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Building a battery lab with low-cost Raspberry Pi’s
Shane D. Beattiea,i, Ben Beck i, Ryley R. LeBlanci, James Lanigani
i) Elcora Advanced Materials, Bedford, 275 Rocky Lake Drive, Suite 11, Bedford, NS, B4A 2T3, Canada
a) corresponding author: [email protected] or [email protected], CTO, Elcora Advanced
Materials
Abstract
Battery labs are expensive to build and maintain. Significant capital investment is required to build a quality
laboratory capable of testing batteries and the materials they are made from. This paper will discuss several
advanced techniques for testing Lithium-ion batteries. All techniques use a low-cost Raspberry
Pi/microcontroller to perform experiments and collect data. The use of Raspberry-Pi’s significantly reduces the
cost to test batteries and battery materials. This, in turn, will accelerate the discovery of new battery materials.
Keywords
Lithium-ion, battery, Raspberry, expansion, hardware, testing
1. Introduction
A quality research and development (R&D) lab for making/testing Li-ion batteries can cost millions of dollars.
The capital and equipment involved is cost prohibitive for many organizations. Hence, they do not invest in the
discovery of new and improved battery materials. This financial barrier slows the improvement of battery
technology, which is non-ideal for society. Battery technology is becoming more and more important to
humanity. Batteries are used in numerous critical applications (e.g. grid storage, electric vehicles and portable
personal electronics). As battery technology advances, so does society. Hence, one should remove as many
barriers to the improvement of battery technology as possible. The purpose of this paper is to introduce the
reader to high-quality experiments that can be performed using low cost equipment. For example, a Raspberry
Pi.
The Raspberry Pi is a small, low-cost (~ $50 USD) computer. It was developed to be affordable and promote
the teaching of basic computer science in schools and in developing countries. The operating system (OS) is
free, as are numerous powerful software packages (e.g. Python, Mathematica). The original Raspberry Pi model
became far more popular than anticipated, selling outside its target market. Since then, it has been used by
enthusiasts to bridge the gap between computers, sensors and data collection.
In this paper, Raspberry Pi’s will be used to control a variety of experiments that test the performance of Li-ion
batteries and the materials they are made from. Using a Raspberry Pi, and inexpensive components,
sophisticated tests can be performed at very low cost. This strategy removes/lowers the cost barrier associated
with testing Li-ion batteries/materials. This cost-reduction will allow researchers world-wide to perform
affordable, high-quality experiments. These tests will eventually result in improved battery materials, and
superior battery performance. Those batteries will find their way into critical applications, ultimately making
the world a better, cleaner place to live.
2. Experimental:
2.1. Graphite electrodes:
Graphite electrodes were prepared in multiple steps, outlined below:
2.1.1. A stock solution of 8% /w polyvinylidene fluoride (PVdF; SPVDFD2, Targray) in anhydrous N-
Methyl-2-pyrrolidone (NMP) was made in a dual shaft planatery mixer (MTI, MSK-SFM-16) in
a 500 mL vessel (SFM-16) and mixed overnight
2.1.2. 1.35 g of carbon black (Timcal Super 65) was added into a 150 mL vessel with 25 mL of NMP
and set to mix (MTI, MSK-SFM-16) at 250 RPM for 60 minutes
2.1.3. 42.3 g of Elcora’s EL-I-C6 graphite (https://www.elcoracorp.com/products/) and 16.9 mL of
stock PVdF/NMP (from 2.1.1) were added to the mixture and mixed at 500 RPM for one hour
2.1.4. The speed was then reduced to 250 RPM and mixed in the reverse direction for 16 hours
overnight
2.1.5. Next, 4.5 mL NMP was added to wet any unmixed powder stuck to the auger. The mixing speed
was increased to 500 RPM for 8 hours, then reduced to 250 RPM for 16 hours with the vacuum
at -0.78 bar
2.1.6. Anode coatings were cast onto 10 m thick electrodeposited Cu foil (SFLD30001CU, Targray).
Coatings were made using a desktop coater (MSK-AFA-II-VC-H, MTI). Coated electrodes were
dried in air overnight, followed by vacuum drying (Binder Vacuum Drying Ovens with
integrated vacuum pump system at 1.1 inch Hg) for > 12 hours at 50 oC.
