Growing interest in sustainable mobility and green energy has prompted researchers to explore innovative energy storage systems, with a focus on lithium-ion batteries. This study proposes an analytical model for understanding battery cycle aging and accurate estimation of state of charge, with promising results.<\/p>\n","protected":false},"author":93,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"tags":[1302,1300,1301,1299,1369],"targets":[1304,1314,1317],"pubblicazioni_tipologie":[773],"class_list":["post-202927","pubblicazioni","type-pubblicazioni","status-publish","hentry","tag-batteries","tag-industrial-sector","tag-sodium-ion-batteries","tag-storage-en","tag-sustainable-mobility","targets-industrial-world","targets-press-media-en","targets-research","pubblicazioni_tipologie-isi-article-en"],"acf":{"dont_show_hompage":true,"projects":{"ID":188409,"post_author":"93","post_date":"2024-06-13 15:10:21","post_date_gmt":"2024-06-13 13:10:21","post_content":"","post_title":"Electrochemical and thermal storage technologies","post_excerpt":"The goal of this project is to develop electrochemical and thermal storage technologies with improved performance and greater environmental and economic sustainability by optimizing the use of resources, material formulations and synthesis methods, diagnostic and control processes, and prototype design.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"electrochemical-and-thermal-storage-technologies","to_ping":"","pinged":"","post_modified":"2024-07-06 15:23:41","post_modified_gmt":"2024-07-06 13:23:41","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.rse-web.it\/progetti\/electrochemical-and-thermal-storage-technologies\/","menu_order":0,"post_type":"progetti","post_mime_type":"","comment_count":"0","filter":"raw"},"order_posts":"","dont_show_search":false,"related_posts":false,"show_on_slider":false,"single_post_data":{"titolo_spot":"","post_content":"
Currently, the urgent needs of sustainable mobility and green energy generation are driving governments and researchers to explore innovative energy storage systems. Concurrently, lithium-ion batteries are one of the most extensively employed technologies. The challenges of battery modeling and parameter estimation are crucial for building reliable battery management systems that ensure optimal battery performance.<\/p>\n
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State of charge (SOC) estimation is particularly critical for predicting the available capacity in the battery. Many methods for SOC estimation rely on the knowledge of the open-circuit voltage (OCV) curve. Another significant consideration is understanding how these curves evolve with battery degradation. In the literature, the effect of cycle aging on the OCV is primarily addressed through the look-up tables and correction factors applied to the OCV curve for fresh cells.<\/p>\n
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However, the variation law of the OCV curve as a function of the battery cycling is not well-characterized. Building upon a simple analytical function with five parameters proposed in the prior research to model the OCV as a function of the absolute state of discharge, this study investigates the dependency of these parameters on the moved charge, serving as an indicator of the cycling level. Specifically, the analysis focuses on the impact of cycle aging in the low-, medium-, and high-SOC regions.<\/p>\n
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Three different cycle aging tests were conducted in these SOC intervals, followed by the extensive experimental verification of the proposed model. The results were promising, with mean relative errors lower than 0.2% for the low- and high-SOC cycling regions and 0.34% for the medium-SOC cycling region. Finally, capacity estimation was enabled by the model, achieving relative error values lower than 1% for all the tests.<\/p>\n","scarica_file":false,"link_estreno":[{"link_text":"Download Publication","link":"https:\/\/www.mdpi.com\/1996-1073\/17\/10\/2364"}],"button":{"text":"","link":""},"referente_group":false,"data_emissione":"2024-05-14","autori":"S. Barcellona, L. Codecasa, L. Piegari (Politecnico di Milano), S. Colnago (RSE S.p.A.)","destinazione":"MDPI Sensors, Vol. 17, Issue 10","rif_rse":"24004868"},"satellite_post_url":""},"yoast_head":"\n