A 42nJ/conversion On-Demand State-of-Charge Indicator for Miniature IoT Li-ion Batteries

被引：0
|
作者：
Jeong, Junwon [1 ,2 ]
Jeong, Seokhyeon [2 ]
Kim, Chulwoo [1 ]
Sylvester, Dennis [2 ]
Blaauw, David [2 ]
机构：
[1] Korea Univ, Seoul, South Korea
[2] Univ Michigan, Ann Arbor, MI 48109 USA
来源：
2018 23RD ASIA AND SOUTH PACIFIC DESIGN AUTOMATION CONFERENCE (ASP-DAC) | 2018年
关键词：
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
An energy efficient State-of-Charge (SOC) indication algorithm and integrated system for small IoT batteries are introduced in this paper. The system is implemented in a 180-nm CMOS technology. Based on a key finding that small Li-ion batteries exhibit a linear dependence between battery voltage and load current, we propose an instantaneous linear extrapolation (ILE) algorithm and circuit allowing on-demand estimation of SOC. Power consumption is 42nW and maximum SOC indication error is 1.7%.
引用
收藏
页码：281 / 282
页数：2
相关论文
共 50 条
  • [31] A Hybrid Long Short-Term Memory Network for State-of-Charge Estimation of Li-ion Batteries
    Oyewole, Isaiah
    Savargaonkar, Mayuresh
    Chehade, Abdallah
    Kim, Youngki
    2021 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE & EXPO (ITEC), 2021, : 469 - 473
  • [32] A method for state-of-charge estimation of Li-ion batteries based on multi-model switching strategy
    Wang, Yujie
    Zhang, Chenbin
    Chen, Zonghai
    APPLIED ENERGY, 2015, 137 : 427 - 434
  • [33] State-of-Charge Implications of Thermal Runaway in Li-ion Cells and Modules
    Karmakar, Avijit
    Zhou, Hanwei
    Vishnugopi, Bairav S.
    Jeevarajan, Judith A.
    Mukherjee, Partha P.
    JOURNAL OF THE ELECTROCHEMICAL SOCIETY, 2024, 171 (01)
  • [34] Robust Observer for State-of-Charge Estimation of Li-ion Battery with Uncertainties
    Goh, Taedong
    Kim, Daehyun
    Jeong, Jae Jin
    Park, Minjun
    Kim, Sang Woo
    2015 10TH ASIAN CONTROL CONFERENCE (ASCC), 2015,
  • [35] On-line estimation of state-of-charge of Li-ion batteries in electric vehicle using the resampling particle filter
    Shao, Sai
    Bi, Jun
    Yang, Fan
    Guan, Wei
    TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2014, 32 : 207 - 217
  • [36] A Modified State of Charge Estimation Method for Li-ion Batteries
    Sandrabyna, Mallikarjuna
    Sharma, Shrivatsal
    Basu, Suman
    2019 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE (ITEC-INDIA), 2019,
  • [37] Impact of Current Rate and Temperature on State-of-Charge Estimation of Li-ion Batteries Based on the Extended Kalman Filter
    Issac, James
    Qin, Jiangchao
    Saeedifard, Maryam
    Wasynczuk, Oleg
    IECON 2014 - 40TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2014, : 3122 - 3128
  • [38] Robust state-of-charge estimation of Li-ion batteries based on multichannel convolutional and bidirectional recurrent neural networks
    Bian, Chong
    Yang, Shunkun
    Liu, Jie
    Zio, Enrico
    APPLIED SOFT COMPUTING, 2022, 116
  • [39] Computationally Efficient State-of-Charge Estimation in Li-Ion Batteries Using Enhanced Dual-Kalman Filter
    Wadi, Ali
    Abdel-Hafez, Mamoun
    Hussein, Ala A.
    ENERGIES, 2022, 15 (10)
  • [40] AC Impedance Based Online State-of-Charge Estimation for Li-ion Battery
    Wu, Shing-Lih
    Chen, Hung-Cheng
    Tsai, Ming-Yang
    Lin, Tong-Chou
    Chen, Liang-Ruei
    PROCEEDINGS OF THE 2017 IEEE INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATION AND ENGINEERING (IEEE-ICICE 2017), 2017, : 53 - 56
12345