"><div class=\"gridContainer\"> <div class=\"row middle-sm\"><div class=\"col-sm-6 space-bottom-xs space-top-xs\" data-type=\"column\"> <img decoding=\"async\" class=\"shadow-large\" src=\"https:\/\/research.dii.unipd.it\/edlab\/wp-content\/uploads\/sites\/29\/2021\/11\/HF_sensorless_convergence_region.jpg\" title=\"HF_sensorless_convergence_region\" alt=\"\"><\/div> <div class=\"col-sm-6\" data-type=\"column\"><h2 class=\"\">Sensorless control<\/h2> <p class=\"\"><span style=\"font-family: Muli, arial, helvetica, sans-serif\">The position sensor increases the cost and the size of electric drives and, more importantly, it reduces the reliability of the system.&nbsp;<\/span><br><span style=\"font-family: Muli, arial, helvetica, sans-serif\">High speed and low speed drives implement different technologies, namely back-electro motive force observers and high frequency signal injections, respectively. Accurate position estimation requires an in-depth knowledge of the motor, which can be achieved by self-commissioning procedures.<\/span><\/p> <a class=\"button color1 square\" href=\"https:\/\/ieeexplore.ieee.org\/search\/searchresult.jsp?queryText=sensorless%20bolognani&amp;highlight=true&amp;returnFacets=ALL&amp;returnType=SEARCH&amp;matchPubs=true&amp;refinements=Author%3ASilverio%20Bolognani\" target=\"_blank\" data-cp-link=\"1\" data-icon=\"\" rel=\"noopener\">LEARN MORE<\/a><\/div> <\/div><\/div> <\/div><div data-label=\"Content\" data-id=\"content--5\" data-export-id=\"content-7\" data-category=\"content\" class=\"content-7 content-section content-section-spacing\" id=\"content-5\"><div class=\"gridContainer\"> <div class=\"row middle-sm\"><div class=\"col-sm-6 space-bottom-xs\" data-type=\"column\"> <h2 class=\"\">Parameter identification<\/h2> <p class=\"\"><span style=\"font-family: Muli, arial, helvetica, sans-serif\">Model based control techniques have been extensively investigated in the last years due to the outstanding achievable control perfromance. Then, the accurate knowledge of motor parameters is becoming of paramount importance. Many estimation algorithms have been proposed with the aim of identifying the engine under different operating conditions, e.g., during self-commissioning of the inverter, on a laboratory test bench or able to track any changes in parameters during the normal motor operation.<\/span><\/p> <a class=\"button color1 square\" href=\"https:\/\/ieeexplore.ieee.org\/search\/searchresult.jsp?newsearch=true&amp;queryText=ludovico%20ortombina%20identification\" target=\"_blank\" data-cp-link=\"1\" data-icon=\"\" rel=\"noopener\">LEARN MORE<\/a><\/div> <div class=\"col-sm-6\" data-type=\"column\"> <img decoding=\"async\" class=\"shadow-large\" src=\"https:\/\/research.dii.unipd.it\/edlab\/wp-content\/uploads\/sites\/29\/2021\/12\/cropped-Cattura.jpg\" title=\"cropped-Cattura.jpg\" alt=\"\"><\/div> <\/div><\/div> <\/div>","protected":false},"excerpt":{"rendered":"<p>Model Predictive Control Model Predictive Control is an optimization based control method. It offers several benefits, including fast dynamic responses, straightforward handling of input and output constraints and high scalability to multiple-input multiple-output plants. Advanced computing and more powerful hardwares are quickly bridging the gap between academic research and industrial applications in embedded systems. LEARN&hellip; <br \/> <a class=\"read-more\" href=\"https:\/\/research.dii.unipd.it\/edlab\/research\/smarte-drives\/\">Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":213,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"pro\/page-templates\/full-width-page.php","meta":{"footnotes":""},"folder":[],"class_list":["post-219","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Smart E-drives - EDLab<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/research.dii.unipd.it\/edlab\/research\/smarte-drives\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Smart E-drives - EDLab\" \/>\n<meta property=\"og:description\" content=\"Model Predictive Control Model Predictive Control is an optimization based control method. 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