Data-driven State-of-health Estimation of EV batteries Using Fatigue Features

被引：0
|
作者：
Park, Sangdo [1 ]
You, Gae-won [1 ]
Oh, Duk-jin [1 ]
机构：
[1] Samsung Elect, Samsung Adv Inst Technol, Suwon, South Korea
来源：
2016 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS (ICCE) | 2016年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Estimating State-of-Health(SOH) for electric vehicle( EV) batteries is the most crucial to determine replacement time of the battery or to calculate driving mileage. However, partial charge and discharge, or steep changes of current loads imposed in EV increase estimation error. In this paper, we present a data-driven method for Battery Management System(BMS) to precisely estimate the SOH reflecting batterys stress pattern.
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页数：2
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