scholarly journals A novel safety anticipation estimation method for the aerial lithium-ion battery pack based on the real-time detection and filtering

2018 ◽  
Vol 185 ◽  
pp. 187-197 ◽  
Author(s):  
Shunli Wang ◽  
Carlos Fernandez ◽  
Mingjie Chen ◽  
Lu Wang ◽  
Jie Su
Keyword(s):  
Lithium Ion Battery ◽  
Real Time ◽  
Estimation Method ◽  
Lithium Ion ◽  
Battery Pack ◽  
The Real ◽  
Real Time Detection

scholarly journals An integrated online adaptive state of charge estimation approach of high-power lithium-ion battery packs

2017 ◽  
Vol 40 (6) ◽  
pp. 1892-1910 ◽  
Author(s):  
Shunli Wang ◽  
Carlos Fernandez ◽  
Liping Shang ◽  
Zhanfeng Li ◽  
Huifang Yuan
Keyword(s):  
Lithium Ion Battery ◽  
Real Time ◽  
High Power ◽  
Computational Cost ◽  
Estimation Method ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
State Of Charge ◽  
The Real ◽  
Soc Estimation

A novel online adaptive state of charge (SOC) estimation method is proposed, aiming to characterize the capacity state of all the connected cells in lithium-ion battery (LIB) packs. This method is realized using the extended Kalman filter (EKF) combined with Ampere-hour (Ah) integration and open circuit voltage (OCV) methods, in which the time-scale implementation is designed to reduce the computational cost and accommodate uncertain or time-varying parameters. The working principle of power LIBs and their basic characteristics are analysed by using the combined equivalent circuit model (ECM), which takes the discharging current rates and temperature as the core impacts, to realize the estimation. The original estimation value is initialized by using the Ah integral method, and then corrected by measuring the cell voltage to obtain the optimal estimation effect. Experiments under dynamic current conditions are performed to verify the accuracy and the real-time performance of this proposed method, the analysed result of which indicates that its good performance is in line with the estimation accuracy and real-time requirement of high-power LIB packs. The proposed multi-model SOC estimation method may be used in the real-time monitoring of the high-power LIB pack dynamic applications for working state measurement and control.

The Numerical Simulation of Thermal Abuse and Runaway in Lithium Ion Battery Pack

2021 ◽  
Vol 105 (1) ◽  
pp. 549-559
Author(s):  
Petr Vyroubal ◽  
Tomas Kazda ◽  
Martin Mačák
Keyword(s):  
Numerical Simulation ◽  
Lithium Ion Battery ◽  
Computer Simulations ◽  
Science And Technology ◽  
Lithium Ion ◽  
Battery Pack ◽  
Experimental Measurements ◽  
The Real ◽  
Charging And Discharging Processes ◽  
Real Test

Computer simulations today play an important role in the field of science and technology. The same is true in the field of electrochemistry, where they are used mainly to model the charging and discharging processes in various types of batteries, at the various loads and temperature processes associated with it. This article deals with the possibility of modeling thermal abuse, which subsequently leads to the thermal runaway effect in a lithium ion battery pack. The simulation is accompanied by experimental measurements and comparison of the original results from the real test and simulation.

An online SOC and capacity estimation method for aged lithium-ion battery pack considering cell inconsistency

2020 ◽  
Vol 29 ◽  
pp. 101250 ◽  
Author(s):  
Chaofan Yang ◽  
Xueyuan Wang ◽  
Qiaohua Fang ◽  
Haifeng Dai ◽  
Yaqian Cao ◽  
...  
Keyword(s):  
Lithium Ion Battery ◽  
Estimation Method ◽  
Lithium Ion ◽  
Battery Pack ◽  
Capacity Estimation

scholarly journals Robust Online State of Charge Estimation of Lithium-Ion Battery Pack Based on Error Sensitivity Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Ting Zhao ◽  
Jiuchun Jiang ◽  
Caiping Zhang ◽  
Kai Bai ◽  
Na Li
Keyword(s):  
Lithium Ion Battery ◽  
Estimation Error ◽  
Estimation Method ◽  
Dynamic Test ◽  
Lithium Ion ◽  
Vital Role ◽  
State Of Charge ◽  
Battery Pack ◽  
Estimation Accuracy ◽  
Soc Estimation

Accurate and reliable state of charge (SOC) estimation is a key enabling technique for large format lithium-ion battery pack due to its vital role in battery safety and effective management. This paper tries to make three contributions to existing literatures through robust algorithms. (1) Observer based SOC estimation error model is established, where the crucial parameters on SOC estimation accuracy are determined by quantitative analysis, being a basis for parameters update. (2) The estimation method for a battery pack in which the inconsistency of cells is taken into consideration is proposed, ensuring all batteries’ SOC ranging from 0 to 1, effectively avoiding the battery overcharged/overdischarged. Online estimation of the parameters is also presented in this paper. (3) The SOC estimation accuracy of the battery pack is verified using the hardware-in-loop simulation platform. The experimental results at various dynamic test conditions, temperatures, and initial SOC difference between two cells demonstrate the efficacy of the proposed method.

The Internal Resistance Characteristics of Lithium-Ion Battery Based on HPPC Method

2012 ◽  
Vol 455-456 ◽  
pp. 246-251 ◽  
Author(s):  
Ting Ting Lou ◽  
Wei Ge Zhang ◽  
Hong Yu Guo ◽  
Ji Song Wang
Keyword(s):  
Lithium Ion Battery ◽  
Real Time ◽  
Lithium Ion ◽  
Internal Resistance ◽  
Battery Pack ◽  
Battery Management System ◽  
Battery Management ◽  
Resistance Characteristic ◽  
Power Prediction ◽  
Ohmic Resistance

The real time power prediction of power battery pack used in electric vehicles is a difficulty of the battery management system. The internal resistance characteristic of the battery can be used to achieve the prediction of battery power based on the close relationship between the value of real time power and internal resistance. In this paper, the internal resistance characteristic of the power type lithium-ion battery are tested with HPPC(hybrid pulse power characterization) method, the relationship curves between the capacity or internal resistance of the battery and temperature are given, the temperature properties of the capacity and the ohmic resistance of the battery are obtained, and the basis of online resistance identification and peak power computation for the battery pack is provided.

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