Joint estimation for SOC and capacity after current measurement offset redress with two-stage forgetting factor recursive least square method
To ensure the safe operation of electric vehicles (EVs), it is essential to estimate the internal status of lithium-ion batteries online. When current sensors are faulty, current measurement offset (CMO) interference occurs, and traditional state estimation algorithms become invalid due to incorrect...
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| Published in | JOURNAL OF POWER ELECTRONICS Vol. 23; no. 12; pp. 1942 - 1953 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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Singapore
Springer Nature Singapore
01.12.2023
전력전자학회 |
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| ISSN | 1598-2092 2093-4718 |
| DOI | 10.1007/s43236-023-00683-3 |
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| Abstract | To ensure the safe operation of electric vehicles (EVs), it is essential to estimate the internal status of lithium-ion batteries online. When current sensors are faulty, current measurement offset (CMO) interference occurs, and traditional state estimation algorithms become invalid due to incorrect current data. In this paper, a two-stage forgetting factor recursive least squares (FFRLS) algorithm is proposed for online identification of battery parameters and estimation of the CMO. Afterwards, a joint estimation framework is established to obtain the state of charge (SOC) and capacity with adaptive extended Kalman filter (AEKF) and iterative reweighted least squares (IRLS) algorithms, respectively. The open-source dataset of the CALCE Battery Research Group is used to verify the accuracy and robustness of the algorithm. The results show that the mean absolute error (MAE) of the CMO online estimation is less than 2.5 mA, the mean absolute percentage error (MAPE) of the SOC estimation is less than 2%, and the error in estimating the usable capacity is less than 2.5%. |
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| AbstractList | To ensure the safe operation of electric vehicles (EVs), it is essential to estimate the internal status of lithium-ion batteries online. When current sensors are faulty, current measurement offset (CMO) interference occurs, and traditional state estimation algorithms become invalid due to incorrect current data. In this paper, a two-stage forgetting factor recursive least squares (FFRLS) algorithm is proposed for online identification of battery parameters and estimation of the CMO. Afterwards, a joint estimation framework is established to obtain the state of charge (SOC) and capacity with adaptive extended Kalman filter (AEKF) and iterative reweighted least squares (IRLS) algorithms, respectively. The open-source dataset of the CALCE Battery Research Group is used to verify the accuracy and robustness of the algorithm. The results show that the mean absolute error (MAE) of the CMO online estimation is less than 2.5 mA, the mean absolute percentage error (MAPE) of the SOC estimation is less than 2%, and the error in estimating the usable capacity is less than 2.5%. To ensure the safe operation of electric vehicles (EVs), it is essential to estimate the internal status of lithium-ion batteries online. When current sensors are faulty, current measurement offset (CMO) interference occurs, and traditional state estimation algorithms become invalid due to incorrect current data. In this paper, a two-stage forgetting factor recursive least squares (FFRLS) algorithm is proposed for online identification of battery parameters and estimation of the CMO. Afterwards, a joint estimation framework is established to obtain the state of charge (SOC) and capacity with adaptive extended Kalman filter (AEKF) and iterative reweighted least squares (IRLS) algorithms, respectively. The open-source dataset of the CALCE Battery Research Group is used to verify the accuracy and robustness of the algorithm. The results show that the mean absolute error (MAE) of the CMO online estimation is less than 2.5 mA, the mean absolute percentage error (MAPE) of the SOC estimation is less than 2%, and the error in estimating the usable capacity is less than 2.5%. KCI Citation Count: 0 |
| Author | Jia, Yunxu Wang, Aobo Chen, Yong Huo, Weiwei |
