Smartphone Battery State-of-Charge (SoC) Estimation and battery lifetime prediction: State-of-art review

被引:0
作者
Singh, Magendra [1 ]
Maan, Priyanka [1 ]
Trivedi, Jay [1 ]
Goyal, Jai [1 ]
机构
[1] Samsung Res Inst Noida, Prod R&D, Noida, India
来源
PROCEEDINGS OF THE CONFLUENCE 2020: 10TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING, DATA SCIENCE & ENGINEERING | 2020年
关键词
Battery optimization; SoC; Battery estimation; power modelling; battery life prediction;
D O I
10.1109/confluence47617.2020.9057951
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With advancements in hardware and software technologies in mobile devices, there is an ever increasing demand of power supply. The battery consumption by hardware and software components has drastically increased. Significant research has been done in the area of mobile battery SoC estimation and battery lifetime prediction. Accurate estimation of battery consumption and remaining battery lifetime helps to optimize battery usage and enables the user to plan his/her usage accordingly. We studied the literature related to various approaches and methodologies that have been proposed for Battery SoC Estimation and Battery Lifetime estimation. In the following paper, we summarize their approach and present a qualitative comparison of these studied methods. We underline the approaches used in different schemes, summarize the features considered by them for battery lifetime prediction and list the potential pros and cons of each approach. Finally, major challenges in this area have been put forward along with the open issues in mobile battery lifetime estimation and prediction.
引用
收藏
页码:94 / 101
页数:8
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