State of Charge: Why It’s Harder to Measure Than You Think [The Battery Cycle #2]

In 2021, Claudius Jehle, CEO of volytica diagnostics GmbH, and Sustainable Bus launched a series of articles around the “The Battery Cycle”. They shed light on the complexities of Li-Ion batteries and provided valuable insights for anyone involved in electric mobility. In 2025 and 2026, the articles were updated with real-world data and lessons learned to understand how battery chemistry affects real-world operations. (The article was first published in May 2021, this is a revised version.)
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In our last article on battery chemistry, we explained both parallels and differences of the various subspecies of Li-Ion batteries such as NMC, LFP and LTO. The underlying basic principle is always the same, which we explained using the – to some extent ironical, but ultimately very helpful – analogy of parachuters for ions, congesting at the exit of their vessel (aka anode) during discharge, their adventurous and tedious travel through electrolyte and separator, their crowding during landing and finally slow migration into and settling in the opposite electrode (aka cathode).

Today we will stay figurative to explain the seemingly boring topic State of Charge (SOC) and give some interesting insights and take-aways. In fact, it is surprisingly difficult for the onboard electronics (which we will refer to as BMS, battery management system) to determine the SOC even if these systems have signals like cell voltages, currents and temperatures directly at hand.

State of Charge: How Full is it?

Unfortunately, our microscopic (i.e. on atom/ion level) parachuter analogy becomes clumsy when explaining a macroscopic effect like SOC – so think of a glass with a certain content (trillions of parachuters). The maximum possible content is the capacity. The SOC is simply content per capacity, i.e. 150ml in a 300ml glass results in 50% SOC. Ha, we’re done, great.

Of course it doesn’t stop here, unfortunately. The only signals the BMS can really measure, in the very sense of the word, are the cell voltages and the current flowing through the cells (okay, and temperature, but that’s not needed for now). Yes, it doesn’t “measure” SOC, it’s estimating it!

Why Measurement is Hard

In the analogy of a glass, the cell voltage is synonymous for the current filling height. If you can accurately measure this, and you have a translation table to convert height into content, you should be good. That’s exactly how a BMS determines SOC…

…once in a while, at least, because most BMS cannot do this continuously: there is something that I call “foam”*. The liquid in the glass is not water, it’s foamy beer. When drafting, gulping or shaking (i.e. when using the battery, or charging it), a layer of foam builds up, making it difficult even for the trained eye to measure filling height to the fraction of millimetres. This phenomenon and the characteristics of this “foamy voltage” (mostly called “overpotentials”) are highly dependent on chemistry, immediate past current flow, temperature and many other nasty things.

*Disclaimer: There is no real foam, again just an analogy. For the geekier readers: The congestion of ions at the gates to the electrodes, i.e. them slowing down before entering the anode or cathode, and their then ensuing slow and tedious migration into that solid material, is causing the macroscopic effect of the settling voltages (foam) after current was flowing. It’s called the overpotential voltages that build up when current is flowing and slowly reduce after this has stopped. Exactly like drafting a beer.

The foam/overpotentials slowly decay, just like on a beer. The BMS frequently needs phases of idle and rest of typically 30-60 minutes, to be able to reset the SOC. In the busy times in-between, the only way the BMS can somehow keep track of SOC is to count how much beer (=current) went in and out and adding/subtracting it from the last known reset value. This is called “Coulomb Counting”, and the longer the time from last reset, the farther off this tally taking will be.

Determining State of Charge is Not an Easy Task

Guess what, we’re still not done. So not only needs the BMS frequent and prolonged phases of rest to reset, and in the meantime roughly tracks SOC by tally taking, the shape of the glass, the mentioned ‘translation table’ is yet another obstacle.

In the left of the illustration, a cylindrical glass is shown. Easy game: 2x as much filling height means 2x the SOC, absolutely linear relationship. Sadly, that’s not the case for Li ion batteries: as alluded already in the last article, depending on chemistry, this (and other properties) of cells varies significantly. The “glass shapes” are highly irregular and manifold across chemistries.

