CarTwin—Development of a Digital Twin for a Real-World In-Vehicle CAN Network

Abstract

Digital twins are used to replicate the behavior of physical systems, and in-vehicle networks can greatly benefit from this technology. This is mainly because in-vehicle networks circulate large amounts of data coming from various sources such as wired, or in some cases even wireless, sensors that are fused by actuators responsible for safety-critical tasks that require careful testing. In this work, we build a laboratory in-vehicle network that mimics a real vehicle network in regards to wire length, number of stubs and devices that are connected to it. The Controller Area Network (CAN), which is still the most popular communication bus inside cars, is used as a network layer. Using models defined in MATLAB for various subsystems, e.g., Anti-lock Braking System (ABS), Powertrain and Electric Power-Steering, deployed on automotive-grade microcontrollers, we evaluate the in-vehicle bus digital twin by providing realistic inputs and recording and reproducing in-vehicle network traffic. The experimental results showed good correlation between the output of the implemented digital twin and the data collected from an actual car.