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| References | Guha, Patra (CR20) 2018; 4 Al-Gabalawy, Hosny, Dawson, Omar (CR7) 2021; 45 Hannan, Lipu, Hussain, Mohamed (CR1) 2017; 78 Lee, Kim, Lee (CR14) 2022; 10 Zhang, Zhu, Dong, Wei (CR10) 2019; 43 Zhang, Xiong, He, Qu, Pecht (CR17) 2019; 1 Zheng, Xing, Jiang, Sun, Kim (CR29) 2016; 183 Yang, Wang, Yang, Wang (CR2) 2019; 443 Hu, Hua, Wu, Dai, Xiao, Wang (CR25) 2020; 35 Zheng, Cui, Han, Dai, Ouyang (CR24) 2021; 44 Plett (CR5) 2004; 134 Xiong, Yu, Wang, Lin (CR11) 2017; 207 He, Xiong, Zhang, Sun, Fan (CR12) 2011; 60 Guo, Qiu, Hou, Liaw, Zhang (CR18) 2014; 249 Zheng, Ouyang, Han (CR15) 2018; 377 CR6 CR27 CR23 Manoharan, Mohankumar, Karthick, Sowmya (CR3) 2018; 6 Zheng, Zhu, Lu, Wang, He (CR19) 2018; 150 Tang, Wang, Chen (CR26) 2015; 296 Asghar, Talha, Kim, Ra (CR4) 2016; 20 Han, Ouyang, Lu, Li (CR16) 2015; 278 Xing, He, Pecht, Tsui (CR30) 2014; 113 Wassiliadis, Adermann, Frericks, Pak, Reiter, Lohmann, Lienkamp (CR22) 2018; 19 Peng, Zhang, Guo, Zhang (CR8) 2021; 45 Wei, Leng, He, Zhang, Li (CR21) 2018; 11 Cui, He, Li, Cheng (CR9) 2019; 43 Jiang, Dai, Wei, Xu (CR28) 2019; 253 Sun, Hu, Zou, Li (CR13) 2011; 36 N Wassiliadis (683_CR22) 2018; 19 MA Hannan (683_CR1) 2017; 78 683_CR6 683_CR23 F Zheng (683_CR29) 2016; 183 M Al-Gabalawy (683_CR7) 2021; 45 F Asghar (683_CR4) 2016; 20 B Jiang (683_CR28) 2019; 253 S Lee (683_CR14) 2022; 10 Y Zhang (683_CR17) 2019; 1 Y Xing (683_CR30) 2014; 113 P Manoharan (683_CR3) 2018; 6 C Zhang (683_CR10) 2019; 43 X Tang (683_CR26) 2015; 296 Z Wei (683_CR21) 2018; 11 Z Guo (683_CR18) 2014; 249 F Sun (683_CR13) 2011; 36 H He (683_CR12) 2011; 60 A Guha (683_CR20) 2018; 4 GL Plett (683_CR5) 2004; 134 N Peng (683_CR8) 2021; 45 R Xiong (683_CR11) 2017; 207 Y Zheng (683_CR24) 2021; 44 X Cui (683_CR9) 2019; 43 M Hu (683_CR25) 2020; 35 Y Zheng (683_CR15) 2018; 377 A Yang (683_CR2) 2019; 443 L Zheng (683_CR19) 2018; 150 X Han (683_CR16) 2015; 278 683_CR27 |
| References_xml | – volume: 19 start-page: 73 year: 2018 end-page: 87 ident: CR22 article-title: Revisiting the dual extended kalman filter for battery state-of-charge and state-of-health estimation: a use-case life cycle analysis publication-title: J. Energy Storage. doi: 10.1016/j.est.2018.07.006 – volume: 4 start-page: 135 issue: 1 year: 2018 end-page: 146 ident: CR20 article-title: State of health estimation of lithium-ion batteries using capacity fade and internal resistance growth models publication-title: IEEE Trans. Transp Electr. doi: 10.1109/TTE.2017.2776558 – volume: 113 start-page: 106 year: 2014 end-page: 115 ident: CR30 article-title: State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures publication-title: Appl. Energy doi: 10.1016/j.apenergy.2013.07.008 – volume: 134 start-page: 277 issue: 2 year: 2004 end-page: 292 ident: CR5 article-title: Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs: part 3. State and parameter estimation publication-title: J. Power Sources. doi: 10.1016/j.jpowsour.2004.02.033 – volume: 183 start-page: 513 year: 2016 end-page: 525 ident: CR29 article-title: Influence of different open circuit voltage tests on state of charge online estimation for lithium-ion batteries publication-title: Appl. Energy doi: 10.1016/j.apenergy.2016.09.010 – volume: 35 start-page: 11119 issue: 10 year: 2020 end-page: 11128 ident: CR25 article-title: Compensation of current measurement offset error for permanent magnet synchronous machines publication-title: IEEE Trans. Power Electron. doi: 10.1109/TPEL.2020.2978230 – volume: 78 start-page: 834 year: 2017 end-page: 854 ident: CR1 article-title: A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: challenges and recommendations publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2017.05.001 – ident: CR6 – volume: 278 start-page: 814 year: 2015 end-page: 825 ident: CR16 article-title: Simplification of physics-based electrochemical model for lithium ion battery on electric vehicle. Part II: pseudo-two-dimensional model simplification and state of charge estimation publication-title: J. Power Sources. doi: 10.1016/j.jpowsour.2014.08.089 – volume: 45 start-page: 6708 issue: 5 year: 2021 end-page: 6726 ident: CR7 article-title: State of charge estimation of a Li-ion battery based on extended Kalman filtering and sensor bias publication-title: