scholarly journals Capacity Fade in Lithium-Ion Batteries and Cyclic Aging over Various State-of-Charge Ranges

2019 ◽  
Vol 11 (23) ◽  
pp. 6697 ◽  
Author(s):  
Sophia Gantenbein ◽  
Michael Schönleber ◽  
Michael Weiss ◽  
Ellen Ivers-Tiffée
Keyword(s):  
Particle Surface ◽  
High Capacity ◽  
Lithium Ion ◽  
Open Circuit ◽  
Operating Conditions ◽  
State Of Charge ◽  
Capacity Fade ◽  
Active Electrode ◽  
Capacity Loss ◽  
Aging Mechanisms

In order to develop long-lifespan batteries, it is of utmost importance to identify the relevant aging mechanisms and their relation to operating conditions. The capacity loss in a lithium-ion battery originates from (i) a loss of active electrode material and (ii) a loss of active lithium. The focus of this work is the capacity loss caused by lithium loss, which is irreversibly bound to the solid electrolyte interface (SEI) on the graphite surface. During operation, the particle surface suffers from dilation, which causes the SEI to break and then be rebuilt, continuously. The surface dilation is expected to correspond with the well-known graphite staging mechanism. Therefore, a high-power 2.6 Ah graphite/LiNiCoAlO2 cell (Sony US18650VTC5) is cycled at different, well-defined state-of-charge (SOC) ranges, covering the different graphite stages. An open circuit voltage model is applied to quantify the loss mechanisms (i) and (ii). The results show that the lithium loss is the dominant cause of capacity fade under the applied conditions. They experimentally prove the important influence of the graphite stages on the lifetime of a battery. Cycling the cell at SOCs slightly above graphite Stage II results in a high active lithium loss and hence in a high capacity fade.

scholarly journals OCV Hysteresis in Li-Ion Batteries including Two-Phase Transition Materials

2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
Author(s):  
Michael A. Roscher ◽  
Oliver Bohlen ◽  
Jens Vetter
Keyword(s):  
Phase Transition ◽  
Electrode Materials ◽  
Open Circuit Voltage ◽  
Lithium Ion ◽  
Open Circuit ◽  
State Of Charge ◽  
High Current ◽  
Two Phase ◽  
Active Electrode ◽  
Li Ion

The relation between batteries' state of charge (SOC) and open-circuit voltage (OCV) is a specific feature of electrochemical energy storage devices. Especially NiMH batteries are well known to exhibit OCV hysteresis, and also several kinds of lithium-ion batteries show OCV hysteresis, which can be critical for reliable state estimation issues. Electrode potential hysteresis is known to result from thermodynamical entropic effects, mechanical stress, and microscopic distortions within the active electrode materials which perform a two-phase transition during lithium insertion/extraction. Hence, some Li-ion cells including two-phase transition active materials show pronounced hysteresis referring to their open-circuit voltage. This work points out how macroscopic effects, that is, diffusion limitations, superimpose the latte- mentioned microscopic mechanisms and lead to a shrinkage of OCV hysteresis, if cells are loaded with high current rates. To validate the mentioned interaction, Li-ion cells' state of charge is adjusted to 50% with various current rates, beginning from the fully charged and the discharged state, respectively. As a pronounced difference remains between the OCV after charge and discharge adjustment, obviously the hysteresis vanishes as the target SOC is adjusted with very high current rate.

scholarly journals Recursive State of Charge and State of Health Estimation Method for Lithium-Ion Batteries Based on Coulomb Counting and Open Circuit Voltage

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1811 ◽  
Author(s):  
Alejandro Gismero ◽  
Erik Schaltz ◽  
Daniel-Ioan Stroe
Keyword(s):  
Open Circuit Voltage ◽  
Estimation Method ◽  
Lithium Ion ◽  
Open Circuit ◽  
Operating Conditions ◽  
State Of Charge ◽  
Recursive Least Squares ◽  
State Of Health ◽  
Operation Conditions ◽  
Extensive Test

The state of charge (SOC) and state of health (SOH) are two crucial indicators needed for a proper and safe operation of the battery. Coulomb counting is one of the most adopted and straightforward methods to calculate the SOC. Although it can be implemented for all kinds of applications, its accuracy is strongly dependent on the operation conditions. In this work, the behavior of the batteries at different current and temperature conditions is analyzed in order to adjust the charge measurement according to the battery efficiency at the specific operating conditions. The open-circuit voltage (OCV) is used to reset the SOC estimation and prevent the error accumulation. Furthermore, the SOH is estimated by evaluating the accumulated charge between two different SOC using a recursive least squares (RLS) method. The SOC and SOH estimations are verified through an extensive test in which the battery is subjected to a dynamic load profile at different temperatures.

