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IN PROGRESS


Also, make a battery basics page - links to MDPI pages

To get a better understanding of the equivalent circuit model of a cell, see this page (link).



Quick Overview and Recommendations:

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The goal of cell testing:

The more data and the more informed we are about the status of our pack, the better.

Any imbalances present in the pack at the start will only get worse as the pack is cycled. Within series modules, this variance can be overcome with cell balancing, but within parallel cells there is no way to overcome this. (link study) Due to the nature of li-ion cells being a manufactured component, there is always some degree of tolerance from the manufacturer. This page will discuss the parameters that can vary and how they affect pack imbalance.

Also, make a battery basics page - links to MDPI pages

To get a better understanding of the equivalent circuit model of a cell, see this page (link).







What parameters can be measured, and do they cause pack imbalance?

As-Received OCV - Assuming the cells were manufactured at the same point on the voltage curve, the as-received OCV is an indicator of the amount of self-discharge current of the cell. See the self-discharge method.

Cell Weight - The weight of a cell is an indicator of how much material is inside the cell. According to this paper (   https://www.nature.com/articles/srep35051), the weight of a cell correlates loosely with the capacity of the cell.

Ir - 

Im - The internal impedance of a cell is a similar measure to the DC internal resistance

EIS Measurements, before factory screening occurs, as tested on 5473 Boston Power Li-ion cells (Swing 5300 5.3Ah). See capacity section for the effect of capacity on imbalance.

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Self-Discharge (https://literature.cdn.keysight.com/litweb/pdf/5992-2517EN.pdf?id=2911018). Keysight has developed a self-discharge measuring unit, which incorporates a super-high precision DC voltage source and a super high precision current measurement device (accurate to the tens of uA). The bucket method described in the document provides a quick (1 hour) test of the self-discharge current. A single cells having a significantly higher self-discharge current will cause the module to have a larger self-discharge current. Over long periods of time (such as sitting idle in the bay for a month), this self discharge current will cause an imbalance in SoC of the cells and lead to decreased pack capacity.

Capacity The difference in capacity between cells in parallel groups causes current spikes in these cells at the end of charge or discharge cycles.


DC Internal Resistance - The DC Internal resistance (DCIR, DCR, RI, or IR) is modelled as a resistor in series with the cell. Measuring the resistor involves putting a pulse discharge current on the cell, and measuring the voltage drop. This voltage drop is attributed to the series resistance inside the cell. Typical values for DCIR are between 30-80mOhm for a new 18650 cells. For comparison, LiPo cells with high discharge ratings used in RC models typically have a DCIR in the range of 2-10mOhm.

AC Internal Impedance - The internal impedance of a cell is a similar measure to the DC internal resistance except measured with a 1kHz sinusoidal signal applied.

Electrochemical Impedance Spectroscopy (EIS) Measurements - For basics of EIS measurements, there is a great explanation here

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urlhttps://www.youtube.com/watch?v=I3uvugRXHG8
. EIS measurement, by sweeping the frequency of an applied signal across a wide range of frequencies determines the cell impedance at each of these frequency. Complex mathematical algorithms can fit many free parameters to this data, allowing measurement and evaluation of much more complex cell models, involving inductors, capacitors, and resistors to model the AC behaviour. As a research tool, this is a super powerful technique allowing characterization of all cell parameters except capacity. Nyquist plots are used to determine the real component of the series resistance at the zero-crossing point. EIS measurements take a long time to perform, and are not necessarily better than the other methods for our applications.

A comparison of EIS measurement and DC Pulse measurement of resistance is shown below (https://www.sciencedirect.com/science/article/pii/S2352152X18300732#bib0090). I don't claim to understand everything about EIS measurements, but according to this report (https://pdfs.semanticscholar.org/58a9/c593a684fa1a503492383ec807334b4aaaef.pdf?_ga=2.120996168.1162077320.1560615736-269352092.1559077519, page 17) explaining the Nyquist plot (blue) below, the intersection between the semicircle and the Warburg straight line represents the sum of all the internal resistances (the electrolyte, the solid electrolyte interface, and the electron transfer reaction). Notice how the DC IR curve intersects that corner at a pulse time of around 2s. The value obtained for the resistance matches the expected value when compared with calorimetry data in the same report calculating the amount of temperature rise in the system.