2.1.7. Dry electrodes have a graphite:binder:carbon black ratio of 94:3:3.
2.2. Electrolyte:
Electrolyte consisted of 1 M LiPF6 in 3:7 v/v ethylene carbonate (EC):ethyl methyl carbonate (EMC) with
2% vinylene carbonate (VC) and 1 % 1,3-Propane Sultone (PS) (Soulbrain).
2.3. Half cells:
Half cells were fabricated in 2032 stainless steel coin cell hardware from Hohsen. A polyethylene film (20
m thick, 19 mm diameter; PMISC, Targray) was used as the separator. 16 mm diameter graphite electrodes
were cut using a precision punch (MSK-T10, MTI). All cell components were dried in a vacuum oven at 50
oC overnight before assembly. Lithium foil discs (16 mm diameter, 0.2 mm thick) were used as the counter
electrode.
2.4. Open Circuit Voltage (OCV) measurements:
OCV measurements were made using a low-cost, 16-channel voltmeter. A Raspberry Pi Model 2 B+ was
used as the controller computer. Four, four-channel ADS1115 16-Bit Analogue to Digital Converter (ADC)
breakout boards (e.g. https://www.adafruit.com/product/1085) were connected to the Raspberry Pi. The
four-channel ADS1115 breakout boards can be purchased for as low as ~ $3 USD/board (ebay.ca), and can
measure voltages between 0 and 5 V. The Raspberry Pi communicates with the ADC boards via an Inter-
Integrated Circuit (i2C) bus using code written in Python3 (code freely available, contact corresponding
author). The OCV of the 16 different channels is measured approximately once per second. The code
allows data to be saved to a text file using user defined save conditions (e.g. every Δt, time or ΔV, voltage).
20mm Coin Cell Breakout Boards (CR2032) were used to hold the coin cells under test (e.g.
https://www.adafruit.com/product/1870). The coin cell holder and ADS1115 breakout boards were soldered
to a bread/protoboard (e.g. https://www.adafruit.com/product/590) (Figure 1). The total cost is ~ $5/channel.
To date, the author has been running continuous, stable OCV experiments for well over one year.
Connecting the Raspberry Pi to an Uninterruptable Power Supply (UPS) is highly recommended for long
term tests.
2.5. Cell cycler:
A custom-made circuit was designed to perform constant-current charge/discharge cycling . A simple
schematic is shown in Figure 2. An analogue to digital converter (ADC) is used to measure voltages (e.g.
like the ASD1115 above), while a digital to analogue converter (DAC) is used to control voltage (e.g.
MCP4725). A high precision shunt-resistor is used to measure current. ADC’s, DAC’s and resistors are
very affordable. The ADC and DAC used in the schematic in Figure 2 below cost less than $3 each.
A Raspberry Pi was used to communicate with the ADC/DAC chips (using the i2c bus) and record relevant
data (e.g. time, voltage, current, temperature) to the Secure Digital (SD) card. The components for the
circuit shown in Figure 2 cost less than $60 (including the Raspberry Pi). The circuit is called the Pi
CycLing OPerating System (PiClops).
In Figure 2 the DAC is used to control to voltage across the shunt resistor (VR) and the battery (VB). Such
that:
VDAC = VR + VB
To keep VR constant (e.g. galvanaostatic/constant current mode), VDAC must be constantly adjusted as VB
changes (i.e. during charge/discharge). Software running on the Raspberry Pi is used to accomplish this.
VB and VR are measured using the ADC and their values stored as variables in the software. The required
VDAC is calculated based on the user defined current and the resistance of the shunt resistor (VR = IR). The
software applies the newly calculated VDAC value to the DAC then measures VB and VR; and repeat. If the
upper/lower cut-off voltage of the battery is reached the current sign is switched and the circuit continues
cycling the cell for the desired number of cycles. In the software the user can define current, upper/lower
cut-off voltage, active mass, as well as the desired number of cycles. The software can also be written so the
circuit acts as a constant voltage source. This way industry standard constant current/constant voltage
(CCCV) cycling profiles can be applied.