scholarly journals A Study on the Open Circuit Voltage and State of Charge Characterization of High Capacity Lithium-Ion Battery Under Different Temperature

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2408 ◽  
Author(s):  
Ruifeng Zhang ◽  
Bizhong Xia ◽  
Baohua Li ◽  
Libo Cao ◽  
Yongzhi Lai ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion Battery ◽  
Electrode Materials ◽  
Open Circuit Voltage ◽  
Gaussian Model ◽  
High Capacity ◽  
Lithium Ion ◽  
Open Circuit ◽  
State Of Charge ◽  
Different Temperatures

Open circuit voltage (OCV) is an important characteristic parameter of lithium-ion batteries, which is used to analyze the changes of electronic energy in electrode materials, and to estimate battery state of charge (SOC) and manage the battery pack. Therefore, accurate OCV modeling is a great significance for lithium-ion battery management. In this paper, the characteristics of high-capacity lithium-ion batteries at different temperatures were considered, and the OCV-SOC characteristic curves at different temperatures were studied by modeling, exponential, polynomial, sum of sin functions, and Gaussian model fitting method with pulse test data. The parameters of fitting OCV-SOC curves by exponential model (n = 2), polynomial model (n = 3~7), sum of sin functions model (n = 3), and Gaussian model (n = 4) at temperatures of 45 °C, 25 °C, 0 °C, and −20°C are obtained, and the errors are analyzed. The experimental results show that the operating temperature of the battery influences the OCV-SOC characteristic significantly. Therefore, these factors need to be considered in order to increase the accuracy of the model and improve the accuracy of battery state estimation.

scholarly journals Parameter Identification and State-of-Charge Estimation for Lithium-Ion Batteries Using Separated Time Scales and Extended Kalman Filter

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1054
Author(s):  
Kuo Yang ◽  
Yugui Tang ◽  
Zhen Zhang
Keyword(s):  
Kalman Filter ◽  
Parameter Identification ◽  
Open Circuit Voltage ◽  
Lithium Ion ◽  
Open Circuit ◽  
State Of Charge ◽  
Recursive Least Squares ◽  
Model Parameters ◽  
Soc Estimation ◽  
Battery Model

With the development of new energy vehicle technology, battery management systems used to monitor the state of the battery have been widely researched. The accuracy of the battery status assessment to a great extent depends on the accuracy of the battery model parameters. This paper proposes an improved method for parameter identification and state-of-charge (SOC) estimation for lithium-ion batteries. Using a two-order equivalent circuit model, the battery model is divided into two parts based on fast dynamics and slow dynamics. The recursive least squares method is used to identify parameters of the battery, and then the SOC and the open-circuit voltage of the model is estimated with the extended Kalman filter. The two-module voltages are calculated using estimated open circuit voltage and initial parameters, and model parameters are constantly updated during iteration. The proposed method can be used to estimate the parameters and the SOC in real time, which does not need to know the state of SOC and the value of open circuit voltage in advance. The method is tested using data from dynamic stress tests, the root means squared error of the accuracy of the prediction model is about 0.01 V, and the average SOC estimation error is 0.0139. Results indicate that the method has higher accuracy in offline parameter identification and online state estimation than traditional recursive least squares methods.

scholarly journals Estimation of lithium-ion battery state-of-charge using an extended kalman filter

2021 ◽  
Vol 10 (4) ◽  
pp. 1759-1768
Author(s):  
Mouhssine Lagraoui ◽  
Ali Nejmi ◽  
Hassan Rayhane ◽  
Abderrahim Taouni
Keyword(s):  
Kalman Filter ◽  
Lithium Ion Battery ◽  
Extended Kalman Filter ◽  
Lithium Ion ◽  
The State ◽  
Operating Conditions ◽  
State Of Charge ◽  
Ohmic Loss ◽  
Battery Management System ◽  
Transfer Resistance

The main goal of a battery management system (BMS) is to estimate parameters descriptive of the battery pack operating conditions in real-time. One of the most critical aspects of BMS systems is estimating the battery's state of charge (SOC). However, in the case of a lithium-ion battery, it is not easy to provide an accurate estimate of the state of charge. In the present paper we propose a mechanism based on an extended kalman filter (EKF) to improve the state-of-charge estimation accuracy on lithium-ion cells. The paper covers the cell modeling and the system parameters identification requirements, the experimental tests, and results analysis. We first established a mathematical model representing the dynamics of a cell. We adopted a model that comprehends terms that describe the dynamic parameters like SOC, open-circuit voltage, transfer resistance, ohmic loss, diffusion capacitance, and resistance. Then, we performed the appropriate battery discharge tests to identify the parameters of the model. Finally, the EKF filter applied to the cell test data has shown high precision in SOC estimation, even in a noisy system.

