Development of an automated test setup for RFID-based EV charging systems

Test automation of RFID authentication in AC wallbox. Purpose & Motivation. In modern development environments test automation tools are essential for ensuring the reliability and efficiency of complex systems. Manually validating electric vehicle supply equipment (EVSE), e.g. AC wallbox, is time-consuming and costly. This research focuses on designing and developing an automated test setup for AC Wallbox chargers, with a specific emphasis on RFID-based authentication. Among the various validation interfaces available, RFID has been chosen due to its widespread use in EVSE authentication and billing. This study explores how to automate RFID testing, e.g. authentication mechanisms, and state transitions within EV charging systems with RFID authentication. By emulating RFID tag behavior and analyzing system responses, the research aims to exploit test automation while identifying potential weaknesses in authentication workflows. Problem. RFID authentication is a widely adopted solution in EV charging stations for enabling user identification and billing. However, its implementation varies across different Wallbox models, leading to challenges in ensuring standardization. Traditional testing methods rely on physical RFID tags and manual validation, making them inefficient, time wasting and difficult to reproduce. Additionally, unexpected state transitions in authentication workflows can lead to operational inconsistencies. This research aims to develop an automated framework that accurately emulates RFID tags, providing a repeatable, scalable, and efficient solution for testing Wallbox chargers. Methods. The study begins with an analysis of AC Wallbox products and key test specifications. A market survey is conducted to assess existing test automation tools, identifying limitations that lead to a custom approach. The test setup is then developed using a combination of hardware and software components. The methodology involves RFID tag emulation to perform controlled testing of authentication protocols under various conditions. This includes simulating different RFID tags, testing multiple authentication attempts and observing Wallbox responses. Additionally, automated logging and analysis tools are integrated to ensure systematic validation. The firmware is then put under extensive testing to confirm its reliability in replicating real-world authentication interactions. Results. The developed test setup successfully automates RFID authentication testing across multiple AC Wallbox models. The RFID emulation proves highly effective in reproducing real-world authentication scenarios, allowing for a detailed analysis of system responses. Differences has been found in how wallboxes process authentication requests, with some models exhibiting unexpected state transitions when subjected to rapid authentication attempts. Additionally, minor inconsistencies has been identified in certain implementations, highlighting areas for potential firmware improvements. Conclusion. This research demonstrates the benefits of an automated RFID authentication test setup for AC Wallbox chargers. By replacing manual validation with controlled emulation, the framework enables faster and more consistent testing. Future work could explore the integration of AI-based algorithms to further refine test automation or enhance the firmware to simulate a wider range of authentication scenarios within a single file.