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State of Charge Estimation for Lithium-Ion Batteries Using Extended Kalman Filter with Local Linearization
Technical Paper
2017-01-1734
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
An accurate estimation of the state of charge (SOC) is necessary not only for optimal energy management but also for protecting the lithium-ion batteries (LIB) from being deeply discharged or overcharged. In this paper, an equivalent circuit model (ECM) is established to simulate the dynamic behavior of LIB. Parameters of internal resistance, diffusion resistance and diffusion capacitance are identified using the recursive least square method. Because open circuit voltage (OCV) and SOC have an obviously nonlinear relationship, an extended Kalman filter is proposed to estimate the SOC based on the ECM model. Local linearization is employed to approximate the nonlinear SOC-OCV curve by a straight line with the slope and intersection around the operating point. Simulation results show that the estimation error of the proposed algorithm is less than 5% for the test patterns.
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Chen, B. and Chuang, G., "State of Charge Estimation for Lithium-Ion Batteries Using Extended Kalman Filter with Local Linearization," SAE Technical Paper 2017-01-1734, 2017, https://doi.org/10.4271/2017-01-1734.Data Sets - Support Documents
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References
- Soon , Kong , Moo Chin-sien , Chen Yi-ping , and Hsieh Yao-ching 2009 Enhanced Coulomb Counting Method for Estimating State-of-Charge and State-of-Health of Lithium-Ion Batteries Applied Energy 86 9 Elsevier Ltd 1506 11 10.1016/j.apenergy.2008.11.021
- Lu , Languang , Han Xuebing , Li Jianqiu , Hua Jianfeng , and Ouyang Minggao 2013 A Review on the Key Issues for Lithium-Ion Battery Management in Electric Vehicles Journal of Power Sources 226 Elsevier B.V 272 88 10.1016/j.jpowsour.2012.10.060
- Waag , Wladislaw , Fleischer Christian , and Uwe Dirk 2014 Critical Review of the Methods for Monitoring of Lithium-Ion Batteries in Electric and Hybrid Vehicles Journal of Power Sources 258 Elsevier B.V 321 39 10.1016/j.jpowsour.2014.02.064
- Fotouhi , Abbas , Auger Daniel J , Propp Karsten , Longo Stefano , and Wild Mark 2016 A Review on Electric Vehicle Battery Modelling: From Lithium-Ion toward Lithium - Sulphur Renewable and Sustainable Energy Reviews 56 Elsevier 1008 21 10.1016/j.rser.2015.12.009
- He , Wei , Williard Nicholas , Chen Chaochao , and Pecht Michael 2014 Electrical Power and Energy Systems State of Charge Estimation for Li-Ion Batteries Using Neural Network Modeling and Unscented Kalman Filter-Based Error Cancellation International Journal of Electrical Power and Energy Systems 62 Elsevier Ltd 783 91 10.1016/j.ijepes.2014.04.059
- Salkind , Alvin J , Fennie Craig , Singh Pritpal , Atwater Terrill , and Reisner David E 1999 Determination of State-of-Charge and State-of-Health of Batteries by Fuzzy Logic Methodology 293 300
- Kim , Taesic 2013 Online SOC and SOH Estimation for Multicell Lithium-Ion Batteries Based on an Adaptive Hybrid Battery Model and Sliding-Mode Observer 292 98
- Rezwan , Mohammad , Mulder Grietus , and Van Mierlo Joeri 2014 An Online Framework for State of Charge Determination of Battery Systems Using Combined System Identi Fi Cation Approach Journal of Power Sources 246 Elsevier B.V 629 41 10.1016/j.jpowsour.2013.07.092
- Barillas , Joaquín Klee , Li Jiahao , Günther Clemens , and Danzer Michael A 2015 A Comparative Study and Validation of State Estimation Algorithms for Li-Ion Batteries in Battery Management Systems 155 455 62 10.1016/j.apenergy.2015.05.102
- He , Hongwen , Xiong Rui , Zhang Xiaowei , Sun Fengchun , Fan Jinxin Student Member 2011 State-of-Charge Estimation of the Lithium-Ion Battery Using an Adaptive Extended Kalman Filter Based on an Improved Thevenin Model 60 4 1461 69
- Xia , Bizhong , Wang Haiqing , Tian Yong , Wang Mingwang , Sun Wei , and Xu Zhihui 2015 State of Charge Estimation of Lithium-Ion Batteries Using an Adaptive Cubature Kalman Filter 5916 36 10.3390/en8065916
- Sun , Fengchun , Hu Xiaosong , Zou Yuan , and Li Siguang 2011 Adaptive Unscented Kalman Fi Ltering for State of Charge Estimation of a Lithium-Ion Battery for Electric Vehicles State of Charge Energy 36 5 Elsevier Ltd 3531 40 10.1016/j.energy.2011.03.059
- Dai , Haifeng , Wei Xuezhe , Sun Zechang , Wang Jiayuan , and Gu Weijun 2012 Online Cell SOC Estimation of Li-Ion Battery Packs Using a Dual Time-Scale Kalman Filtering for EV Applications Applied Energy 95 Elsevier Ltd 227 37 10.1016/j.apenergy.2012.02.044
- Snihir , Iryna , Rey William , Verbitskiy Evgeny , Belfadhelayeb Afifa , and Notten Peter H L 2006 Battery Open-Circuit Voltage Estimation by a Method of Statistical Analysis 159 1484 87 10.1016/j.jpowsour.2005.11.090
- Kim , Jong Hoon , Lee Seong Jun , Lee Jae Moon , and Cho Bo Hyung 2008 A New Direct Current Internal Resistance and State of Charge Relationship for the Li-Ion Battery Pulse Power Estimation 1173 78
- Id-, D O E 2003 FreedomCAR Battery Test Manual For Power-Assist Hybrid Electric Vehicles Disclaimer
- Yu , Zhihao , Huai Ruituo , and Xiao Linjing 2015 State-of-Charge Estimation for Lithium-Ion Batteries Using a Kalman Filter Based on Local Linearization 7854 73 10.3390/en8087854