Extended Physics-Based Reduced-Order Capacity Fade Model for Lithium Ion Battery Cells

2021 ◽  
pp. 1-12
Author(s):  
Zachary Salyer ◽  
Matilde D'Arpino ◽  
Marcello Canova
Keyword(s):  
Lithium Ion Battery ◽  
Cell Model ◽  
Active Material ◽  
Lithium Ion ◽  
Calibration Procedure ◽  
Layer Growth ◽  
Operating Conditions ◽  
Capacity Fade ◽  
Computationally Efficient ◽  
Reduced Order

Abstract Aging models are necessary to accurately predict the SOH evolution in lithium ion battery systems when performing durability studies under realistic operatings, specifically considering time-varying storage, cycling, and environmental conditions, while being computationally efficient. This paper extends existing physics-based reduced-order capacity fade models that predict degradation resulting from the solid electrolyte interface (SEI) layer growth and loss of active material (LAM) in the graphite anode. Specifically, the physics of the degradation mechanisms and aging campaigns for various cell chemistries are reviewed to improve the model fidelity. Additionally, a new calibration procedure is established relying solely on capacity fade data and results are presented including extrapolation/validation for multiple chemistries. Finally, a condition is integrated to predict the onset of lithium plating. This allows the complete cell model to predict the incremental degradation under various operating conditions, including fast charging.

Electrochemical Comparison of Chemically or Physically Modified Natural Graphite Anode for Lithium-Ion Batteries

2007 ◽  
Vol 124-126 ◽  
pp. 995-998
Author(s):  
Joong Pyo Shim ◽  
Hong Ki Lee ◽  
Byung Ho Song
Keyword(s):  
Heat Treatment ◽  
Carbon Black ◽  
Lithium Ion ◽  
Graphite Powder ◽  
Capacity Fade ◽  
Irreversible Capacity ◽  
Natural Graphite ◽  
Capacity Loss ◽  
Graphite Anodes ◽  
Powder Addition

Natural graphite anodes were treated by different methods to improve their cyclability. We tried following methods; heat-treatment at 550oC for graphite powder, addition of carbon black for electrode and VC (vinylene carbonate) in electrolyte. All methods decreased capacity fade rate during constant cycling. The addition of carbon black decreased capacity fade significantly but increased irreversible capacity much at first cycle. Heat-treatment and VC were also effective for cycling and irreversible capacity loss.

scholarly journals Fast charging of lithium-ion batteries at all temperatures

2018 ◽  
Vol 115 (28) ◽  
pp. 7266-7271 ◽  
Author(s):  
Xiao-Guang Yang ◽  
Guangsheng Zhang ◽  
Shanhai Ge ◽  
Chao-Yang Wang
Keyword(s):  
Low Temperature ◽  
Electric Vehicles ◽  
Cell Structure ◽  
Lithium Ion ◽  
State Of Charge ◽  
Trade Off ◽  
Battery Materials ◽  
Capacity Loss ◽  
Fast Charging ◽  
Conventional Cell

Fast charging is a key enabler of mainstream adoption of electric vehicles (EVs). None of today’s EVs can withstand fast charging in cold or even cool temperatures due to the risk of lithium plating. Efforts to enable fast charging are hampered by the trade-off nature of a lithium-ion battery: Improving low-temperature fast charging capability usually comes with sacrificing cell durability. Here, we present a controllable cell structure to break this trade-off and enable lithium plating-free (LPF) fast charging. Further, the LPF cell gives rise to a unified charging practice independent of ambient temperature, offering a platform for the development of battery materials without temperature restrictions. We demonstrate a 9.5 Ah 170 Wh/kg LPF cell that can be charged to 80% state of charge in 15 min even at −50 °C (beyond cell operation limit). Further, the LPF cell sustains 4,500 cycles of 3.5-C charging in 0 °C with <20% capacity loss, which is a 90× boost of life compared with a baseline conventional cell, and equivalent to >12 y and >280,000 miles of EV lifetime under this extreme usage condition, i.e., 3.5-C or 15-min fast charging at freezing temperatures.

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