{"id":948,"date":"2022-08-17T15:26:49","date_gmt":"2022-08-17T20:26:49","guid":{"rendered":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/?p=948"},"modified":"2022-08-17T15:26:49","modified_gmt":"2022-08-17T20:26:49","slug":"a-jana-s-mitra-s-das-w-c-chueh-m-z-bazant-r-edwin-garcia-physics-based-reduced-order-degradation-model-of-lithium-ion-batteries-journal-of-power-sources-545231900-2022","status":"publish","type":"post","link":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/2022\/08\/17\/a-jana-s-mitra-s-das-w-c-chueh-m-z-bazant-r-edwin-garcia-physics-based-reduced-order-degradation-model-of-lithium-ion-batteries-journal-of-power-sources-545231900-2022\/","title":{"rendered":"A. Jana, S. Mitra, S. Das, W.C. Chueh, M.Z. Bazant, R. Edwin Garc\u00eda “Physics-based, reduced order degradation model of lithium-ion batteries.” Journal of Power Sources. 545:231900, (2022)."},"content":{"rendered":"\n

A. Jana, S. Mitra, S. Das, W.C. Chueh, M.Z. Bazant, R.Edwin Garc\u00eda “Physics-based, reduced order degradation model of lithium-ion batteries.<\/em>” Journal of Power Sources<\/strong>. 545:231900, (2022). https:\/\/doi.org\/10.1016\/j.jpowsour.2022.231900<\/a><\/p>\n\n\n\n

Abstract<\/h2>\n\n\n\n

A physics-based, reduced order framework is developed to calculate the charge capacity loss contributions from spatially homogeneous and heterogeneous degradation mechanisms, chemomechanical cycling and initial capacity recovery. The formulation goes well beyond prevalent coulomb-counting models and is tuned solely based on experimentally measurable parameters, although it neglects any buildup of internal resistance. The model is compared against the largest data set available to date for commercial LiFePO4-graphite cells and shows less than 10% error for 92% of the cells. Results suggest that in most cells the charge capacity increases through the first \u223c50 cycles, beyond which homogeneous SEI growth dominates capacity loss up to \u223c500 cycles. Above \u223c500 cycles and at high current densities, the model attributes capacity loss primarily to heterogeneous SEI growth proceeding at microstructurally favored locations, further assisted by chemomechanical failure of the graphite anode particles towards the end of cell life. The developed model sets the stage for on-the-fly capacity loss calculations in hybrid and electric vehicles, especially at low currents and constant voltage holds and could be extended to capture the deleterious effects of high current densities in fast-charging scenarios by including resistive losses.<\/p>\n","protected":false},"excerpt":{"rendered":"

