Battery State Estimation Using Unscented Kalman Filter

被引：0
|
作者：
Zhang, Fei [1 ]
Liu, Guangjun [2 ]
Fang, Lijin [1 ]
机构：
[1] Chinese Acad Sci, State Key Lab Robot, Shenyang Inst Automat, Shenyang 110016, Peoples R China
[2] Ryerson Univ, Dept Aerosp Engn, Toronto, ON M5B 2K3, Canada
来源：
ICRA: 2009 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-7 | 2009年
基金：
国家高技术研究发展计划(863计划);
关键词：
LEAD-ACID-BATTERIES; PREDICTING STATE; OF-CHARGE; HEALTH;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Online evaluation of battery State of Function (SOF) is crucial for battery management systems of autonomous mobile robots. Battery State of Charge (SOC) represents its remaining energy available, whereas internal resistance and capacity reflect its State of Health (SOH). In this paper, an improved equivalent circuit model is proposed to estimate SOC, internal resistance and capacity using an Unscented Kalman Filter (UKF). The proposed method not only estimates SOC, but also evaluates SOH and SOF. Experimental results have shown the effectiveness of the proposed method using resistive loads and a robot prototype for inspecting power transmission line.
引用
收藏
页码：3574 / +
页数：2
相关论文
共 50 条
  • [21] Vehicle State Information Estimation with the Unscented Kalman Filter
    Ren, Hongbin
    Chen, Sizhong
    Liu, Gang
    Zheng, Kaifeng
    ADVANCES IN MECHANICAL ENGINEERING, 2014,
  • [22] State of Charge and parameters estimation for Lithium-ion battery using Dual Adaptive Unscented Kalman Filter
    Guo, Hongzhen
    Wang, Zhonghua
    Li, Yueyang
    Wang, Dongxue
    Wang, Guangying
    2017 29TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2017, : 4962 - 4966
  • [23] Partition-based Unscented Kalman Filter for Reconfigurable Battery Pack State Estimation using an Electrochemical Model
    Couto, Luis D.
    Kinnaert, Michel
    2018 ANNUAL AMERICAN CONTROL CONFERENCE (ACC), 2018, : 3122 - 3128
  • [24] An Accurate State of Charge Estimation Method for Lithium Iron Phosphate Battery Using a Combination of an Unscented Kalman Filter and a Particle Filter
    Nguyen, Thanh-Tung
    Khan, Abdul Basit
    Ko, Younghwi
    Choi, Woojin
    ENERGIES, 2020, 13 (17)
  • [25] Estimation of Rotary Inverted Pendulum by using the Unscented Kalman Filter - Estimation of the initial state
    Zheng, Min
    Ikeda, Kenji
    Shimomura, Takao
    PROCEEDINGS OF SICE ANNUAL CONFERENCE, VOLS 1-8, 2007, : 1665 - 1668
  • [26] Information Fusion for State Estimation of Power Battery in Electric Vehicle Based on Unscented Kalman Filter
    Zheng, Hongyu
    Zong, Changfu
    SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS, PTS 1-4, 2013, 303-306 : 975 - 978
  • [27] A Novel State-of-Health Estimation for Lithium-Ion Battery via Unscented Kalman Filter and Improved Unscented Particle Filter
    Zhu, Feng
    Fu, Jingqi
    IEEE SENSORS JOURNAL, 2021, 21 (22) : 25449 - 25456
  • [28] State of charge estimation of vehicle lithium-ion battery based on unscented Kalman filter
    Chen, Junlin
    Wang, Chun
    Pu, Long
    39TH YOUTH ACADEMIC ANNUAL CONFERENCE OF CHINESE ASSOCIATION OF AUTOMATION, YAC 2024, 2024, : 1934 - 1938
  • [29] State Estimation of Nonlinear Systems Using Novel Adaptive Unscented Kalman Filter
    Jargani, Lotfollah
    Shahbazian, Mehdi
    Salahshoor, Karim
    Fathabadi, Vahid
    ICET: 2009 INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES, PROCEEDINGS, 2009, : 124 - 129
  • [30] State Estimation in a Hydraulically Actuated Log Crane Using Unscented Kalman Filter
    Khadim, Qasim
    Hagh, Yashar Shabbouei
    Pyrhonen, Lauri
    Jaiswal, Suraj
    Zhidchenko, Victor
    Kurvinen, Emil
    Sopanen, Jussi
    Mikkola, Aki
    Handroos, Heikki
    IEEE ACCESS, 2022, 10 : 62863 - 62878
12345