eTruckCharge

As the project lead, HKA coordinates the collaborative project and public relations efforts. Using open-source components, it is developing a web-based software system that allows charging stations from multiple companies to be aggregated and pre-reserved by registered third parties. As a data foundation, the HKA is building a digital twin of the federated charging network that maps the charging infrastructure in real time without disclosing sensitive data. Using federated learning, it trains AI models to predict occupancy, arrival and departure times, charging statuses, and peak loads, thereby laying the foundation for a regional baseline model for the Upper Rhine region.

CESI is leading the work on security and resilience in the federated charging network. Charging stations, electric trucks, operators, and software systems form a highly interconnected IoT ecosystem that, as critical infrastructure, is particularly vulnerable to cyberattacks. To address this, CESI is developing a collaborative intrusion detection system based on federated learning and graph neural networks that detects anomalies and complex attacks—including zero-day attacks—without exchanging sensitive data. The system will be implemented on CESI’s federated learning platform, expanded to multiple locations, and finally integrated into the federated charging network’s software platform.

The RPTU develops algorithms for optimized charging and route planning for electric trucks, as well as optimal fast-charging profiles. In doing so, it takes into account grid contracts, battery dynamics, agreements with truck owners, and market prices for energy. The algorithms are validated in RPTU’s Power Hardware-in-the-Loop (PHIL) environment, which includes connected electric truck batteries and a grid simulator. In addition, RPTU is responsible for the system architecture and technical demonstrators and, upon completion of the project, will provide an open-source transfer package containing optimization algorithms, fast-charging profiles, and backend modules.

The CCI is leading the needs assessment and requirements analysis for the project. Using questionnaires and expert interviews, it gathers information from logistics providers and industrial companies on the technical, economic, and procedural framework conditions, including regulatory differences between Germany and France. These requirements are consolidated and validated in expert workshops with industry representatives and trade associations. In addition, the CCI participates in technical testing, the evaluation of results, and the establishment of channels for transferring knowledge to the French business community.

EMS coordinates the dissemination of results and their transfer to the target industries in the Upper Rhine region. Together with its associated partners, it develops feasible use cases and future services and documents processes, data flows, and interactions between logistics providers, dispatchers, truck drivers, charging station operators, and energy providers. It contributes its network of e-mobility providers and logistics operators, as well as its experience in testing charging stations and analyzing data. Through industry meetings, trade shows, and events, it makes the project results available to regional companies.

The FHNW University of Applied Sciences and Arts Northwestern Switzerland contributes its expertise in IT security and data protection in information systems. At the start of the project, it analyzes the interfaces, data flows, and potential vulnerabilities in the federated charging network’s IoT ecosystem, thereby laying the foundation for the security architecture. Together with CESI, it develops the collaborative intrusion detection system and conducts security tests on the software and systems. In this way, it helps ensure that the federated charging network can be operated safely and reliably for all stakeholders.