A. Jana, S. Mitra, S. Das, W.C. Chueh, M.Z. Bazant, R.Edwin Garc\u00eda…<\/p>\n

Continue reading “A. Jana, S. Mitra, S. Das, W.C. Chueh, M.Z. Bazant, R. Edwin Garc\u00eda “Physics-based, reduced order degradation model of lithium-ion batteries.” Journal of Power Sources. 545:231900, (2022).”<\/span>…<\/a><\/div>\n
Continue reading \"A. Jana, S. Mitra, S. Das, W.C. Chueh, M.Z. Bazant, R. Edwin Garc\u00eda “Physics-based, reduced order degradation model of lithium-ion batteries.” Journal of Power Sources. 545:231900, (2022).\"<\/span>…<\/a><\/div>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"advanced_seo_description":"","jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true},"categories":[45],"tags":[9,74,6],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/peeeSR-fi","jetpack_likes_enabled":true,"jetpack-related-posts":[{"id":811,"url":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/2019\/03\/21\/a-jana-g-m-shaver-r-edwin-garcia-physical-on-the-fly-capacity-degradation-prediction-of-linimncoo2-graphite-cells-journal-of-power-sources-422-2019-185-195\/","url_meta":{"origin":948,"position":0},"title":"A. Jana, G. M. Shaver, R. Edwin Garc\u00eda “Physical, on the fly, capacity degradation prediction of LiNiMnCoO2- graphite cells,” Journal of Power Sources. 422 (2019) 185\u2013195","date":"03\/21\/2019","format":false,"excerpt":"A. Jana, G. M. Shaver, R. Edwin Garc\u00eda \"Physical, on the fly, capacity degradation prediction of LiNiMnCoO2- graphite cells,\" Journal of Power Sources. 422 (2019) 185\u2013195;\u00a0https:\/\/doi.org\/10.1016\/j.jpowsour.2019.02.073 abstract A physics-based, reduced order model was developed to describe the capacity degradation in LiNiMnCoO2- graphite cells. By starting from fundamental principles, the model\u2026","rel":"","context":"In "Papers"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":517,"url":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/2017\/11\/04\/x-jin-a-vora-v-hoshing-t-saha-g-shaver-re-garcia-o-wasynczuk-s-varigonda-physically-based-reduced-order-capacity-loss-model-for-graphite-anodes-in-li-ion-battery-cells-journal-of-powe\/","url_meta":{"origin":948,"position":1},"title":"X Jin, A Vora, V Hoshing, T Saha, G Shaver, RE Garc\u00eda, O Wasynczuk, S Varigonda “Physically-based reduced-order capacity loss model for graphite anodes in Li-ion battery cells.”\u00a0Journal of Power Sources, 342:750-761, 2017.","date":"11\/04\/2017","format":false,"excerpt":"X Jin, A Vora, V Hoshing, T Saha, G Shaver, RE Garc\u00eda, O Wasynczuk, S Varigonda \"Physically-based reduced-order capacity loss model for graphite anodes in Li-ion battery cells.\"\u00a0Journal of Power Sources, 342:750-761, 2017. Abstract Physically-based Li-ion electrochemical cell models have been shown capable of predicting cell performance and degradation, but\u2026","rel":"","context":"In "Papers"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":507,"url":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/2017\/11\/04\/a-jana-dr-ely-re-garcia-dendrite-separator-interactions-in-lithium-based-batteries-journal-of-power-sources-275912-921-2015\/","url_meta":{"origin":948,"position":2},"title":"A Jana, DR Ely, RE Garc\u00eda “Dendrite-separator interactions in lithium-based batteries.”\u00a0Journal of Power Sources, 275:912-921, 2015.","date":"11\/04\/2017","format":false,"excerpt":"A Jana, DR Ely, RE Garc\u00eda \"Dendrite-separator interactions in lithium-based batteries.\"\u00a0Journal of Power Sources, 275:912-921, 2015. Abstract The effect of separator pore size on lithium dendrite growth is assessed through the use of the phase field method (PFM). Dendrites are found to undergo concurrent electrodeposition and electrodissolution that define their\u2026","rel":"","context":"In "Papers"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":502,"url":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/2017\/11\/04\/dr-ely-a-jana-re-garcia-phase-field-kinetics-of-lithium-electrodeposits-journal-of-power-sources-272581-594-2014\/","url_meta":{"origin":948,"position":3},"title":"DR Ely, A Jana, RE Garc\u00eda “Phase field kinetics of lithium electrodeposits.”\u00a0Journal of Power Sources, 272:581-594, 2014.","date":"11\/04\/2017","format":false,"excerpt":"DR Ely, A Jana, RE Garc\u00eda \"Phase field kinetics of lithium electrodeposits.\"\u00a0Journal of Power Sources, 272:581-594, 2014. Abstract A phase field description is formulated to describe the growth kinetics of an heterogeneously nucleated distribution of lithium electrodeposits. The underlying variational principle includes the bulk electrochemical contributions to the free energy\u2026","rel":"","context":"In "Papers"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":939,"url":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/2022\/08\/04\/y-sun-s-mitra-ayalasomayajula-a-deva-g-lin-r-edwin-garcia-artificial-intelligence-inferred-microstructural-properties-from-voltage-capacity-curves-scientific-reports-1213421\/","url_meta":{"origin":948,"position":4},"title":"Y. Sun, S. Mitra Ayalasomayajula, A. Deva, G. Lin & R. Edwin Garc\u00eda “Artificial intelligence inferred microstructural properties from voltage\u2013capacity curves.” Scientific Reports. 12:13421, 2022.","date":"08\/04\/2022","format":false,"excerpt":"Y. Sun, S. Mitra Ayalasomayajula, A. Deva, G. Lin & R. Edwin Garc\u00eda \"Artificial intelligence inferred microstructural properties from voltage\u2013capacity curves.\" Scientific Reports. 12:13421, 2022. https:\/\/doi.org\/10.1038\/s41598-022-16942-5 Abstract The quantification of microstructural properties to optimize battery design and performance, to maintain product quality, or to track the degradation of LIBs remains\u2026","rel":"","context":"In "Papers"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":837,"url":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/2019\/11\/15\/a-jana-s-i-woo-k-s-n-vikrant-and-r-e-garcia-electrochemomechanics-of-lithium-dendrite-growth-energy-environmental-science-2019\/","url_meta":{"origin":948,"position":5},"title":"A. Jana, S.-I. Woo, K.S.N. Vikrant, and R.E. Garc\u00eda \u00a0“Electrochemomechanics of lithium dendrite growth.”\u00a0Energy & Environmental Science, 12:3595-3607, 2019","date":"11\/15\/2019","format":false,"excerpt":"A. Jana, S.-I. Woo, K.S.N. Vikrant, and R.E. Garc\u00eda \u00a0\"Electrochemomechanics of lithium dendrite growth.\"\u00a0Energy Environ. Sci., 12:\u00a03595-3607, 2019.\u00a0https:\/\/doi.org\/10.1039\/C9EE01864F abstract A comprehensive roadmap describing the current density- and size-dependent dendrite growth mechanisms is presented. Based on a thermodynamically consistent theory, the combined effects of chemical diffusion, electrodeposition, and elastic and plastic\u2026","rel":"","context":"In "Papers"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"_links":{"self":[{"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/posts\/948"}],"collection":[{"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/comments?post=948"}],"version-history":[{"count":2,"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/posts\/948\/revisions"}],"predecessor-version":[{"id":950,"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/posts\/948\/revisions\/950"}],"wp:attachment":[{"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/media?parent=948"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/categories?post=948"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/tags?post=948"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}