کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1285520 1497927 2016 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An adaptive remaining energy prediction approach for lithium-ion batteries in electric vehicles
ترجمه فارسی عنوان
یک رویکرد پیش بینی انرژی باقی مانده برای باتری های لیتیوم یون در خودروهای الکتریکی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه شیمی الکتروشیمی
چکیده انگلیسی


• An adaptive SoE estimation approach is established.
• A data-driven model is established for SoE estimation.
• The forgetting factor RLS method is employed for parameter identification.
• Dynamic current and temperature profiles are performed on the LiFePO4 cells.

With the growing number of electric vehicle (EV) applications, the function of the battery management system (BMS) becomes more sophisticated. The accuracy of remaining energy estimation is critical for energy optimization and management in EVs. Therefore the state-of-energy (SoE) is defined to indicate the remaining available energy of the batteries. Considering that there are inevitable accumulated errors caused by current and voltage integral method, an adaptive SoE estimator is first established in this paper. In order to establish a reasonable battery equivalent model, based on the experimental data of the LiFePO4 battery, a data-driven model is established to describe the relationship between the open-circuit voltage (OCV) and the SoE. What is more, the forgetting factor recursive least-square (RLS) method is used for parameter identification to get accurate model parameters. Finally, in order to analyze the robustness and the accuracy of the proposed approach, different types of dynamic current profiles are conducted on the lithium-ion batteries and the performances are calculated and compared. The results indicate that the proposed approach has robust and accurate SoE estimation results under dynamic working conditions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Power Sources - Volume 305, 15 February 2016, Pages 80–88
نویسندگان
, , ,