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[\/et_pb_text][et_pb_image src=”https:\/\/research.ece.ncsu.edu\/wp-content\/uploads\/sites\/3\/2020\/10\/co-estimation-1-1.png” title_text=”co-estimation 1″ align=”center” align_tablet=”center” align_phone=”” align_last_edited=”on|desktop” admin_label=”Image” _builder_version=”4.6.6″ max_width=”600px” use_border_color=”off” border_color=”#ffffff” border_style=”solid” animation=”off” sticky=”off” always_center_on_mobile=”on”] [\/et_pb_image][et_pb_text admin_label=”content” _builder_version=”4.6.6″ text_font_size=”18″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” use_border_color=”off” border_color=”#ffffff” border_style=”solid”]<\/p>\n
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Real-time estimation of the state of charge (SOC) of the battery is a crucial need in the growing fields of plug-in hybrid electric vehicles and smart grid applications. The SOC estimation accuracy depends on the accuracy of the model used to describe the characteristics of the battery. To accurately estimate the SOC of the battery, a Co-Estimation algorithm is proposed. The Co-Estimation algorithm is developed based on a resistance\u2013capacitance (RC)-equivalent circuit model to model the battery dynamics. Considering the parameters of the battery model are functions of the SOC, C-rate, temperature, and aging, the Co-Estimation algorithm adopts an adaptive online parameter-identification algorithm to identify and update the model\u2019s parameters as they change. We also deployed a piecewise linearized mapping of the VOC\u2013SOC curve along with continuously updating the parameters to accurately represent all of the battery\u2019s static and dynamic characteristics. Using this adaptive structure, we design an observer based on the updating model to estimate the SOC as one of the states of the battery model.<\/span><\/p>\n Sponsor:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_4,1_4,1_4,1_4″ _builder_version=”4.6.6″ _module_preset=”default”][et_pb_column type=”1_4″ _builder_version=”4.6.6″ _module_preset=”default”][et_pb_blurb image=”https:\/\/research.ece.ncsu.edu\/wp-content\/uploads\/sites\/3\/2019\/03\/ford.png” _builder_version=”4.6.6″ _module_preset=”default”][\/et_pb_blurb][et_pb_blurb image=”https:\/\/research.ece.ncsu.edu\/wp-content\/uploads\/sites\/3\/2019\/03\/samsung.png” _builder_version=”4.6.6″ _module_preset=”default”][\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_4″ _builder_version=”4.6.6″ _module_preset=”default”][et_pb_blurb image=”https:\/\/research.ece.ncsu.edu\/wp-content\/uploads\/sites\/3\/2019\/09\/Duke-Energy-Logo.jpg” _builder_version=”4.6.6″ _module_preset=”default”][\/et_pb_blurb][et_pb_blurb image=”https:\/\/research.ece.ncsu.edu\/wp-content\/uploads\/sites\/3\/2020\/10\/6-300×180.png” _builder_version=”4.6.6″ _module_preset=”default”][\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_4″ _builder_version=”4.6.6″ _module_preset=”default”][et_pb_blurb image=”https:\/\/research.ece.ncsu.edu\/wp-content\/uploads\/sites\/3\/2019\/03\/ncemc.jpeg” _builder_version=”4.6.6″ _module_preset=”default” hover_enabled=”0″ title_text=”North Carolinas Electric Cooperatives Logo” sticky_enabled=”0″][\/et_pb_blurb][et_pb_blurb image=”https:\/\/research.ece.ncsu.edu\/wp-content\/uploads\/sites\/3\/2019\/03\/NSF.png” _builder_version=”4.6.6″ _module_preset=”default”][\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_4″ _builder_version=”4.6.6″ _module_preset=”default”][et_pb_blurb image=”https:\/\/research.ece.ncsu.edu\/wp-content\/uploads\/sites\/3\/2019\/03\/total.png” _builder_version=”4.6.6″ _module_preset=”default”][\/et_pb_blurb][et_pb_blurb image=”https:\/\/research.ece.ncsu.edu\/wp-content\/uploads\/sites\/3\/2019\/03\/huawei-e1604566307904.png” _builder_version=”4.6.6″ _module_preset=”default”][\/et_pb_blurb][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" Real-time estimation of the state of charge (SOC) of the battery is a crucial need in the growing fields of plug-in hybrid electric vehicles and smart grid applications. The SOC estimation accuracy depends on the accuracy of the model used to describe the characteristics of the battery. To accurately estimate the SOC of […]<\/p>\n","protected":false},"author":14,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"Under Construction<\/h2>","_et_gb_content_width":"","footnotes":"","_wp_rev_ctl_limit":""},"categories":[66,64,1],"tags":[],"class_list":["post-2466","post","type-post","status-publish","format-standard","hentry","category-control-and-management","category-energy-storage","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/research.ece.ncsu.edu\/adac\/wp-json\/wp\/v2\/posts\/2466","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/research.ece.ncsu.edu\/adac\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/research.ece.ncsu.edu\/adac\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/adac\/wp-json\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/adac\/wp-json\/wp\/v2\/comments?post=2466"}],"version-history":[{"count":11,"href":"https:\/\/research.ece.ncsu.edu\/adac\/wp-json\/wp\/v2\/posts\/2466\/revisions"}],"predecessor-version":[{"id":2758,"href":"https:\/\/research.ece.ncsu.edu\/adac\/wp-json\/wp\/v2\/posts\/2466\/revisions\/2758"}],"wp:attachment":[{"href":"https:\/\/research.ece.ncsu.edu\/adac\/wp-json\/wp\/v2\/media?parent=2466"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/adac\/wp-json\/wp\/v2\/categories?post=2466"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/adac\/wp-json\/wp\/v2\/tags?post=2466"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}