The circuit shown in Figure 2 can be built by any enthusiast with some knowledge of circuit design and
hobby hardware (i.e. a breadboard, wires, DAC, ADC, resistor and a Raspberry Pi). Although functional,
when the circuit from Figure 2 was built on a breadboard it was not particularly accurate. A more
sophisticated circuit (based on Figure 2) has been developed by experienced electrical engineers [1]. It will
be discussed next.
The circuit described in Figure 2 has been optimized for speed and accuracy. Relays are added to the circuit
so the ADC is only connected to the battery during voltage measurements (unlike most commercial
manufacturers of cell cycling hardware). This minimizes the current leakage through the ADC. Although
the ADC has a high impedance, and therefore low current draw, the current draw is non-zero, hence the true
capacity of the cell can be over/under estimated during charge/discharge. Over and undervoltage safety
limits are also hardwired into the circuit to increase safety.
The PiClops is a self-contained printed circuit board (PCB) that plugs directly into the general purpose
input/output (GPIO) pins on a Raspberry Pi (Figure 3) [1].
The boards can be made available to interested parties (contact author). The circuit is designed with three
current ranges (0-100 A, 1 mA and 10 mA; automatically selected by the software) and a voltage range of
±5 V. A 2032 coin cell holder is provided for ease of mounting. In addition, there are pins in parallel with
the coin cell holder so any type of cell could be connected to the board (e.g. a cylindrical, prismatic or pouch
cell). There is a temperature probe directly below the cell to measure temperature as a function of time.
There is an auxiliary voltage channel allowing other voltage-based measurements to be measured/recorded
during cycling (e.g. reference electrode, three electrode cell, pressure, temperature, stress, strain, volume,
etc.)
All data is stored in easy to read/manipulate text files (no special software necessary). During cycling
Gnuplot (free - http://www.gnuplot.info/) plotting software is used to display the data. The graph is updated
approximately every 10 seconds so the user can monitor ‘live’ cycling data.
The authors typically run the Raspberry Pi’s in ‘headless mode’ (e.g. not connected to a keyboard, mouse or
monitor). This saves space and lowers-cost. Data files are easily transferred via file transfer protocol (FTP)
or a USB memory stick. An appropriately configured headless Raspberry Pi can be accessed/controlled by
any device (e.g. computer, tablet, smart phone) that can run Virtual Network Computer (VNC) software (e.g.
TightVNC).
2.6. Archimedean Pouch Swell System (APSS)
The Archimedean Pouch Swell System (APSS) was developed to accurately measure volume changes
(expansion/contraction) of a lithium-ion (Li-ion) cell during dis/charge. The APSS is based on a technique
developed by Dahn et. al.[2]. Changes in volume are tracked in situ as the battery is dis/charged over several
cycles. Volume is measured by submersing the cell in a liquid of known density and measuring the apparent
mass using a strain gauge load cell (refer to [2] for more information). Inexpensive strain gauge load cells
can be purchased for < $10 (e.g. ebay.ca). The signal from the strain gauge needs to be amplified to measure
mass accurately. An HX711 amplifier chip (~ $1 from eBay.ca) is used for this purpose. The HX711
outputs mass readings as a digital signal. That signal is read using general/purpose input-output (GPIO) pins
on a Raspberry Pi and Python code (contact the author for code). The HX711 amplifier chip was supplied a
constant +5 V using a precision LP2951CN voltage regulator (to minimize noise in the mass readings).
Mass measurements are affected by temperature due to changes in the liquid’s density. To understand how
temperature varies with volume a BMP180 temperature sensor (~ $2 from eBay.ca) was added to the
Raspberry Pi. Conveniently, the BMP180 also measures atmospheric pressure. All components were
mounted to a rigid frame made from painted metal L-bars and placed in an insulated container (Figure 4).
The insulated container minimized temperature fluctuations and rogue air currents during data collection.
The APSS was calibrated by measuring the difference between strain gauge resistance under zero load vs. a
10.0 g mass. Calibration allows the software to establish a linear scale for measuring mass determinations
from strain gauge resistance readings.
Figure 4 shows the APSS inside the insulated container. A pouch cell is fully submerged in a 500 mL
beaker filled with mechanical pump oil (ρ = 0.844 g mL-1; Edwards Ultra Grade 19). The pouch cell was
suspended from the strain gauge using an alligator clip (Figure 4). Thin (32 AWG) bare copper wire was
used to supply the cell with ±500 mA for cycling. The current carrying wires were as thin as possible to
minimize tension not being measured by the strain gauge. The wires were connected to the cell with enough
slack to ensure that they carried virtually zero tension. Cells were cycled using a Neware battery testing
system (BTS-4008-5V6A).