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Initial Characterization Predicted Results

If we do go ahead with individual cell testing, what are the values that are expected, how much variation is expected, and are there outliers that will cause imbalance?

Below is a figure showing DCR and capacity tests for over 20,000 cells measured at beginning of life. The tests were performed on LiFePO4 cells, however the data is a good indication of the variance we should expect as the manufacturing processes are pretty much identical. The key thing to notice here is that  while the capacities and DCR measurements at beginning of life follow a normal distribution, with fairly low variance from nominal (5.8% for DCR and 1.3% for capacity), there are outliers within the data at the edges of the normal distribution. It is these outlier cells that will cause issues in packs, due to previously mentioned imbalance factors (https://www.sciencedirect.com/science/article/pii/S037877531300116X?via%3Dihub) (blue/yellow graphs).

The second set of graphs show Initial Conditioning and Characterization Tests performed on 100 Panasonic NCR18650B cells, and a similar amount of outliers and standard deviation is noted. The Panasonic cells have been around for a long time. An email from Steve McMullen, ASC Inspector, notes that "Their testing was also with very mature technology Panasonic 18650 3.2AH cells that have been manufactured in the millions if not billions.  The newer cells don’t have as much credibility.  I believe your team is using LG CHEM INR 18650 MJI which is a variant of the technology to trade off Rate for Life and Weight for Capacity, so the cell is already working in realm different than the Panasonics". We should be aware that the MJ1 cells we are using could have more variation than the data from the panasonic tests noted below (https://www.hnei.hawaii.edu/sites/www.hnei.hawaii.edu/files/Initial%20Conditioning%20Characterization%20Test.pdf) (red/blue/black graphs).

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Ideal situation: Test, Estimated Time Required per cell

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If balancing modules based on cells tests, one of the most important items to test is the individual cell capacity. Building the modules based on a minimum capacity deviation will allow us to perform less testing on the modules as the capacity is already determined. This will require more test time at the cell level on a tradeoff for less test time at the module level. With access to the right equipment (a large cell cycling machine, around 200 slots), it will take less time to test the cells than to test the 48 modules on 1 or 2 high current cyclers. Building modules with a capacity metric in hand will allow us to create packs with equal useable energy.



Why single cell testing is required (

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comparison against module/pack testing):

1 - A manufacturing error will be impossible to detect once we put the cells in modules

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We do not expect to be using multiple hundreds of cycles on our pack. The capacity loss shown in the figure happens after around 100 cycles, and is due to the mismatched cells being exposed to large charge/discharge currents as the ends of the charging and discharging cycles due to differing SoC-OCV curves cause by the mismatched resistance. The cells in these tests were LiFePO4 cells, and the internal resistance measured by a 15s 40A pulse, with a distribution shown above from 13.5 - 21.5 mOhm. This is a fairly large spread (50%) , or IR and the currents that the pack were tested at are much larger than anything our cells will ever see. A high current test such as this decreases the time that the mismatch effects take to show up as the cells are performing at their peak characteristics.

Internal resistance mismatch causes current mismatch on charge and discharge. The current mismatch creates voltage drop difference and thus a difference in SoC between the cells in parallel groups. Thus there is an SoC mismatch between the cells when current is being drawn.

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Thoughts on Temperature Variation:

Pack-Variation: As the temperature of a battery pack increases, the self-discharge rate also increases due to the increased rate of the chemical reactions inside the cell. An increase in 10 degrees Celsius will double the amount of self-discharge current. (Keysight link) The self-discharge will still be in the high-uA range (maybe low mA in the worst case), and thus not be an issue in module or pack balancing as the passive balancing circuit will take care of the pack-level variation in self-discharge. Assuming the temperature within the pack is only hotter when we are drawing current, the change in DC Internal Resistance will more than offset the change in self-discharge current.

Module-Variation: Temperature variation within a module, under extreme circumstances, can result in a positive feedback situation (until a certain delta OCV is reached). A decrease in internal resistance of the cell due to an increase in temperature will cause more current to be drawn from that cell, which will lower its OCV. Due to the close proximity of cells within a module, the temperature variation (unless caused by a cell with initially high IR) will be very small ans thus its effects negligible.

With temperature variation, the useable capacity of the cell will increase as the internal resistance decreases and thus we have less power loss in the cells due to IR. (Show IR-temp graph and Capacity-Temp Graph) 

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