کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6945870 | 1450520 | 2018 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Heuristic Kalman optimized particle filter for remaining useful life prediction of lithium-ion battery
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
سخت افزارها و معماری
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Accurate prediction of the remaining useful life of a faulty component is important to the prognosis and health management of any engineering system. In recent times, the particle filter algorithm and several variants of it have been used as an effective method for this purpose. However, particle filter suffers from sample degeneracy and impoverishment. In this study, we introduce the Heuristic Kalman algorithm, a metaheuristic optimization approach, in combination with particle filtering to tackle sample degeneracy and impoverishment. Our proposed method is compared with the particle swarm optimized particle filtering technique, another popular metaheuristic approach for improvement of particle filtering. The prediction accuracy and precision of our proposed method is validated using several Lithium ion battery data sets from NASA® Ames research center.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Microelectronics Reliability - Volume 81, February 2018, Pages 232-243
Journal: Microelectronics Reliability - Volume 81, February 2018, Pages 232-243
نویسندگان
Pham Luu Trung Duong, Nagarajan Raghavan,