Volume, atmospheric pressure, atmospheric temperature, and time data were tracked using a Raspberry Pi
and the inexpensive sensors discussed above. Voltage, capacity and current data were tracked with the
Neware battery testing system. Data collected from dis/charging a 10 Ah pouch cell will be presented and
discussed in section 3.3.
2.7. Tap density analyser:
A tap density analyser was built using an Arduino UNO (https://store.arduino.cc/usa/arduino-uno-rev3) and
3D printed hardware. The tap density analyser was built according to ASTM B 527 standards (describes the
typical operation for a standardized tap density test). The design was based on a polypropylene 250 mL
graduated cylinder and M3 bolts/nuts. All parts were made as 2D sketches and extruded into 3D objects in
Autodesk Fusion 360. The CAD files were converted to STL files and printed using polylactic acid with a
30% fill density. The hardware used to build the unit cost < $20. A commercial tap density analyser
typically costs > $2000. Contact the author for detailed schematics and build of materials (BOM).
3. Results and Discussion:
3.1. Open Circuit Voltage (OCV) measurements:
Sixteen graphite-lithium (Li) half cells were studied using the Raspberry Pi multichannel voltmeter
described in section 2.4. Eight of the cells were duplicates (for redundancy), so eight unique experiments
were performed. Using standard cell cycling hardware (Neware BTS4000-5V10mA) each cell was
discharged (graphite electrode is lithiated) at C/20 for different amounts of time: 2, 4, 6, 8, 10, 12, 16, and
20 hours. Table 1 shows lithiation times at C/20 and corresponding lithiation gravimetric capacities. All
cells used a lower cut-off of 0 V vs. Li/Li+ (although only the cell cycled for 20 hours reached 0 V). After
X hours of lithiation (at C/20) the cells were left on the Neware channel while measuring OCV. After
several days the cells were removed from the Neware cycler. The cells were then transferred to the
Raspberry Pi based multichannel voltmeter (discussed in section 2.4) for long-term monitoring (> 6
months). Results can be found in Figure 5.
There are eight different voltage vs. time profiles in Figure 5. These represent the eight different cycling
time profiles: 2, 4, 6, 8, 10, 12, 16, and 20 hours. The data sets in Figure 5 are color coded to easily
differentiate their voltage profiles vs. time (Figure 5 - legend). Note the x-axis on the graph on the left in
Figure 5 is a logarithmic scale. This allows the different graphite lithiation stages to be clearly visible
(labelled in Figure 5). The graph on the right side of Figure 5 shows long term OCV data (not a logarithmic
scale) collected using the 16 channel Raspberry Pi based voltmeter (discussed in section 2.4). Graphite
lithiation staging [3] is clearly evident in Figure 5 (left graph): LiC18 is formed first, then LiC12 and finally
LiC6.
The cell that was cycled for 2 hours drops to just below 0.2 V vs. Li+/Li. An SEI should be formed below
0.2 V [4]. However, the graphite was only slightly lithiated: 37.3 mAh/g (Table 1). The capacity values in
Table 1 do not including irreversible capacity (estimated at ~ 30 mAh/g). Subtracting the irreversible
capacity from the lithiated capacity (Table 1; 2 hours), the graphite was only lithiatied by ~ 7.3 mAh/g.
Over time lithium will be removed from the graphite due to parasitic reactions with the electrolyte [5,6]. In
this case (2 hr lithiation) the OCV quickly rises as the lithium is removed from the graphite. The trend
continues with increased hours of lithiation. The cell lithiated for 4 hours has a capacity of 73.4 mAh/g (~
43.3 mAh/g of lithiated graphite). Similarly, it’s voltage quickly rises vs. time. As does the cell cycled for
6 hours to 111.3 mAh/g (~ 81.3 mAh/g of lithiated graphite). The voltage of the cell lithiated for 6 hours
has a relatively stable OCV for ~ 110 hours (Figure 5; left graph). The initial OCV voltage of this cell
corresponds with the LiC12 phase. Over time the voltage starts to rise (Figure 5; right graph). As lithium is
removed from the graphite it approaches equilibrium with the LiC18 phase, which has a higher OCV
compared to LiC12 (Figure 5). After ~ 120 days the OCV stabilizes to the voltage associated with LiC18.
