Li-ion battery packs are the heart of modern electric vehicles. Due to their perishable nature, it is crucial to supervise them closely. In addition to on-board supervision over safety and range, insights into the battery’s degradation are also becoming increasingly important, not only for the vehicle manufacturers but also for vehicle users. The concept of digital twins has already emerged on the field of automotive technology, and can also help to digitalize the vehicle’s battery. In this work, we set up a data pipeline and digital battery twin to track the battery state, including State of charge (SOC) and State of Health (SOH). To achieve this goal, we reverse-engineer the diagnostics interface of a 2014 e-Golf to query for UDS messages containing both battery pack and cell-individual data. An OBD logger records the data with edge-processing capability. Pushing this data into the cloud twin system using IoT-technology, we can fit battery models to the data and infer for example, cell individual internal resistance from them. We find that the resistances of the cells differ by a magnitude of two. Furthermore, we propose an architecture for the battery twin in which the twin fleet shares resources like models by encapsulating them in Docker containers run on a cloud stack. By using web technology, we present the analyzed results on a web interface.

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Public transportation (PT) systems suffer from disutility compared to private transportation due to the inability to provide passengers with a door-to-door service, referred to as the first/last mile problem. Personal mobility devices (PMDs) are thought to improve PT service quality by closing this first/last mile gap. However, current PMDs are generally driven manually by the rider and require a learning phase for safe vehicle operation. Additionally, most PMDs require a standing riding position and are not easily accessible to elderly people or persons with disabilities. In this paper, the concept of an autonomously operating mobility device is introduced. The visionary concept is designed as an on-demand transportation service which transports people for short to medium distances and increases the accessibility to public transport. The device is envisioned to be operated as a larger fleet and does not belong to an individual person. The vehicle features an electric powertrain and a one-axle self-balancing design with a small footprint. It provides one seat for a passenger and a tilt mechanism that is designed to improve the ride comfort and safety at horizontal curves. An affordable 3D-camera system is used for autonomous localization and navigation. For the evaluation and demonstration of the concept, a functional prototype is implemented.

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