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2020 | OriginalPaper | Chapter

5. State Estimation of Battery System

Author : Rui Xiong

Published in: Battery Management Algorithm for Electric Vehicles

Publisher: Springer Singapore

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Abstract

A battery system mainly consists of battery modules, a BMS, and a battery pack case. A battery cell has maximum available capacity and SOC, the estimation of which has clear reference values and evaluation methods.

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Literature
1.
go back to reference Ye M, Song X, Xiong R, Sun F (2019) A novel dynamic performance analysis and evaluation model of series-parallel connected battery pack for electric vehicles. IEEE Access 7(1):14256–14265CrossRef Ye M, Song X, Xiong R, Sun F (2019) A novel dynamic performance analysis and evaluation model of series-parallel connected battery pack for electric vehicles. IEEE Access 7(1):14256–14265CrossRef
2.
go back to reference Xiong R (2014) Estimation of battery pack state for electric vehicles using model-data fusion approach. Ph.D. dissertation. Beijing Institute of Technology, Beijing Xiong R (2014) Estimation of battery pack state for electric vehicles using model-data fusion approach. Ph.D. dissertation. Beijing Institute of Technology, Beijing
3.
go back to reference Liang L (2018) Study on the optimization of battery pack based on inconsistency analysis. M.A. thesis. Beijing Institute of Technology, Beijing Liang L (2018) Study on the optimization of battery pack based on inconsistency analysis. M.A. thesis. Beijing Institute of Technology, Beijing
4.
go back to reference Xiong R, Sun F, Gong X (2013) Adaptive state of charge estimator for lithium-ion cells series battery pack in electric vehicles. J Power Sources 242(22):699–713CrossRef Xiong R, Sun F, Gong X (2013) Adaptive state of charge estimator for lithium-ion cells series battery pack in electric vehicles. J Power Sources 242(22):699–713CrossRef
5.
go back to reference Sun F, Xiong R, He H (2016) A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique. Appl Energy 162:1399–1409CrossRef Sun F, Xiong R, He H (2016) A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique. Appl Energy 162:1399–1409CrossRef
6.
go back to reference Gong X, Xiong R, Mi CC (2016) A data-driven bias-correction-method-based lithium-ion battery modeling approach for electric vehicle applications. IEEE Transa Ind Appl 52(2):1759–1765 Gong X, Xiong R, Mi CC (2016) A data-driven bias-correction-method-based lithium-ion battery modeling approach for electric vehicle applications. IEEE Transa Ind Appl 52(2):1759–1765
7.
go back to reference Chen X, Lei H, Xiong R (2018) A bias correction based state-of-charge estimation method for multi-cell battery pack under different working conditions. IEEE Access 6:78184–78192CrossRef Chen X, Lei H, Xiong R (2018) A bias correction based state-of-charge estimation method for multi-cell battery pack under different working conditions. IEEE Access 6:78184–78192CrossRef
8.
go back to reference Sun F, Xiong R (2015) A novel dual-scale cell state-of-charge estimation approach for series-connected battery pack used in electric vehicles. J Power Sources 274:582–594CrossRef Sun F, Xiong R (2015) A novel dual-scale cell state-of-charge estimation approach for series-connected battery pack used in electric vehicles. J Power Sources 274:582–594CrossRef
9.
go back to reference Wang J, Xiong R, Li L, Fang Y (2018) A comparative analysis and validation for double-filters-based state of charge estimators using battery-in-the-loop approach. Appl Energy 229:648–659CrossRef Wang J, Xiong R, Li L, Fang Y (2018) A comparative analysis and validation for double-filters-based state of charge estimators using battery-in-the-loop approach. Appl Energy 229:648–659CrossRef
10.
go back to reference Xiong R, Gong X, Mi CC, Sun F (2013) A robust state-of-charge estimator for multiple types of lithium-ion batteries using adaptive extended Kalman filter. J Power Sources 243:805–816CrossRef Xiong R, Gong X, Mi CC, Sun F (2013) A robust state-of-charge estimator for multiple types of lithium-ion batteries using adaptive extended Kalman filter. J Power Sources 243:805–816CrossRef
11.
