Lithium-Ion Battery SOC Estimation and Hardware-in-the-Loop Simulation Based on EKF

被引:27
作者
Guo, Lin [1 ]
Li, Junqiu [1 ]
Fu, Zijian [1 ]
机构
[1] Beijing Inst Technol, Collaborat Innovat Ctr Elect Vehicles Beijing, Beijing 100081, Peoples R China
来源
INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS | 2019年 / 158卷
关键词
state of charge; parameter identification; Extended Kalman Filter; hardware-in-the-loop; bench test; MANAGEMENT-SYSTEMS; CHARGE ESTIMATION; STATE; PACKS; MODELS;
D O I
10.1016/j.egypro.2019.02.009
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
It is difficult to estimate accurate SoC of power battery and meet the practical application due to the complexity of the algorithm. To promote the real-time and feasibility of the SoC algorithm, this paper proposes a set of solutions and verification taking lithium-ion battery as an example: First, an equivalent circuit model is established and a series of power battery tests were designed to provide data support for battery model and off-line parameter identification. In addition, the Extended Kalman Filter (EKF) algorithm is used for the SoC Estimation. To verify the feasibility and effectiveness of the SoC algorithm in the battery management system (BMS). The paper builds the model with chip computing capabilities and performs hardware-in-the-loop simulation tests using SpeedGoat as a platform and the Real-Time Workshop as an automatic code generation tool. Furthermore, the bench experiment of the power battery module is set up to verify and test the SoC algorithm. The results show that the proposed SoC estimation is more practical with the actual SoC estimation error less than 5%. (C) 2019 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:2599 / 2604
页数:6
相关论文
共 12 条
[1]   Energy management strategy research on a hybrid power system by hardware-in-loop experiments [J].
He, Hongwen ;
Xiong, Rui ;
Zhao, Kai ;
Liu, Zhentong .
APPLIED ENERGY, 2013, 112 :1311-1317
[2]   Comparison study on the battery models used for the energy management of batteries in electric vehicles [J].
He, Hongwen ;
Xiong, Rui ;
Guo, Hongqiang ;
Li, Shuchun .
ENERGY CONVERSION AND MANAGEMENT, 2012, 64 :113-121
[3]   State-of-Charge Estimation of the Lithium-Ion Battery Using an Adaptive Extended Kalman Filter Based on an Improved Thevenin Model [J].
He, Hongwen ;
Xiong, Rui ;
Zhang, Xiaowei ;
Sun, Fengchun ;
Fan, JinXin .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2011, 60 (04) :1461-1469
[4]   Evaluation of Lithium-Ion Battery Equivalent Circuit Models for State of Charge Estimation by an Experimental Approach [J].
He, Hongwen ;
Xiong, Rui ;
Fan, Jinxin .
ENERGIES, 2011, 4 (04) :582-598
[5]   Battery algorithm verification and development using hardware-in-the-loop testing [J].
He, Yongsheng ;
Liu, Wei ;
Koch, Brain J. .
JOURNAL OF POWER SOURCES, 2010, 195 (09) :2969-2974
[6]   Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs - Part 2. Modeling and identification [J].
Plett, GL .
JOURNAL OF POWER SOURCES, 2004, 134 (02) :262-276
[7]   Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs - Part 1. Background [J].
Plett, GL .
JOURNAL OF POWER SOURCES, 2004, 134 (02) :252-261
[8]  
Plett GL, 2004, J POWER SOURCES, V134, P277, DOI 10.1016/j jpowsour.2004.02.033
[9]   Hardware-in-the-loop simulation for the design and verification of the control system of a series-parallel hybrid electric city-bus [J].
Wang, Lei ;
Zhang, Yong ;
Yin, Chengliang ;
Zhang, Hu ;
Wang, Cunlei .
SIMULATION MODELLING PRACTICE AND THEORY, 2012, 25 :148-162
[10]   A data-driven based adaptive state of charge estimator of lithium-ion polymer battery used in electric vehicles [J].
Xiong, Rui ;
Sun, Fengchun ;
Gong, Xianzhi ;
Gao, Chenchen .
APPLIED ENERGY, 2014, 113 :1421-1433