Note that the lithiation voltages of the different stages of lithiated graphite will differ slightly while current
is flowing (Figure 5; left graph) vs. OCV (Figure 5; right graph) due to overvoltage. Hence, the OCV
voltage is always slightly higher than the voltage during lithiation.
After 8 hours of lithiation a relatively large amount of the graphite has been lithiated (147.5 mAh/g; Table
1). The voltage profile of this cell is very stable. It’s voltage doesn’t start rising until after ~ 80 days of
OCV monitoring. As above this is associated with the transition from LiC12 to LiC18.
The electrode lithiated for 10 hours (at C/20) shows similar performance compared to the cell cycled for 8
hours. This time the voltage doesn’t start to rise until after ~ 120 days. Figure 6 shows a zoomed in image
of the data in Figure 5. Note the relatively sharp transition from LiC12 toward LiC18. The same sharp
transition was observed in the cell cycled for 8 hours (not explicitly shown).
The cell lithiated for 12 hours (222.1 mAh/g; Table 1) clearly shows a transition from LiC6 to LiC12 after ~
10.5 hours (Figure 5; left graph). The voltage is then steady at LiC12 for the duration of the OCV
measurements.
The cells lithiated for 16 (298.7 mAh/g; Table 1) and 20 hours (367.1 mAh/g; Table 1) do not show a
change in voltage, even after > 160 days of OCV monitoring. These cells have not lost enough lithium to
start transitioning to the LiC12 phase. This data shows that the SEI is very stable and little Li is being lost to
parasitic reactions.
The discussion above shows that OCV monitoring is a useful method for studying cell behaviour (e.g. self-
discharge) over time. OCV monitoring has been shown to be useful in other studies as well [5,6]. The total
cost for the 16-channel voltmeter is ~ $80 (~ $5/channel).
3.2. Evaluation of the PiClops Raspberry Pi PCB cell cycling daughter board:
To evaluate the performance of the PiClops board (as described in section 2.5) resistors were placed across
the battery test leads and two different extreme currents were tested (1 A and 10 mA). On the 100 µA
current range the stability of the current (at 1 A) is ±0.0175% full scale range (FSR) [1]. On the 10 mA
current range the stability of the current (at 10 mA) is ±0.054% FSR [1]. The quoted accuracy of popular
cell cycling equipment providers like Biologic and Maccor are 0.1% (https://www.bio-logic.net/wp-
content/uploads/2016-bio-logic-vsp-VMP3.pdf) and 0.05% (http://www.maccor.com/ProductDocs/Data
Sheet for Series 4000 Test System.pdf) FSR respectively. The PiClops has accuracy similar to the quoted
performance of significantly more expensive hardware providers.
To test the cell cycling performance of the PiClops circuit a ~ 300 mAh commercial Li-ion pouch cell was
cycled using the PiClops circuit (e.g. https://www.adafruit.com/product/2750), then moved to a Neware
BTS4000-5V10mA to continue testing under the same cycle and save parameters. Figure 7 shows the
results of the tests.
Figure 7 shows that the voltage-capacity profiles measured by the PiClops are virtually identical to the
voltage-capacity profiles measured by the Neware BTS4000-5V10mA. It should be noted that the PiClops
circuit is less expensive compared to the Neware BTS4000-5V10mA; which is one of the least expensive
battery testing units available commercially.
The software used to control the PiClops board is coded in Python3 and freely available (contact
corresponding author). The software allows the user to specify:
1. Current: 0 – 10 mA with automatic selection of optimal current range
2. Upper/lower voltage limits (±5V)
3. Frequency of recording data (e.g. if time changes by t or voltage changes by V)
4. Electrode mass (for gravimetric capacity calculations), and
5. Number of cycles
The software also keeps track of cycle number and cycle capacity (in mAh or mAh/g). The data can be
output to a screen and is recorded locally (on the SD card) in a comma separated (.csv) text file. Users have
access to the raw code in text readable format (i.e. users can alter the code at will). Furthermore, users have
access to the rest of the Raspberry Pi’s capabilities (e.g. GPIO pins, USB, HDMI, audio, etc). The GPIO
pins provide code level access to the external environment meaning that instruments/devices can be turned
on/off based on code level events. This can be as simple as turning an LED on when a battery is fully
charged, or as complicated as shutting off main power and closing a fire-proof door in an unexpected event.
