The Trilab studied digital twins through a project on the digital twin of an electric vehicle charging station, focussing on its communications.
What is a digital twin
Digital twins lack centralized implementation standards and are often defined in many different ways. Though, a widely accepted definition of a digital twin is provided by IBM: “a virtual representation of an object or system that spans its lifecycle, is updated from real-time data, and uses simulation, machine learning and reasoning to help decision-making.” In other words, a digital twin is a virtual version of a physical entity that conducts bidirectional communication with the real-world counterpart, and can simulate the entire lifecycle of this counterpart. This bidirectional communication and involvement within the entire lifecycle is what differs digital twins from other simulation models as digital twins are capable of self-evolving alongside the physical entity. The extent or limits associated with the use cases of digital twins remain unclear, but typically digital twins are used for running predictive behavior simulations or data visualizations for system monitoring.
Components of a Digital Twin
There are three main components without which a digital twin could not exist:
- The physical asset (physical component)
- The digital asset (virtual component)
- Two-way synchronized information flow between the physical and digital assets
Furthermore, the following components could be considered as imperative components which simply add properties to the digital twin:
- IoT devices
- Integrated Time continuous data
- Machine Learning
- Evaluation metrics / Testing
We use Troca to obtain data on the charging stations, with which we can build a profile containing its configuration of the station. This profile is used to create a “Thing” in Ditto with the same OCPP configuration, which is then used by OCPPvs to simulate a charging station with the same parameters as the physical twin.
Learn more about our demo [here].