To get images into your head, LFP looks like a broad, bellied, bulbous wine decanter and NMC has rather an elongated candy-shape (narrow, fairly straight, narrow). This lookup-table to translate height (voltage) to content is determined once by the manufacturer in a lab and programmed into the BMS; it is called the “open-circuit voltage characteristics”, or also OCV curve.

One Battery, One Number?

The main challenge, as one can easily imagine, comes during operation: 5mm of height in the belly-part can be a good 20 or 30% of total liquid content! In fact, LFP is so broad that between ca. 20 to 90% the voltage virtually doesn’t change. The slightest measurement error can result in extreme SOC errors. And then there is also this foam!

Imagine the BMS of an LFP battery joyfully finds itself one of those deadly needed idle periods and prepares for a reset – it waits until foam has settled (hoping that the asset remains at rest) but then realizes that it came to rest in the bellied part! The voltage measurement could equally translate to 20% or 40% SOC – an ordeal!

It Gets Worse: “A Battery is 1,000 Batteries Pretending to be One”

I will wrap things up in a moment, but for the full truth, you need to bear with me for another moment. What you have learnt so far is that, particularly for LFP, accurate SOC determination is sometimes sheer luck. The often heard “…but Mr. Jehle, the BMS has full access to everything in microsecond resolution” is fair but doesn’t change physics.

So far, we spoke specifically about how the BMS determines cell-SOC. But you are interested in the battery system SOC. … the (Master-)BMS has the thankless task to come up with one single representative SOC for a flock of hundreds or thousands of individual cell values. And yes, they differ. Not in theory, but in practice.

For reasons we will dedicate at least one article to, this “disbalance” (also called imbalance or asymmetry) causes a challenge. The BMS cannot do the obvious and take an average of all cell SOC, because when discharging, the cells below average will be empty first and demand a stop at >0% SOC, and vice-versa when charging. So oftentimes there is sophisticated logic at play when the BMS performs this task, and believe me, sometimes making things worse.

So what?

Wait, what does this mean in practice? We will dig a bit deeper in the following articles about the most detrimental effects, namely sudden standstill (“sudden depletion events”) and inhomogeneous degradation, but one thing is universal: I estimate the average SOC error to be somewhere between 5-10%, reaching up to 10-20% in e.g. low-cost systems, high-duty (few breaks) applications and especially LFP/LTO systems. This is significant – a battery that’s off by 10% is, basically, 10% oversized!

Inaccurate SOC causes batteries to be oversized, operations to be erratic, assets not used to their true potential, money being wasted and frustration rising.

* There are two fundamental reasons why Coulomb Counting is inaccurate: Firstly, because every current sensor has tiny offsets and biases; if you keep adding them up, they accumulate and will cause the assessment to “drift away”. I bet when you drink a large glass of beer and had to guess the exact amount of remaining beer just by counting your sips, you’d fail. At least I would. And secondly, the BMS needs the exact maximum capacity (glass size), which shrinks as the battery ages (we will cover than in the article about SOH), which is an even more challenging task, and BMS-SOH is notoriously wrong.

Looking Ahead in the Series

In the next article on charging batteries, we will explain fast charging and different charging options to keep your battery running for a long time.

All knowledge articles of the battery cycle:
Intro – The Battery Cycle – opening the black box
1 – NMC, LFP, LTO: What’s the Difference in Battery Chemistry? – energy density, safety, lifetime, cost
2 – State of Charge: Why It’s Harder to Measure Than You Think – about really knowing how full your battery is
3 – Fast Charging Explained: Why More Power Doesn’t Mean Less Time – how to keep a battery healthy
4 – Why an LFP Bus Can Suddenly Stop: The Battery’s Weakest Cell – why imbalances define the limit
5 – Battery SoH: The Number That Doesn’t Tell the Whole Story – State of Health is mostly misunderstood
6 – Stress Level: The Key Drivers of Battery Degradation – what really hurts a battery
7 – Battery Data: Are You Seeing the Full Picture? – use and interpret your data correctly