scholarly journals Comparative Study on the Calendar Aging Behavior of Six Different Lithium-Ion Cell Chemistries in Terms of Parameter Variation

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3358
Author(s):  
Christian Geisbauer ◽  
Katharina Wöhrl ◽  
Daniel Koch ◽  
Gudrun Wilhelm ◽  
Gerhard Schneider ◽  
...  
Keyword(s):  
Open Circuit Voltage ◽  
Lithium Ion ◽  
Aging Effect ◽  
Open Circuit ◽  
Capacity Loss ◽  
Lithium Ion Cells ◽  
Lithium Ion Cell ◽  
Capacity Degradation ◽  
Aging Conditions ◽  
Stationary Conditions

The degradation of lithium-ion cells is an important aspect, not only for quality management, but also for the customer of the application like, e.g., scooters or electric vehicles. During the lifetime of the system, the overall health on the battery plays a key role in its depreciation. Therefore, it is necessary to monitor the health of the battery during operation, i.e., cycle life, but also during stationary conditions, i.e., calendar aging. In this work, the degradation due to calendar aging is analyzed for six different cell chemistries in terms of capacity degradation and impedance increase and their performance are being compared. In a new proposed metric, the relative deviations between various cells with the exact identical aging history are being analyzed for their degradation effects and their differences, which stands out in comparison to similar research. The capacity loss was found to be most drastic at 60 °C and at higher storage voltages, even for titanate-oxide cells. LiNiMnCoO2 (NMC), LiNiCoAlO2 (NCA) and Li2TiO3 (LTO) cells at 60 °C showed the most drastic capacity decrease. NMC and NCA cells at 60 °C and highest storage voltage did not show any open circuit voltage, as their current interrupt mechanism triggered. The effect of aging shows no uniform impact on the changes in the capacity variance when comparing different aging conditions, with respect to the evaluated standard deviation for all cells. The focus of this work was on the calendar aging effect and may be supplemented in a second study for cyclic aging.

scholarly journals A study of the open circuit voltage characterization technique and hysteresis assessment of lithium-ion cells

2015 ◽  
Vol 295 ◽  
pp. 99-107 ◽  
Author(s):  
Anup Barai ◽  
W. Dhammika Widanage ◽  
James Marco ◽  
Andrew McGordon ◽  
Paul Jennings
Keyword(s):  
Open Circuit Voltage ◽  
Lithium Ion ◽  
Open Circuit ◽  
Lithium Ion Cells ◽  
Characterization Technique

scholarly journals A Comparison of Lithium-Ion Cell Performance across Three Different Cell Formats

Batteries ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 38
Author(s):  
Grace Bridgewater ◽  
Matthew J. Capener ◽  
James Brandon ◽  
Michael J. Lain ◽  
Mark Copley ◽  
...  
Keyword(s):  
Degradation Mechanism ◽  
Single Layer ◽  
Lithium Ion ◽  
Capacity Loss ◽  
Lithium Ion Cells ◽  
Lithium Ion Cell ◽  
A Cell ◽  
The Difference ◽  
Discharge Capacities

To investigate the influence of cell formats during a cell development programme, lithium-ion cells have been prepared in three different formats. Coin cells, single layer pouch cells, and stacked pouch cells gave a range of scales of almost three orders of magnitude. The cells used the same electrode coatings, electrolyte and separator. The performance of the different formats was compared in long term cycling tests and in measurements of resistance and discharge capacities at different rates. Some test results were common to all three formats. However, the stacked pouch cells had higher discharge capacities at higher rates. During cycling tests, there were indications of differences in the predominant degradation mechanism between the stacked cells and the other two cell formats. The stacked cells showed faster resistance increases, whereas the coin cells showed faster capacity loss. The difference in degradation mechanism can be linked to the different thermal and mechanical environments in the three cell formats. The correlation in the electrochemical performance between coin cells, single layer pouch cells, and stacked pouch cells shows that developments within a single cell format are likely to lead to improvements across all cell formats.

scholarly journals Self-discharge rates in cells have a critical effect on the cycle life of parallel lithium-ion batteries

RSC Advances ◽  
2018 ◽  
Vol 8 (54) ◽  
pp. 30802-30812 ◽  
Author(s):  
Fuqiang An ◽  
Hongliang Zhao ◽  
Ping Li
Keyword(s):  
Lithium Ion Batteries ◽  
Open Circuit Voltage ◽  
Lithium Ion ◽  
Open Circuit ◽  
Critical Effect ◽  
Lithium Ion Cells ◽  
Discharge Rates ◽  
Direct Current Resistance ◽  
Two Parameters ◽  
Current Resistance

More than two parameters are adopted to sort lithium ion cells (LICs) for better performance in the production process, such as capacity, open-circuit voltage (OCV), direct current resistance (DCR), et al.

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.

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