The Effect of Charging and Discharging Lithium Iron Phosphate-graphite Cells at Different Temperatures on Degradation

This article describes the effect of dissimilar charging/discharging temperatures on the degradation of lithium iron phosphate-graphite pouch cells, aiming at simulating close to real case scenarios. In total, 10 temperature combinations are investigated in the range -20 to 30 °C in order to analyze the impact of temperature on degradation.

This method can help answer questions about battery aging. Cycling a different charge and discharge temperatures may influence degradation as many processes causing degradation are temperature-dependent. The main advantage of this technique is testing different charging and discharging temperature as conventional testing method use the same environmental temperature for charging and discharging.

The implications of this technique extend toward supporting future standards and regulations with testing of different charge and discharge temperatures. This method can provide an insight into degradation mechanisms at different temperatures. Higher temperature cycling enhances degradation and increases the growth of the SEI layer while low temperature cycling results in lithium plating.

Prior to the experiment, use design of experiment methods to identify the optimal pairs of charge and discharge temperatures to minimize the needed number of temperature combinations. To begin the process, place two lithium iron phosphate-graphite pouch cells at 30%state of charge in rigid, polycarbonate holders. Place the cells in fixtures in a temperature chamber of the battery cycler.

Place a thermo couple connected to the battery cycler at the center of one side of each cell. Connect the cells to the battery cycler via a four-wire connection. In the battery cycler software, set the temperature chamber to 25 degrees Celsius.

Allow the cells to equilibrate for 12 hours. Next, create a new file in the battery cycler test editor for two-step, constant current, constant voltage cell conditioning. Fill in channel safety criteria to stop cycling if the battery conditions exceed specified limits.

Add a constant current discharging step at a C-rate of 0.1 up to 2.7 volts. Follow this with a 30 minute rest. Then, at a constant current, constant voltage charge at 0.1 C-rate to 3.7 volts with the constant voltage phase lasting one hour or until the C-rate drops to 0.01C.

And another 30 minute rest period. Save the conditioning protocol when finished. Create a new protocol for reference cycling.

Set the chamber temperature to 25 degrees Celsius and add a waiting period until the temperature varies by less than one Kelvin per hour. Add two constant current charging/discharging cycles with charge and discharge thresholds of 3.7 volts and 2.7 volts respectively, at a C-rate of 0.3. Follow each cycle with a waiting period to allow the temperature to stabilize.

Save the reference cycling protocol when finished. Open the conditioning method and add the reference cycling to the conditioning as a sub-routine. Then, open the main battery cycler software.

Click on both channels with cells to be tested to select the channels and click the Run button. Select the conditioning process, provide a file name, enter the capacity in ampere hours, and select the temperature chamber. Run the process to determine the initial capacity.

Create a new protocol for long-term cycling with the same charge and discharge temperatures. Start by setting the chamber to the target temperature and allowing the cell temperature to equilibrate. Set the method to perform constant current, constant voltage charging to 3.7 volts at a C-rate of one with the constant voltage phase lasting one hour or until the C-rate drops to 0.1.

Rest the cells for 30 minutes. Then, perform constant current discharging to 2.7 volts at the same C-rate and rest the cells for another 30 minutes. Repeat the charge/discharge cycles 100 times.

Add in the reference cycling as sub-routine after every 25 cycles. Create another protocol for long-term cycling with different charge and discharge temperatures using the same C-rate and voltage thresholds. Set the rest phases after each cycling step to wait until the cell temperature has stabilized.

Repeat the charge/discharge cycles 100 times with reference cycling every 25 cycles. Save the method when finished. Based on these protocols, create long-term cycling protocols for the temperature combinations identified by design of experiment methods.

Then, return to the main battery cycler program. Select the channels for the cells to be tested. Select the desired long-term cycling program.

Fill in a file name for the data. Select the temperature chamber and start the long-term cycling. Repeat the test once on a fresh cell to assess the repeatability.

Once the electrochemical cycling tests have finished, open a data visualization template in the battery cycling software. Then open the saved cycling data and assess the cell degradation over time. Next, open the data in analysis software and select a stepwise fit with a max K-fold R-square function.

Fit the data, evaluate the subsets, and select the best overall R-squared value to avoid over fitting. Then, click Make Model to visualize the fitted data. Evaluate the parameters listed in the Effects Summary and delete any parameters shown as not significant.

View the final degradation rate visualization and adjust the appearance settings as desired. Repeat this process for all tested cells. Next, transfer the cells to an inert, gas-filled glove box.

Disassemble the cells and cut open the pouches with ceramic scissors. Cut 5mm by 5mm pieces of the anodes and cathodes. Mount the electrode pieces on scanning electron microscope sample stubs fixed in a sample holder.

Insert the sample holder in a sealed container and remove it from the glove box via the antechamber. Transfer the sample holder from the glove box to the SEM sample chamber via a glove bag filled with inert gas at a positive pressure. Characterize at least five different locations on the surface of each sample to identify potential surface inhomogenieties.

When cycled with both the charge and discharge temperatures at 20 degrees Celsius, a dramatic decay of capacity was observed within each 25 cycle block, followed by significant recuperation during reference cycling at 25 degrees Celsius. Cycling at 12 degrees Celsius or 30 degrees Celsius resulted in notably greater capacity decay than cycling at 5 degrees Celsius or 5 degrees Celsius. When cycling at a given charge temperature, higher long-term stability was observed at lower discharge temperatures.

Similarly, when cycling at a given discharge temperature, higher long-term stability was usually observed at lower charge temperatures. Cells cycled with the discharge temperature of 20 degrees Celsius and charge temperatures of 0 degrees Celsius or 15 degrees Celsius showed modest capacity recovery after reference cycling with less severe drops in capacity over long-term cycling than was observed with a charge temperature of 20 degrees Celsius. A model was derived from the data to describe the relationships between charge and discharge temperatures and the degradation rates, allowing the optimal temperatures to be identified depending on the potential application.

We first got the idea for this method when we discussed how temperatures variations affect the durability of a battery. We analyzed testing standards and realized that the testing is mostly done at the same environmental temperature. However, batteries are faced with continuously varying temperatures because of seasonal changes, day/night variation, and the operating temperatures of surrounding equipment.

There could be an extremely large number of charge and discharge temperature permutations in a given temperature range. Therefore, we use optimal design of experiments to minimize the number of tests needed for maximal information gain. This technique paved the way to develop fit for purpose better degradation technique standards with comparable condition to real life's usage.

After watching this video, you should have a good understanding of how to design, test, and analyze battery cycling data and compare those data with other test results and with real life usage.