A wide variety of additional sensors can be added to the Raspberry Pi as well.
As of the writing of this manuscript several PiClop units haves been in constant operation for over six
months and thousands of cumulative cycles. The Raspberry Pi can accommodate SD cards of at least 64
GB, providing more than sufficient storage space (typical file size is a few MBs).
The Raspberry Pi’s are usually operated in ‘headless’ mode (with a static IP). A remote connection is made
over a wifi network using a virtual network connection (e.g. TightVNC client running on the Pi and
UltraVNC viewer on a Windows based computer). This allows the units to be operated without a dedicated
mouse, keyboard or monitor. The units are portable and compact. The authors use the units for several
experiments where dedicated cycling equipment is not readily available (e.g. in glove boxes, near X-ray
diffractometers, far away from cell testing areas).
The cost for a PiClops can be as low as $75/channel if appropriate volumes of PCB’s are ordered (e.g. >
10000). Cost per channel is higher at lower build orders but still very reasonable compared to commercial
battery cycling equipment ($125-$5000/channel).
3.3. Evaluation of the APSS:
The APSS was used to measure the volume of a cluster of three pouch cells connected in parallel. The cells
were recovered from a USB battery pack (~ 10 Ah). For simplicity the three cells will be simply referred to
as ‘the pouch cell’. The apparent mass, mbalance, of the pouch cell suspended in pump oil was found to be
approximately 158 g by the APSS. Note that this brought the mass applied to the strain gauge outside of its
rated range (100 g). However, the experiment is only concerned with relative changes in mbalance. Hence, the
accuracy of absolute mass measurements was of little importance.
The pouch cell was cycled on a Neware BTS-4008-5V6A battery testing system using a constant-current,
constant voltage (CCCV) cycling profile. The cell was cycled between 4.2 and 3 V using a constant current
of ±500 mA (~ C/20), and a CV current cut-off of 100 mA. The APSS was enclosed in an insulated box to
limit short timescale room temperature fluctuations and rogue air currents. Figure 8 shows cell voltage and
volume data collected for ~ 80 hours. There is a clear correlation between the change in cell volume and
the cell’s state of charge (SOC). Voltage maxima corresponded exactly with volume maxima (Figure 8,
dashed green lines) and the minimum voltage corresponded to the minimum volume (Figure 8, dashed red
line). This volume change corresponds to the de/lithiation of the cathode/anode, which should vary by 1-3%
[7].
The peak-to-trough volume change of the pouch cell was just under 1.50 mL. The total volume of the cell
(Vtotal) was 130 mL. Therefore, the pouch cell’s volume changed by ~ 1.2% of it’s total volume. This agrees
with [7], where the volume of a 2.50 mL pouch cell was found to vary by 0.03 mL, or 1.2% during cycling.
Figure 9 shows APSS volume and cell voltage data collected for over 350 hours (two weeks). The pouch
cell completed just over 8 full charge/discharge cycles. Each voltage cycle clearly corresponds to a volume
change cycle. Each volume change cycle is nearly identical and the APSS software was stable for the
duration of this test.
The APSS used for these experiments has since been upgraded to have two independent testing channels. A
simple GUI has been implemented in the data collection software. Using a single Raspberry Pi computer, it
is possible to construct an APSS with up to 9 independent channels. This corresponds to a cost of ~
$6/channel.
Furthermore, cells of virtually any size can be studied. The authors have experience testing cells up to 60
Ah in capacity. Testing large cell packs (e.g. hundreds of Ah) is also feasible.
The APSS has also been used to perform tensile strength experiments (e.g. stretch and break testing) on
polymer composites (data not shown).
3.4. Evaluation of the Tap density analyser:
The tap density analyser built by Elcora (Figure 10). was compared to a commercial tap density analyser.
EL-I-C6 graphite powder was tested in both units. The tap density analysis was the same for both units
(0.95 g/cm3), illustrating the effectiveness of Elcora’s inexpensive tap density analyser.
