Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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A synthetic dataset of 12 LG M50 cells was generated using physics-based models. The model parameters for this commercial NMC 811/graphite-SiOx cell were taken from multiple sources in the literature. In particular, five degradation parameters were varied from their default values as parameter sensitivity analysis. The 12 LG M50 cells were identically discharged at a 1C galvanostatic profile to 0 % state-of-charge (SoC) and then charged at a 1C constant-current and constant-voltage (CC-CV) protocol to 100 % SoC. The ambient temperature in the simulation was set to be constant at 25 °C. As a result, 4 degradation pathways were identified with 4 different configurations of interacting degradation mechanisms, i.e., solid electrolyte interphase (SEI) growth, particle cracking, lithium plating, and loss of active material. The dataset allows for the validation of battery degradation diagnosis and prognosis methods with insights into interactions between multiple degradation mechanisms. One exemplary application of validating a knee identification method can be found in Ref. [1].
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11570748 | PMC |
http://dx.doi.org/10.1016/j.dib.2024.111076 | DOI Listing |