Does the battery deliver what was promised?

If not: the battery or how it was used? I assess this independently, for electric vehicles and battery storage.

Dr. Gerald Sammer Dr. Gerald Sammer Owner, Simotive e.U. Independent Technical Expert for Electric Vehicles & Battery Energy Storage Systems

Is your case among these?

Concrete questions from practice, sorted by client. Law firms will find their cases in all three groups. In the initial consultation, we clarify which data exist and how you can obtain them.

What sets me apart

Battery tests and software deliver figures. I assess what a figure means in your case.

With an electric vehicle, the manufacturer says the battery was fast-charged too often. The owner says it was weak from the start. With a storage system, the supplier says the system was used too heavily. The operator says the cells are weaker than promised. I examine independently which claim holds.

Before an investment, the performance figures usually come from the supplier itself. I check them before you sign.

Battery module with the influencing factors temperature, charging, ageing and time
  • Independent. I am not tied to any manufacturer, supplier, or software vendor. My product is my expertise.
  • Your case, your usage. Most battery tests measure the condition without taking into account how the battery was used. From the physics of the battery, I determine which value is to be expected under exactly this usage. You learn whether the measured value is normal for this use.
  • Development experience. I spent 27 years at AVL. Vehicle manufacturers have their powertrains and batteries developed and tested there. I know the manufacturers' data and analyses from my own work.
  • Verifiable. My calculation is open. Every step can be checked. The result can be used in court.

One case, step by step

How a measured loss becomes a reasoned finding.

The Case

41 percent less range than the data sheet states

22 electric light-duty trucks in a delivery fleet in northern Germany. Since the second winter, drivers have reported sharply declining range. The operator suspects a battery defect, the leasing company holds the usage responsible.

-41% range in the third winter, measured against the manufacturer's figure

Normal ageing or a defect?

Step 1: Capture the usage

How were the vehicles charged?

Vehicle data and the logs of the charging stations show: the fleet charges mostly at fast chargers, on average 1.2 times a day, often only once the charge level is below 15 percent.

Fast charging
73%
Normal charging
20%
Slow charging
7%
Frequent fast charging makes a battery age faster. At first, this supports the leasing company.
Step 2: Model the battery

How much should the batteries still store today?

A simulation model knows the battery type and the vehicle, but not the measurements of this fleet. All it learns is how the vehicles were charged and driven and how cold it was in Hamburg. From this, it predicts how much energy the batteries ought to store today. Separately, I determine from the charging logs how much they actually store. I do not rely on the vehicle's own display for this.

Storage capacity 100% 95% 90% 85% 0 1 year 2 years 3 y. Expected from the model Measured from charging logs
The model never saw the measurements and matches them to within 3 percent across three years.
Step 3: Separate the causes

Where do the 41 percent come from?

In the model, each influence can be switched off on its own. This shows how much it accounts for.

Cold (-8 °C)
-19%
Heating
-11%
Ageing
-7%
Route and driving style
-4%
No battery defect. In three years, the batteries lost 7 percent of their storage capacity. That is normal for this usage. Most of the loss comes from cold and heating and disappears again in summer.
Result

Settled without court

The report discloses every calculation step. On this basis, the operator and the leasing company reach an agreement. Both are spared a lawsuit.

3 weeks to the report
0 vehicles with a battery defect

This is how I work. Do you have a similar case?

Request an initial consultation

How I work

The basis is the data that the vehicle, charging station, or system records anyway. I evaluate it in three steps.

  1. Capture the usage. I establish how the battery was actually used: how often and how fast it was charged, at which temperatures, and how heavily it was loaded.
  2. Model the battery. A simulation model reproduces how the battery responds to charging, temperature, and load. I match it against measurements until it reproduces the real behaviour.
  3. Separate the causes. The model shows which value is to be expected under this usage. If the measurement deviates, I break the deviation down into its causes and quantify each one separately.
Simulation-based methodology, vehicle and data analysis

Environment, usage, or battery?

If an electric vehicle falls short on range, the cause is the environment, the way it is used, or the battery, often several at once. Temperature belongs to the environment; route, driving style, and heating, for example, belong to usage. Set the controls. You see how much each influence accounts for on its own.

508 km
Simulated electric vehicle with visible battery pack
Battery health: 98%
Environment
Usage
Battery

About

I founded simotive.ai to resolve technically contested cases independently. My work begins where measurement and diagnostics no longer give a clear answer.

Experience
27 years at AVL List GmbH, more than 20 of them in leadership, most recently responsible for the business strategy of batteries and electric powertrains. Alongside that, 15 years until 2026 on the technical steering committee of ASAM, the standardization body of the automotive industry.
Education
Dipl.-Ing. in Telematics, TU Graz, with a thesis on artificial intelligence and machine learning. Dr. techn. in Mechanical Engineering and Business Economics with the dissertation "Success Factors for Automotive Testing". Advanced training in battery systems and electric vehicles, TH Ingolstadt 2022.
Fields
Battery, battery management, vehicle software, electrified powertrain, and stationary storage systems.
Speaking
Regularly at international technical conferences.

Dr. Gerald Sammer
Founder and Managing Director, simotive.ai

Dr. Gerald Sammer, Founder and Managing Director of simotive.ai

Why now

  • 29 November 2026. Euro 7 makes battery durability part of type approval. New car types must still deliver 80 percent of their certified energy after five years or 100,000 km, and 72 percent after eight years or 160,000 km.
  • 9 December 2026. The new EU Product Liability Directive treats software as a product, introduces disclosure obligations, and eases the burden of proof for claimants. Cases become arguable that previously failed on the evidence.
  • 18 February 2027. Electric-vehicle and industrial batteries above 2 kWh need a digital battery passport carrying service-life and condition figures. What it states has to hold.
  • Grid-scale storage. By the end of March 2026 Germany had 489 grid-scale systems of 1 MWh or more on the register. In the first quarter of 2026 their additions exceeded home storage for the first time. In Austria the roughly 3.2 GWh installed by mid-2026 still consisted mostly of units below 50 kWh. The warranty cases are still ahead.

Contact

Are you facing a decision with real exposure, an unexplained failure, or a technical dispute? In an initial conversation we establish whether an independent technical analysis helps.

gerald.sammer@simotive.ai

Free initial consultation