Field programmable gate arrays implementation of a Kalman filter based state of charge observer of a lithium ion battery pack

被引:6
作者
Benkara, Khadija El Kadri [1 ]
Alchami, Amalie [1 ]
Eddine, Achraf Nasser [1 ]
Bakaraki, Ghada [1 ]
Forgez, Christophe [1 ]
机构
[1] Univ Technol Compiegne, Roberval Mech Energy & Elect, Ctr Recherche Royallie, CS 60319, Compiegne, F-60203, France
关键词
Energy management; Lithium-Ion batteries; Battery Management System (BMS); State Of Charge (SOC Estimation); Extended Kalman Filter (EKF) algorithms; Field Programmable Gate Arrays (FPGA; implementation; Real-time Applications; MANAGEMENT; SIMULATION;
D O I
10.1016/j.est.2023.107860
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper presents a study on the state of charge observation of lithium-Ion batteries for energy management in embedded applications. The knowledge of the state of charge is fundamental for the safety and optimal usage of these batteries. The study focuses on the development and implementation of a Kalman filter-based observer algorithm on a Spartan 6 FPGA that can accurately estimate the state of charge of a battery, even if it is initialized differently from its actual state. In this paper we have focused on the opportunities of FPGA for fast calculation which allow to use the FPGA as a slave component in a BMS and allow to observe the SOC a great deal of cells with a low cost. The implementation of this observer on a low-cost FPGA can lead to cost reduction for battery management systems in various applications, such as electric cars and any other systems requiring the observation of the state of charge of a battery pack. The observer model was validated through simulations and real-time testing. This study presents a promising approach to accurately estimate the state of charge of Lithium-Ion batteries for efficient energy management in various applications.
引用
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页数:11
相关论文
共 54 条
[1]  
Abhinav K., 2021, 2021 INT C INT TECHN, DOI [10.1109/conit51480.2021.9498495, DOI 10.1109/CONIT51480.2021.9498495]
[2]  
Babu D, 2012, INT CONF INTELL SYST, P363, DOI 10.1109/ISDA.2012.6416565
[3]   Review of building integrated applications of photovoltaic and solar thermal systems [J].
Baljit, S. S. S. ;
Chan, Hoy-Yen ;
Sopian, Kamaruzzaman .
JOURNAL OF CLEANER PRODUCTION, 2016, 137 :677-689
[4]  
Baronti F., 2013, P IEEE INT S IND ELE
[5]  
Baronti F, 2014, IEEE IND ELEC, P5641, DOI 10.1109/IECON.2014.7049364
[6]   Critical review of state of health estimation methods of Li-ion batteries for real applications [J].
Berecibar, M. ;
Gandiaga, I. ;
Villarreal, I. ;
Omar, N. ;
Van Mierlo, J. ;
Van den Bossche, P. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2016, 56 :572-587
[7]   Impedance-based simulation models of supercapacitors and Li-ion batteries for power electronic applications [J].
Buller, S ;
Thele, M ;
De Doncker, RWAA ;
Karden, E .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2005, 41 (03) :742-747
[8]  
Chen GW, 2019, CHIN CONTR CONF, P697, DOI [10.23919/ChiCC.2019.8865913, 10.23919/chicc.2019.8865913]
[9]   Aging aware operation of lithium-ion battery energy storage systems: A review [J].
Collath, Nils ;
Tepe, Benedikt ;
Englberger, Stefan ;
Jossen, Andreas ;
Hesse, Holger .
JOURNAL OF ENERGY STORAGE, 2022, 55
[10]   A combined state-of-charge estimation method for lithium-ion battery using an improved BGRU network and UKF [J].
Cui, Zhenhua ;
Kang, Le ;
Li, Liwei ;
Wang, Licheng ;
Wang, Kai .
ENERGY, 2022, 259