We live in a time when energy and electric devices define and shape our everyday experiences—from transportation to communications, work to the grid infrastructure that makes it all possible.
It’s no wonder that the production and supply of Li-ion batteries is expected to skyrocket. According to Bloomberg New Energy, global battery storage capacity will reach 4,500 GWh by 2050, compared to 2.85 GWh today.
As the need for energy storage continues to grow at an exponential rate, the world is crying out for a safer, more efficient solution to the production, management, re-use and recycling of Li-ion batteries.
Modern life, the environment and the global economy all depend on it.
Traditional battery management systems (BMS) use a combination of voltage (V), current (I), and temperature (T) inputs to determine how to safely operate Li-ion batteries and output state-of-charge (SoC) and state-of-health (SoH). The issue is that incumbent BMS technology doesn’t actually measure SoC and SoH – it estimates them.
As such, a battery’s charge and capacity are both calculated with some degree of error, and the consequences of this error, aggregated across time and billions of batteries across the world, are dramatic. Untold dollars are wasted annually, along with millions of usable kWh, while many tons of CO2 are released into the atmosphere.
Various efforts have been devised to avoid or resolve this fundamental problem, but none have been effective because they continue to rely on estimations, all with the same V, I, and T combination.
But at long last there’s now a way to prevent battery management errors—and it revolves around the concept of resolution.
In this context, resolution refers to two components—accuracy and precision. Both made possible by observing batteries from the inside, at the molecular level.
With high accuracy and precision, we measure two critical parameters —State-of-Health (SoH) and State-of-Charge (SoC), both of which dictate how a BMS for a battery-operated vehicle or device operates.
As described above, Incumbent systems can’t deliver high resolution, creating different problems depending on the application.
• EVs using NMC batteries have precise voltage measurements but low SoH accuracy. Thus, as the system degrades over time (lowering SoH) the high-precision voltage measurement is rendered meaningless.
• ESS solutions using LFP batteries have both low accuracy and low precision. This is caused by the voltage flatness characteristic of LFP batteries (SoC) and their reliance on pre-determined look-up tables to determine SoH.
TITAN delivers superior resolution—helping batteries run better, safer, and longer—through the magic of ultrasound.
Ultrasound uses high frequency (above 20kHz) energy to conduct diagnostics and make real-time measurements. It’s been used for the last 50 years in applications as diverse as medical devices, building integrity inspection, nuclear plants, back up sensors in cars, and fingerprint sensors in phones.
Just like batteries, ultrasound is everywhere.
It’s nothing less than a game changer in battery knowledge. We get 2D real-time diagnostics of batteries at the molecular level, which translates into very high accuracy and high precision SoC/SoH measurements. As an added bonus, we also achieve unprecedented safety through an early warning/detection system made possible by the very nature of ultrasound.
Sound travels through different mediums at a different velocity (water, wood, air, etc.). This works very well for determining the SoC of a battery. A fully charged battery is stiffer, the Li-ions are in the anode and the speed of sound is faster than when the battery is less charged. Through ultrasound we can measure SoC with 99% accuracy and precision at all stages of the battery’s life, regardless of the current applied, since the SoC corresponds to the volume of Li-ions physically present in the anode.
The graph below shows different SoC values which correspond to different speeds (time-of-flight) in a typical Li-ion battery matrix:
Ultrasound is highly effective at detection/evaluation, dimensional measurements, material characterization, and revealing changes in materials, which is exactly what happens as a battery ages. Several chemical processes influence the physical properties of a battery, and therefore its capacity, over time. One of the dominant degradation mechanisms is the growth of the secondary solid electrolyte interface (SSEI), a plaque (long organic polymer chain) which prevents the normal flow of Li-ions from the anode to the cathode.
We see outgassing, lithium plating and dendrite growth as physical manifestations as well, which is CRITICAL for fast-charging applications.
To date, our system has been proven to deliver real-time SoC/SoH accuracy at 99% for NMC, LMO, and LFP batteries.