Int. J. Energy Res. doi: 10.1002/er.6265 – volume: 43 start-page: 3561 issue: 8 year: 2019 end-page: 3577 ident: CR9 article-title: State-of-charge estimation of power lithium-ion batteries based on an embedded micro control unit using a square root cubature Kalman filter at various ambient temperatures publication-title: Int. J. Energy Res. doi: 10.1002/er.4503 – volume: 6 start-page: 418 issue: 4 year: 2018 end-page: 427 ident: CR3 article-title: SoC estimation and monitoring of li-ion cell using kalman-filter algorithm publication-title: Indonesian J. Electr. Eng. Inform. – ident: CR27 – volume: 20 start-page: 861 issue: 6 year: 2016 end-page: 866 ident: CR4 article-title: Simulation study on battery state of charge estimation using Kalman filter publication-title: J. Adv. Comput. Intell. Intell. Inform. doi: 10.20965/jaciii.2016.p0861 – volume: 36 start-page: 3531 issue: 5 year: 2011 end-page: 3540 ident: CR13 article-title: Adaptive unscented Kalman filtering for state of charge estimation of a lithium-ion battery for electric vehicles publication-title: Energy doi: 10.1016/j.energy.2011.03.059 – ident: CR23 – volume: 296 start-page: 23 year: 2015 end-page: 29 ident: CR26 article-title: A method for state-of-charge estimation of LiFePO4 batteries based on a dual-circuit state observer publication-title: J. Power Sources doi: 10.1016/j.jpowsour.2015.07.028 – volume: 249 start-page: 457 year: 2014 end-page: 462 ident: CR18 article-title: State of health estimation for lithium ion batteries based on charging curves publication-title: J. Power Sources doi: 10.1016/j.jpowsour.2013.10.114 – volume: 150 start-page: 759 year: 2018 end-page: 769 ident: CR19 article-title: Incremental capacity analysis and differential voltage analysis based state of charge and capacity estimation for lithium-ion batteries publication-title: Energy doi: 10.1016/j.energy.2018.03.023 – volume: 11 start-page: 1810 issue: 7 year: 2018 ident: CR21 article-title: Online state of charge and state of health estimation for a lithium-ion battery based on a data-model fusion method publication-title: Energies doi: 10.3390/en11071810 – volume: 207 start-page: 346 year: 2017 end-page: 353 ident: CR11 article-title: A novel method to obtain the open circuit voltage for the state of charge of lithium ion batteries in electric vehicles by using H infinity filter publication-title: Appl. Energy doi: 10.1016/j.apenergy.2017.05.136 – volume: 60 start-page: 1461 issue: 4 year: 2011 end-page: 1469 ident: CR12 article-title: State-of-charge estimation of the lithium-ion battery using an adaptive extended Kalman filter based on an improved thevenin model publication-title: IEEE Trans. Veh. Technol. doi: 10.1109/TVT.2011.2132812 – volume: 45 start-page: 975 issue: 1 year: 2021 end-page: 990 ident: CR8 article-title: Online parameters identification and state of charge estimation for lithium-ion batteries using improved adaptive dual unscented Kalman filter publication-title: Int. J. Energy Res. doi: 10.1002/er.6088 – volume: 1 start-page: 100004 year: 2019 ident: CR17 article-title: Aging characteristics-based health diagnosis and remaining useful life prognostics for lithium-ion batteries publication-title: eTransportation. doi: 10.1016/j.etran.2019.100004 – volume: 377 start-page: 161 year: 2018 end-page: 188 ident: CR15 article-title: Investigating the error sources of the online state of charge estimation methods for lithium-ion batteries in electric vehicles publication-title: J. Power Sources doi: 10.1016/j.jpowsour.2017.11.094 – volume: 443 year: 2019 ident: CR2 article-title: A comprehensive investigation of lithium-ion battery degradation performance at different discharge rates publication-title: J. Power Sources doi: 10.1016/j.jpowsour.2019.227108 – volume: 10 start-page: 2619 issue: 2 year: 2022 end-page: 2628 ident: CR14 article-title: Current measurement offset error compensation in vector-controlled SPMSM drive systems publication-title: IEEE J. Emerg. Topics Power Electron. doi: 10.1109/JESTPE.2022.3151351 – volume: 44 year: 2021 ident: CR24 article-title: Lithium-ion battery capacity estimation based on open circuit voltage identification using the iteratively reweighted least squares at different aging levels publication-title: J. Energy Storage. doi: 10.1016/j.est.2021.103487 – volume: 253 