scholarly journals Modeling and validation of lithium-ion battery with initial state of charge estimation

2021 ◽  
Vol 21 (3) ◽  
pp. 1317
Author(s):  
Ali Mohsen Alsabari ◽  
M.K Hassan ◽  
Azura CS ◽  
Ribhan Zafira
Keyword(s):  
Lithium Ion Battery ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Industrial Applications ◽  
State Of Charge ◽  
Lookup Table ◽  
Maximum Relative Error ◽  
Initial State ◽  
Internal Parameters ◽  
Terminal Voltage

The modeling of lithium-ion battery is an important element to the management of batteries in industrial applications. Various models have been studied and investigated, ranging from simple to complex. The second-order equivalent circuit model was studied and investigated since the dynamic behavior of the battery is fully characterized. The simulation model was built in Matlab Simulink using the Kirchhoff Laws principle in mathematical equations, while the battery's internal parameters were identified by using the BTS4000 (Battery tester) device. To estimate the full state of charge (SOC), the initial state of charge (SOC0) must be identified or measured. Hence, this paper seeks for the SOC estimation by using experimental terminal voltage data and SOC with Matlab lookup table. Then, the simulated terminal voltage, as well as the SOC of the battery are compared and validated against measured data. The maximum relative error of 0.015 V and 2% for terminal voltage and SOC respectively shows that the proposed model is accurate and relevant based on the error analysis.

scholarly journals Effects of State-of-Charge and Penetration Location on Variations in Temperature and Terminal Voltage of a Lithium-Ion Battery Cell during Penetration Tests

Batteries ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. 81
Author(s):  
Yiqun Liu ◽  
Yitian Li ◽  
Y. Gene Liao ◽  
Ming-Chia Lai
Keyword(s):  
Experimental Data ◽  
Short Circuit ◽  
Lithium Ion ◽  
State Of Charge ◽  
Initial State ◽  
Battery Cell ◽  
Temperature Increment ◽  
Terminal Voltage ◽  
Internal Short Circuit ◽  
Penetration Tests

The nail penetration test has been widely adopted as a battery safety test for reproducing internal short-circuits. In this paper, the effects of cell initial State-of-Charge (SOC) and penetration location on variations in cell temperature and terminal voltage during penetration tests are investigated. Three different initial SOCs (10%, 50%, and 90%) and three different penetration locations (one is at the center of the cell, the other two are close to the edge of the cell) are used in the tests. Once the steel cone starts to penetrate the cell, the cell terminal voltage starts to drop due to the internal short-circuit. The penetration tests with higher initial cell SOCs have larger cell surface temperature increases during the tests. Also, the penetration location always has the highest temperature increment during all penetration tests, which means the heat source is always at the penetration location. The absolute temperature increment at the penetration location is always higher when the penetration is close to the edge of the cell, compared to when the penetration is at the center of the cell. The heat generated at the edges of the cell is more difficult to dissipate. Additionally, a battery cell internal short-circuit model with different penetration locations is built in ANSYS Fluent, based on the specifications and experimental data of the tested battery cells. The model is validated with an acceptable discrepancy range by using the experimental data. Simulated data shows that the temperature gradually reduces from penetration locations to their surroundings. The gradients of the temperature distributions are much larger closer to the penetration locations. Overall, this paper provides detailed information on the temperature and terminal voltage variations of a lithium-ion polymer battery cell with large capacity and high power under penetration tests. The presented information can be used for assessing the safety of the onboard battery pack of electric vehicles.

scholarly journals Implementation of Coulomb Counting Method for Estimating the State of Charge of Lithium-Ion Battery

2021 ◽  
pp. 1-8
Author(s):  
Kevin C. Ndeche ◽  
Stella O. Ezeonu
Keyword(s):  
Lithium Ion Battery ◽  
Coulombic Efficiency ◽  
Lithium Ion ◽  
The State ◽  
State Of Charge ◽  
Battery Management System ◽  
Counting Method ◽  
Voltage Measurement ◽  
Initial State ◽  
Battery Capacity

An accurate estimate of the state of charge, which describes the remaining percentage of a battery’s capacity, has been an important and ever existing problem since the invention of the electrochemical cell. State of charge estimation is one of the important function of a battery management system which ensures the safe, efficient and reliable operation of a battery. In this paper, the coulomb counting method is implemented for the estimation of the state of charge of lithium-ion battery. The hardware comprises an Arduino based platform for control and data processing, and a 16-bit analog to digital converter for current and voltage measurement. The embedded algorithm initializes with a self-calibration phase, during which the battery capacity, coulombic efficiency and initial state of charge are evaluated. The initial state of charge is determined at the fully charged state (100% state of charge) or the fully discharged state (0% state of charge). The cumulative error of this method was addressed by routine recalibration of the capacity, coulombic efficiency and state of charge at the fully-charged and fully-discharged states. The algorithm was validated by charging/discharging a lithium-ion battery through fifty complete cycles and evaluating the error in the estimated state of charge. The result shows a mean absolute error of 0.35% in the estimated state of charge during the test. Further analysis, considering prolonged battery operation without parameters recalibration, suggests that error in the coulombic efficiency term contributes the most to the increasing error in the estimated state of charge with each cycle.

scholarly journals Experimental design for an enhanced parametric modeling of supercapacitor equivalent circuit model

