Digital Twin Architecture for Mobile EV Fast Chargers 

Overview

Uniper AG, a leading international energy company, needed a digital twin for its EV fast chargers. The company operates across power generation, energy trading, and infrastructure. In the EV space, Uniper runs two mobile fast chargers (MFCs) that support the growing charging ecosystem. However, getting the most out of these units took more than hardware. It required a connected, edge-cloud hybrid system that manages the chargers intelligently while keeping people in oversight.

Challenge: Running EV Fast Chargers Without a Digital Twin

Operating a distributed fleet of mobile EV fast chargers brings complex operational demands. Each charger is an IoT device deployed in the field, often in dynamic or remote locations. As a result, physical inspection and manual troubleshooting are costly and slow. 

Uniper faced three interconnected challenges: 

1. No real-time visibility into device health. This made it hard to detect and diagnose errors before they impacted availability. 
2. High operation efforts in logistics and device management. Transport orders and deployment processes required manual coordination with logistics partners, which slowed down operational workflows as the fleet scaled.  
3. Logistics inefficiency, with no predictive model to optimize where and when to deploy chargers.

Without a unified, intelligent architecture, operational teams could only react to problems. For a rapidly scaling EV infrastructure, that was a significant limitation.

Our Solution: A Digital Twin for EV Fast Chargers

Uniper has partnered with our team at iits-consulting to design and implement a Digital Twin Architecture for their fleet of mobile EV fast chargers. This scalable, cloud-connected solution replaces fragmented, manual operations with a unified platform that gives operations team full visibility and control over every device in the field in real time. 

At the device level, each charger is equipped with an on-site edge computing unit that continuously collects sensor data, monitors hardware status, and runs AI-powered anomaly detection locally. This means faults can be identified and flagged immediately, without waiting for data to reach the cloud. A secure, bidirectional connection to the cloud enables remote monitoring and control, so teams can diagnose and respond to issues from anywhere. Implemented remote control capabilities include changing device settings, triggering emergency shutdown, rolling out advertisements, adjusting screen brightness, and controlling LEDs.  

In the cloud, a purpose-built IoT platform ingests data from the entire fleet, routes it through dedicated services for enrichment, event detection, and process management, and makes it available to operations teams through intuitive web applications. A fully simulated device environment was built in parallel with the physical hardware, allowing the team to develop and stress-test the entire IT infrastructure at scale. This proved that the platform was ready to handle a fleet of 1,000 devices at a time when only a limited number of hardware prototypes were available. 

Machine learning models are integrated throughout the platform to forecast charger demand by location and time, enabling smarter logistics decisions and more efficient fleet positioning across Uniper’s network. 

Business Impact

Live monitoring and remote diagnostics reduced the need for on-site interventions. This improved both fleet uptime and operational response time.

Virtual commissioning enabled faster, risk-free rollouts of new devices and configurations, because testing no longer depends on physical deployment. 

ML-driven logistics optimization improved charger placement decisions and increased fleet utilization.

iits-consulting also delivered a scalable, reusable IoT cloud architecture. Uniper can apply it to other asset types beyond EV charging, such as industrial equipment and buildings.

Finally, the microservices-based design lets each service scale independently. This supports Uniper’s long-term growth in e-mobility infrastructure.