Slalom and Scheidt & Bachmann – Solving EV charging infrastructure challenges with data and AI
Scheidt & Bachmann Energy Retail Solutions partnered with Slalom to develop a proprietary AI solution based on predictive analytics. The objective was to bring greater transparency and reliability to EV charging infrastructure by improving utilisation, availability and operational efficiency of charging points.
The result is a data‑driven system that reduces uncertainty for drivers while giving operators new tools to manage and optimise their charging parks more effectively.
Outcome
SIQMA FlowMax.AI addresses key pain points in today’s charging infrastructure:
- more accurate availability forecasts
- improved utilisation of charging points
- increased transparency for drivers
- higher operational reliability for operators
By doing so, the solution actively supports the transition to electric mobility.
Market context: rapid growth, limited transparency
Electric mobility continues to grow at pace. However, this development is often constrained by structural challenges such as limited expansion of charging infrastructure, unclear pricing models and insufficient transparency around availability and location of charging points.
With its strong background in fuel stations, charging parks and energy retail, Scheidt & Bachmann Energy Retail Solutions set out to tackle these challenges where they most directly impact the charging experience – at the point of use.
“E‑mobility will continue to gain ground and dominate the market within the next few years. With SIQMA FlowMax.AI, we underline our ambition to transform our business model early and to offer unique solutions that did not previously exist.”
“E‑mobility is growing rapidly – but only with transparency, reliability and a user‑friendly infrastructure will it become accessible for everyone. This is where we take responsibility and actively shape the future of charging.”
"Projects like this show how AI innovation can solve concrete infrastructure problems and transform entire industries. We have supported Scheidt & Bachmann in using data and artificial intelligence to establish a future-oriented business model that creates real added value for end customers."
The human factor: predicting the unpredictable
One of the solution’s most demanding features is its ability to predict when an occupied charging point will become available again. Unlike conventional refuelling, charging processes are influenced by numerous variables such as target charge level, dwell time or nearby amenities.
To meet these requirements, Scheidt & Bachmann Energy Retail Solutions and Slalom developed a proof of concept within a short timeframe. The model combines open data sources, purchased datasets and well‑founded assumptions to deliver reliable forecasts early in a charging session.
Within the first five minutes of a charging session, we were able to reliably predict when the charging point would be available again. Slalom’s data and AWS expertise enabled us to develop, scale and implement the pilot in a very short time and to build up the necessary know‑how. AI‑based forecasting cannot eliminate every outlier, but most predictions are accurate to within a few minutes. Our long‑term goal is to further improve average forecast accuracy and enable AI‑driven e‑mobility experiences for both operators and EV drivers.
From pilot to operational solution
Following a successful proof of concept, the solution was transferred to live operation. During this phase, differences between training data and live data initially reduced forecast accuracy. Through additional model training and the integration of further parameters – such as location, day of the week, time of day, weather and surrounding amenities – forecast performance was significantly improved.
To ensure stable quality, a central KPI was defined: the Mean Average Percentage Error (MAPE). Deviations trigger automatic alerts, allowing continuous optimisation of the model.
“With SIQMA FlowMax.AI, we are setting a new standard in charging: precise forecasts, clear information and a reliable charging experience. Our goal is to reduce complexity and create real added value for operators and drivers.”
Jörg M. Heilingbrunner, CEO, Scheidt & Bachmann Energy Retail Solutions
End‑to‑end solution with future potential
Operators can use SIQMA FlowMax.AI as a standalone solution or combine it with digital signage, such as SIQMA Sign, to display pricing, availability and charging location information directly on site. This enables:
- improved utilisation of charging parks
- seamless charging experiences for drivers
- stronger customer loyalty through transparency
The solution is already deployed in operational environments and continues to learn from real‑world data, further enhancing forecast accuracy over time. Alternatively, operators can integrate SIQMA FlowMax.AI via interfaces into their own platforms and applications.
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