2021 ◽  
Vol 23 (1) ◽  
pp. 63
Author(s):  
Ali Mohsen Alsabari ◽  
M. K Hassan ◽  
Azura CS ◽  
Ribhan Zafira
Keyword(s):  
Experimental Design ◽  
Equivalent Circuit ◽  
Equivalent Circuit Model ◽  
Structure Design ◽  
Parametric Modeling ◽  
Circuit Model ◽  
Maximum Relative Error ◽  
Internal Parameters ◽  
Terminal Voltage ◽  
Real Challenge

The modelling of the supercapacitor (SC) plays an important role for the industrial application with many model representations such as electrical, chemical, and electrochemical models. Among one of those models are the equivalent circuit model which has been used to describe the real-time (charging/discharging) operation characteristics of the SC. Apart of its mathematical complexity, the time-consuming experimentally is also a real challenge for obtaining the internal parameters values for the SC. Choices of test equipment with a structure design of experiment also play important criteria affect the accuracy of the model. This research emphasis on a structured of experimental design for SC modelling by using Neware battery tester. The experimental exercise to attain internal parameters of the SC are described and discussed in the paper. The findings were benchmarked with an empirical model of previous researchers. The terminal voltage of SC was validated via experiment with maximum relative error of 0.045%. The model successfully reproduce the SC dynamic behavior during the charge/discharge phase which indicates the proposed method and model accuracy.

An Improved Test Method of LiFePO4/Graphene Hybrid Cathode Lithium-Ion Battery and the State of Charge Estimation

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Meiying Li ◽  
Zhiping Guo ◽  
Yuan Li ◽  
Wenliang Wu
Keyword(s):  
Lithium Ion Battery ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Open Circuit ◽  
The State ◽  
State Of Charge ◽  
Least Square ◽  
Test Method ◽  
Battery Management System ◽  
Battery Management

Abstract The state of charge (SoC) of the battery is a typical characterization of the operating state of the battery and criterion for the battery management system (BMS) control strategy, which must be evaluated precisely. The establishment of an accurate algorithm of SoC estimation is of great significance for BMS, which can help the driver judge the endurance mileage of electric vehicle (EV) correctly. In this paper, a second-order resistor-capacity (RC) equivalent circuit model is selected to characterize the electrical characteristics based on the electrochemical model of the LiFePO4/graphene (LFP/G) hybrid cathode lithium-ion battery. Moreover, seven open circuit voltage (OCV) models are compared and the best one of them is used to simulate the dynamic characteristics of the battery. It is worth mentioning that an improved test method is proposed, which is combined with least square for parameters identification. In addition, the extended Kalman filter (EKF) algorithm is selected to estimate the SoC during the charging and discharging processes. The simulation results show that the EKF algorithm has the higher accuracy and rapidity than the KF algorithm.

scholarly journals Quadrature Kalman filter–based state of charge estimation for lithium-ion battery

2020 ◽  
Vol 12 (7) ◽  
pp. 168781402094269
Author(s):  
Mengtao Huang ◽  
Chao Wang ◽  
Bao Liu ◽  
Fan Wang ◽  
Jingting Wang
Keyword(s):  
Kalman Filter ◽  
Lithium Ion Battery ◽  
Extended Kalman Filter ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Quadrature Rule ◽  
State Of Charge ◽  
Gauss Hermite Quadrature ◽  
State Of Charge Estimation ◽  
Unscented Filter

This article presents an approach to lithium-ion battery state of charge estimation based on the quadrature Kalman filter. Among the existing state of charge estimation approaches, the extended Kalman filter–based state of charge and unscented filter–based state of charge algorithms are influenced by the linearization or the solution of sigma points. The proposed quadrature Kalman filter–based state of charge algorithm avoids these problems. Specifically, the battery system equations are built based on the second-order resistance–capacitance equivalent circuit model, and the parameters are identified according to the hybrid pulse power characterization discharging test. Then, the quadrature points and corresponding weights are defined by the Gauss–Hermite quadrature rule, and the Kronecker tensor product is adopted to solve the points of multivariate. In addition, the stability of quadrature Kalman filter–based state of charge is verified. Finally, the simulation is carried out under the discharging and urban dynamometer driving schedule condition, which demonstrates that the quadrature Kalman filter–based state of charge algorithm has a better performance compared with extended Kalman filter–based state of charge and unscented filter–based state of charge.

scholarly journals Estimation of State of Charge for Lithium-Ion Battery Based on Finite Difference Extended Kalman Filter

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Ze Cheng ◽  
Jikao Lv ◽  
Yanli Liu ◽  
Zhihao Yan
Keyword(s):  
Kalman Filter ◽  
Finite Difference ◽  
Lithium Ion Battery ◽  
Extended Kalman Filter ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Nonlinear Dynamic System ◽  
State Of Charge ◽  
Energy Utilization ◽  
Accurate Estimation

An accurate estimation of the state of charge (SOC) of the battery is of great significance for safe and efficient energy utilization of electric vehicles. Given the nonlinear dynamic system of the lithium-ion battery, the parameters of the second-order RC equivalent circuit model were calibrated and optimized using a nonlinear least squares algorithm in the Simulink parameter estimation toolbox. A comparison was made between this finite difference extended Kalman filter (FDEKF) and the standard extended Kalman filter in the SOC estimation. The results show that the model can essentially predict the dynamic voltage behavior of the lithium-ion battery, and the FDEKF algorithm can maintain good accuracy in the estimation process and has strong robustness against modeling error.

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.

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