Photo courtesy of Nissan

With more electric vehicles (EVs) on the road, manufacturers must ensure that battery packs will not leak under normal field conditions, creating a performance issue or safety hazard for drivers and passengers.

A leaking battery is more than just an inconvenience for the vehicle owner. Lithium-ion, the most common form of rechargeable battery for EVs, can burst into flame or even explode.

Leak testing these large and structurally complex packs poses unique challenges. While air-leak testing is well established, battery pack testing best practices are still evolving. How can manufacturers efficiently and cost-effectively ensure quality and assure consumers that they have nothing to fear when getting behind the wheel?

Size, stability

Manufacturers want to keep battery packs as light and cost-effective as possible by using enclosure materials such as aluminum alloys, glass-fiber-reinforced polymers, or thermoset vinyl hybrid resins. That means part stability may suffer, and common test methods can easily create destructive amounts of force. This issue is only compounded by the large size and internal volume of the pack. More volume means more surface area, which increases vari- ability due to factors outside the control of the leak test instrument.

This can make it difficult to simulate the exact leak conditions these packs will experience in the field while meeting production requirements.

An employee at Nissan’s Smyrna, Tennessee, Vehicle Assembly Plant builds a lithium-ion battery pack for a Leaf electric vehicle (EV). Testing battery packs for leaks is a critical safety step for automakers.

Expansion

Due to material instability, any test that uses air to build pressure inside the pack can cause the volume to expand like a balloon, increasing the measured leak rate. Parts that balloon during testing can present inconsistencies in repeatability due to elastic/plastic deformation of the part.

We are, as always, governed by the ideal gas law: pressure (P) x volume (V) = amount of gas in moles (n) x universal gas constant (R) x absolute temperature (T) of the gas or PV=nRT. We know that pressure, volume, and temperature are all related in a closed system (which a leak test is). If the part temperature changes during a test, the pressure within the part will change.

By the same token, the change in volume means change in measured leak rate. If the part changes in volume during the fill portion of the test, it is also susceptible to leak rate changes.

Temperature, pressure impact

Changes in environmental conditions, or testing for water intrusion, can lead to negative pressure within the pack. This can easily cause the pack to shrink, which can mask a potential leak.

Environmental changes are transient. They could be weather-related, but typically large effects are due to opening bay doors or running machinery. The more flexible the part, the larger the effect, meaning we must consider the pressure differential and decide which test approach – creating negative or positive pressure within the pack – is best.

Test type

It’s a long-running debate – which is better, a pressure decay leak test or a mass flow leak test? The answer, as always, is it depends. Pressure decay measurements are volume dependant, while mass flow is volume independent.

Mass flow does not require calibration factors or PD cals (the slope and offset to convert a pressure change to a leak rate) and will read the same leak no matter how large the part in question. It’s important to remember that the measured leak will still vary between parts if the measurement is taken before each part has stabilized and reached thermal equilibrium.

Pressure decay, on the other hand, relies on the calibration factor to give an accurate measurement. If you use a pressure decay test for flexible battery packs, leak rate must be based on a PD cal factor. Volume references for calculation of leak rate will result in incorrect results.

Mass flow tests do not require managing cal values or cal factors; therefore, it may be a better choice for large and flexible battery packs. The test method eliminates variables in measurement due to variations in part stiffness.

Now, to contradict myself, I have also tested flexible parts that were more consistent when using pressure decay. In these cases, the physical characteristics of the part, the plastic and elastic deformation it underwent during a normal test, responded better to allowing the pressure to drop during the stabilize and test phases. This halted the continual elastic deformation the part exhibited using mass flow for the given cycle time of the station.

An employee at Fiat Chrysler Automobiles (FCA) Windsor Assembly Plant in Canada installs the 16kWh lithium-ion battery in the Chrysler Pacifica Hybrid. The battery pack is neatly packaged under the second-row floor in a battery case that retains maximum interior volume for passengers and cargo.
Photo courtesy of FCA US LLC

Data time

Whether it’s pressure decay or mass flow, the next step is deciding how to ensure the most accurate, reliable test possible.

We do this by recording all the traceable waveforms from the test and correlating these with the related data for environmental effects. So, we can document and visualize the impact that any variable has on tests. By measuring and accounting for variables, we can improve process repeatability.

In other words, understanding and tracking activity in our test environment, and correlating this with what is happening within the pack, gives us insight to control and account for changes in the environment, to ensure the most repeatable and reproducible test result for an air-based test.

Conclusion

Better data provide better visibility, or as the old cliché goes, garbage in - garbage out. If you are not measuring the right things, you can’t account for the variables that negatively impact the measured leak rate. Achieving a reliable and repeatable leak test for EV batteries requires modern digital sensors and data analytics.

This allows you to track and measure the impact of external changes in the environment and provide the insight to account for them. And, it allows optimization of the test cycle to ensure the ideal result is achieved in the shortest time. This allows the test station to keep pace with the speed of production and avoid staffing an additional parallel test station or stations.

With the right data and means to analyze that data, you can find test limits faster, calibrate test setup faster, run simulations that allow you to immediately see the impact of changes to test parameters, and hit gage repeatability and reproducibility (Gage R) and cycle time targets.

Sciemetric 

About the author: Rob Plumridge is a leak applications engineer and leak test specialist at Sciemetric. He can be reached at robertp@sciemetric.com.