کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7730039 | 1497931 | 2016 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Capacity-loss diagnostic and life-time prediction in lithium-ion batteries: Part 1. Development of a capacity-loss diagnostic method based on open-circuit voltage analysis
ترجمه فارسی عنوان
پیش بینی احتمالی تشخیصی و طول عمر در باتری های لیتیوم یون: بخش 1: توسعه یک روش تشخیص ظرفیت از دست رفته بر اساس تحلیل ولتاژ باز
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
باتری لیتیوم یون، ظرفیت تلفات تشخیصی پیش بینی طول عمر، ولتاژ مدار آزاد،
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
الکتروشیمی
چکیده انگلیسی
Effective capacity-loss diagnosis and life-time prediction are the foundations of battery second-use technology and will play an important role in the development of the new energy industry. Of the two, the capacity-loss diagnostic, as a precondition of the life-time prediction, needs to be studied first. Performing a capacity-loss diagnosis for an aging cell consists of finding the decisive degradation mechanisms for the cell's capacity degradation. Because a cell's capacity just equals the span of the open-circuit voltage (OCV), when suspect degradation mechanisms affect a cell's capacity, they will leave corresponding and particular clues in the OCV curve. Taking a cell's OCV as the diagnostic indicator, a multi-mechanistic and non-destructive diagnostic method is developed in this paper. To establish an unambiguous relationship between OCV changes and the combinations of the decisive mechanisms, all the possible OCV changes under various aging situations are systematically analyzed based on a novel simultaneous coordinate system, in which the effects of each suspect capacity-loss mechanism on the OCV curve can be clearly represented. As a summary of the analysis results, a straightforward diagnostic flowchart is presented. By following the flowchart, an aging cell can be diagnosed within three steps by observation of the OCV changes.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Power Sources - Volume 301, 1 January 2016, Pages 187-193
Journal: Journal of Power Sources - Volume 301, 1 January 2016, Pages 187-193
نویسندگان
Tiansi Wang, Lei Pei, Tingting Wang, Rengui Lu, Chunbo Zhu,