SoH Differences and Discrepancies - What are the causes?

Is the SoH shown on the vehicle display correct? Answering this question is not as easy as it seems. The relevant SoH of a battery strongly depends on the reliability of the data used for SoH calculation.

The Health of the Traction Battery, also known as State of Health (SoH), is currently a hotly debated topic in the field of battery diagnostics. The SoH of the battery is one of the most important parameters for its condition and material value. In addition, the SoH is also an indicator of safe driving and acceleration.

The SoH provides information about how well a battery is still functioning and how much energy it can store compared to its new condition. This leads to an important question for many electric car drivers: is the SoH shown on the vehicle display correct? Answering that is not quite as simple as it seems. The relevant SoH of a battery also depends heavily on the reliability of the data used to calculate the SoH.

To understand this better, you need to know

1. what the SoH is,
2. how it is calculated,
3. why different sources, provide different data. - We answer that in this text.

The SoH values of different sources are basically not comparable

To illustrate the problem, we have created a graph with 1000 statistically relevant cases, in which the SoH values read out are compared and visualized with the SoH values actually analyzed on the basis of real data. The graph shows the deviations in percentage points (%P) between these two values. "Read-out SoH values" are those calculated by the battery management system (BMS) of the respective vehicle and used for range calculation. "SoH values analyzed based on real data" are exact battery health results generated via a process, e.g., discharge process.

The zero line representing exact SoH values is the baseline. The SoH values read out from it are represented as lines to the left (SoH value read out is less than the actual SoH value) or to the right (SoH value read out is greater than the actual SoH value).

Whether the absolute value is 90% or 50% SoH, for example, is irrelevant for this task. What is important is how much the readout values differ from the measured actual values. In some cases the deviation of the comparative values is ±5 %P, in extreme cases even up to +91 %P.

The reasons for the discrepancies

There are several reasons for these discrepancies, which we can divide into different groups:

• Technical reasons: This extreme scatter simply comes from the inaccuracy of the algorithm used to determine battery health. In the battery management system (BMS), the health status is projected. Each BMS manufacturer (indeed, with each software variant) creates an algorithm for this purpose, based on models of battery cells, operating models, and mathematical models. These are intended to map the health in the BMS. Very small processors with limited power are used for conducting the calculations. Over the course of their lives, these processors need to compute SoH estimates as accurately as possible, but here we see that many of these processors are reaching their performance limits in doing so. The AVILOO assessment method is based on the extremely powerful AVILOO Battery Data Cloud and is continuously assessing data, which is a huge technical advantage.

• Real (real-time measured) data vs. readout data: Real data is needed to calculate the actual SoH value. This means that data must be collected during a process (discharging, charging, etc.). However, the BMS works with statistically extrapolated laboratory data.

• Use of various methods and non-uniformity approach: What also plays a role here with the zero line are always the same rules, methodologies and mathematical models adapted to different car models. Another scattering arises from the different manufacturer approaches. Manufacturer A uses method A, manufacturer B uses method B, etc. One bases its estimate on discharge, the other on charge. One measures by capacity, the other by energy. One manufacturer specifies that this applies at a certain discharge rate, e.g., the appropriate WLTP cycle. Another says "this is a very slow discharge" or "a very slow charge." Cell manufacturers, on the other hand, often have completely different definitions than car manufacturers. All of these factors contribute to a wide variation. However, the main reason is not only the different method, but also the inaccuracy in the algorithm. The use of different methods causes a scatter of about +15% to -10%. The remaining discrepancy is based on inaccuracies in the algorithm. However, this can change over time. A good example of this is a customer who read the SoH value of his battery and it was 80%, for example. After a software update in the workshop, the value was process-safe at 100%. So we hold here: The manufacturer itself, delivered before software update 80% SoH, after software update the SoH was suddenly at 100%.

So if you want to know how far you can actually drive with a vehicle without breaking down halfway, you should leave the measurement of the SoH value to those whose technology you know. At AVILOO, you not only get high quality calculated data, but also real values from the tested car. We make the health of the traction battery transparent for everyone. This is what we work for every day. Connect to detect.