year: 2019 ident: CR28 article-title: Joint estimation of lithium-ion battery state of charge and capacity within an adaptive variable multi-timescale framework considering current measurement offset publication-title: Appl. Energy doi: 10.1016/j.apenergy.2019.113619 – volume: 43 start-page: 8230 issue: 14 year: 2019 end-page: 8241 ident: CR10 article-title: Data-driven lithium-ion battery states estimation using neural networks and particle filtering publication-title: Int. J. Energy Res. – volume: 278 start-page: 814 year: 2015 ident: 683_CR16 publication-title: J. Power Sources. doi: 10.1016/j.jpowsour.2014.08.089 – volume: 249 start-page: 457 year: 2014 ident: 683_CR18 publication-title: J. Power Sources doi: 10.1016/j.jpowsour.2013.10.114 – volume: 183 start-page: 513 year: 2016 ident: 683_CR29 publication-title: Appl. Energy doi: 10.1016/j.apenergy.2016.09.010 – volume: 43 start-page: 8230 issue: 14 year: 2019 ident: 683_CR10 publication-title: Int. J. Energy Res. – volume: 60 start-page: 1461 issue: 4 year: 2011 ident: 683_CR12 publication-title: IEEE Trans. Veh. Technol. doi: 10.1109/TVT.2011.2132812 – volume: 35 start-page: 11119 issue: 10 year: 2020 ident: 683_CR25 publication-title: IEEE Trans. Power Electron. doi: 10.1109/TPEL.2020.2978230 – volume: 1 start-page: 100004 year: 2019 ident: 683_CR17 publication-title: eTransportation. doi: 10.1016/j.etran.2019.100004 – volume: 45 start-page: 6708 issue: 5 year: 2021 ident: 683_CR7 publication-title: Int. J. Energy Res. doi: 10.1002/er.6265 – volume: 43 start-page: 3561 issue: 8 year: 2019 ident: 683_CR9 publication-title: Int. J. Energy Res. doi: 10.1002/er.4503 – volume: 36 start-page: 3531 issue: 5 year: 2011 ident: 683_CR13 publication-title: Energy doi: 10.1016/j.energy.2011.03.059 – volume: 443 year: 2019 ident: 683_CR2 publication-title: J. Power Sources doi: 10.1016/j.jpowsour.2019.227108 – ident: 683_CR6 doi: 10.1109/IEVC.2014.7056126 – volume: 44 year: 2021 ident: 683_CR24 publication-title: J. Energy Storage. doi: 10.1016/j.est.2021.103487 – volume: 377 start-page: 161 year: 2018 ident: 683_CR15 publication-title: J. Power Sources doi: 10.1016/j.jpowsour.2017.11.094 – volume: 253 year: 2019 ident: 683_CR28 publication-title: Appl. Energy doi: 10.1016/j.apenergy.2019.113619 – volume: 20 start-page: 861 issue: 6 year: 2016 ident: 683_CR4 publication-title: J. Adv. Comput. Intell. Intell. Inform. doi: 10.20965/jaciii.2016.p0861 – volume: 19 start-page: 73 year: 2018 ident: 683_CR22 publication-title: J. Energy Storage. doi: 10.1016/j.est.2018.07.006 – volume: 45 start-page: 975 issue: 1 year: 2021 ident: 683_CR8 publication-title: Int. J. Energy Res. doi: 10.1002/er.6088 – volume: 207 start-page: 346 year: 2017 ident: 683_CR11 publication-title: Appl. Energy doi: 10.1016/j.apenergy.2017.05.136 – volume: 134 start-page: 277 issue: 2 year: 2004 ident: 683_CR5 publication-title: J. Power Sources. doi: 10.1016/j.jpowsour.2004.02.033 – volume: 11 start-page: 1810 issue: 7 year: 2018 ident: 683_CR21 publication-title: Energies doi: 10.3390/en11071810 – volume: 78 start-page: 834 year: 2017 ident: 683_CR1 publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2017.05.001 – volume: 113 start-page: 106 year: 2014 ident: 683_CR30 publication-title: Appl. Energy doi: 10.1016/j.apenergy.2013.07.008 – ident: 683_CR27 doi: 10.1109/CCTA.2017.8062643 – volume: 4 start-page: 135 issue: 1 year: 2018 ident: 683_CR20 publication-title: IEEE Trans. Transp Electr. doi: 10.1109/TTE.2017.2776558 – volume: 150 start-page: 759 year: 2018 ident: 683_CR19 publication-title: Energy doi: 10.1016/j.energy.2018.03.023 – ident: 683_CR23 doi: 10.1109/VPPC.2016.7791782 – volume: 10 start-page: 2619 issue: 2 year: 2022 ident: 683_CR14 publication-title: IEEE J. Emerg. Topics Power Electron. doi: 10.1109/JESTPE.2022.3151351 – volume: 6 start-page: 418 issue: 4 year: 2018 ident: 683_CR3 publication-title: Indonesian J. Electr. Eng. Inform. – volume: 296 start-page: 23 year: 2015 ident: 683_CR26 publication-title: J. Power Sources doi: 10.1016/j.jpowsour.2015.07.028 |
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| Title | Joint estimation for SOC and capacity after current measurement offset redress with two-stage forgetting factor recursive least square method |
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