go back to reference Sun F, Xiong R, He H (2012) Model-based dynamic multi-parameter method for peak power estimation of lithium–ion batteries. Appl Energy 96(3):378–386CrossRef Sun F, Xiong R, He H (2012) Model-based dynamic multi-parameter method for peak power estimation of lithium–ion batteries. Appl Energy 96(3):378–386CrossRef
12.
go back to reference He H, Xiong R, Fan J (2011) Evaluation of lithium-ion battery equivalent circuit models for state of charge estimation by an experimental approach. Energies 4(4):582–598CrossRef He H, Xiong R, Fan J (2011) Evaluation of lithium-ion battery equivalent circuit models for state of charge estimation by an experimental approach. Energies 4(4):582–598CrossRef
13.
go back to reference Roscher MA, Sauer DU (2011) Dynamic electric behavior and open-circuit-voltage modeling of LiFePO4-based lithium ion secondary batteries. J Power Sources 196(1):331–336CrossRef Roscher MA, Sauer DU (2011) Dynamic electric behavior and open-circuit-voltage modeling of LiFePO4-based lithium ion secondary batteries. J Power Sources 196(1):331–336CrossRef
14.
go back to reference Kim J, Lee S, Cho BH (2011) Discrimination of li-ion batteries based on hamming network using discharging–charging voltage pattern recognition for improved state-of-charge estimation. J Power Sources 196(4):2227–2240CrossRef Kim J, Lee S, Cho BH (2011) Discrimination of li-ion batteries based on hamming network using discharging–charging voltage pattern recognition for improved state-of-charge estimation. J Power Sources 196(4):2227–2240CrossRef
15.
go back to reference He H, Xiong R, Chang YH (2010) Dynamic modeling and simulation on a hybrid power system for electric vehicle applications. Energies 3(11):1821–1830CrossRef He H, Xiong R, Chang YH (2010) Dynamic modeling and simulation on a hybrid power system for electric vehicle applications. Energies 3(11):1821–1830CrossRef
16.
go back to reference Xiong R, He H, Sun F (2013) Model-based state of charge and peak power capability joint estimation of lithium-ion battery in plug-in hybrid electric vehicles. J Power Sources 229(9):159–169CrossRef Xiong R, He H, Sun F (2013) Model-based state of charge and peak power capability joint estimation of lithium-ion battery in plug-in hybrid electric vehicles. J Power Sources 229(9):159–169CrossRef
17.
go back to reference Xiong R, Sun F, He H (2013) A data-driven adaptive state of charge and power capability joint estimator of lithium-ion polymer battery used in electric vehicles. Energy 63(1):95–308 Xiong R, Sun F, He H (2013) A data-driven adaptive state of charge and power capability joint estimator of lithium-ion polymer battery used in electric vehicles. Energy 63(1):95–308
18.
go back to reference Xiong R, He H, Sun F, Zhao K (2012) Online estimation of peak power capability of Li-Ion batteries in electric vehicles by a hardware-in-loop approach. Energies 5(5):1455–1469CrossRef Xiong R, He H, Sun F, Zhao K (2012) Online estimation of peak power capability of Li-Ion batteries in electric vehicles by a hardware-in-loop approach. Energies 5(5):1455–1469CrossRef
19.
go back to reference Sun F, Xiong R, He H (2014) Estimation of state-of-charge and state-of-power capability of lithium-ion battery considering varying health conditions. J Power Sources 259:166–176CrossRef Sun F, Xiong R, He H (2014) Estimation of state-of-charge and state-of-power capability of lithium-ion battery considering varying health conditions. J Power Sources 259:166–176CrossRef
20.
go back to reference Lu J, Chen Z, Yang Y, Lv M (2018) Online estimation of state of power for lithium-ion batteries in electric vehicles using genetic algorithm. IEEE Access 6:20868–20880CrossRef Lu J, Chen Z, Yang Y, Lv M (2018) Online estimation of state of power for lithium-ion batteries in electric vehicles using genetic algorithm. IEEE Access 6:20868–20880CrossRef
21.
go back to reference Lu, J (2018) Research on state of power estimation of Lithium battery and its applications in energy management. M.A. thesis. Northeastern University, Shenyang Lu, J (2018) Research on state of power estimation of Lithium battery and its applications in energy management. M.A. thesis. Northeastern University, Shenyang
Metadata
Title
State Estimation of Battery System
Author
Rui Xiong
Copyright Year
2020
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-15-0248-4_5