4. Conclusions
The high cost of testing hardware is hindering the rapid discovery of new battery technologies. This paper has
shown how inexpensive testing hardware can be built using simple, low-cost circuit components and Raspberry
Pi/Arduino’s. Inexpensive testing hardware can accelerate the discovery of new battery materials by allowing
researchers to purchase more testing hardware at a lower cost.
Table 1 - Lithiation time at C/20 and corresponding lithiation gravimetric capacities
Lithiation time
@ C/20 (hrs)
Lithiation capacity
(mAh/g)
2 37.3
4 73.4
6 111.3
8 147.5
10 186.2
12 222.1
16 298.7
20 367.1
Figure 1 - 16 channel OCV monitoring circuit connected to a Raspberry Pi
Figure 2 – Simple battery testing circuit
Figure 3 - PiClops battery testing daughter board plugged into a Raspberry Pi
Figure 4 - Top-view (left) and side-view (right) of the APSS in an insulating container
Figure 5 - Open Circuit Voltage monitoring of eight graphite-Li half cells lithiated to different capacities. The
graph on the left shows cell voltage vs. log of time (hrs) so the formation of different LiCX phases are easier to
see. The voltage at which different LiCX phases are formed is labelled. The graph on the right plots cell voltage
vs. time in days. The legend describes which colour corresponds to which tests (e.g. lithiated for X hours at
C/20)
Figure 6 - OCV monitoring of partially lithiated graphite-Li half cells. Data zoomed in from Figure 5 showing
the relatively sharp transition from LiC12 to LiC18
Figure 7 – Voltage vs. capacity profiles of a Li-ion pouch cell as measured by the PiClops circuit (red curve; 10
cycles) and a commercial cell testing system (Neware BTS4000-5V10mA; blue curve; 18 cycles). The cell was
charged to 4200 mV and discharged to 3000 mV at ±10 mA using both cell cycling systems
Figure 8 - Change in cell voltage and cell volume (measured by the APSS) vs. time
Figure 9- Change in cell voltage and cell volume (measured by the APSS) vs. time
Figure 10 - Tap density analyser made from 3D printed parts and controlled by an Arduino UNO
References
[1] Shane D. Beattie, http://past.ukenergystorage.co/2015/assets/talks/Shane-Beattie.pdf [2] C. P. Aiken; J. Xia; D. Y. Wang; D. A. Stevens; S. Trussler and J. R. Dahn, An Apparatus for the Study of In Situ Gas Evolution in Li-Ion Pouch Cells. Journal of The Electrochemical Society, 161, (2014); DOI: 10.1149/2.0151410jes [3] J. R. Dahn, Phase diagram of LixC6, Phys. Rev. B, 44, 9170 (1991); DOI:10.1103/PhysRevB.44.9170 [4] M. B. Pinson and M.Z. Bazant, Theory of SEI Formation in Rechargeable Batteries: Capacity Fade, Accelerated Aging and Lifetime Prediction. Journal of The Electrochemical Society. 160(2), A243 (2013); DOI.org/10.1149/2.044302jes [5] Nupur Nikkan Sinha, Thomas H Marks, Hannah M Dahn, Aaron J Smith, J.C. Burns, Dillon J Coyle, Jackson J Dahn, J.R. Dahn, The Rate of Active Lithium Loss from a Soft Carbon Negative Electrode as a Function of Temperature, Time and Electrode Potential. Journal of The Electrochemical Society. 159(10), A1672-A1681 (2012); DOI: 10.1149/2.048210jes [6] Nupur Nikkan Sinha, AJ Smith, Gaurav Jain, Aaron J Smith, Chris J Burns, K. W. Eberman, Erik Scott, J. P. Gardner, J.R. Dahn, The use of elevated temperature storage experiments to learn about parasitic reactions in wound LiCoO2/graphite cells. Journal of The Electrochemical Society. 158(11), A1194-A1201 (2011); DOI: 10.1149/2.007111jes [7] A. J. Louli, "Probing the Reversible and Irreversible Volume Expansion Observed in Li-ion Pouch Cells," Masters Thesis, Dalhousie University, Halifax (2017); http://hdl.handle.net/10222/73460