Real-time CAN Data Acquisition and Visualization: Synerging Physical-to-Virtual (P2V) Twinning of Automotive Battery Management Systems

Controller area network (CAN) is widely used in automotive applications and has become the standard communication protocol to enable efficient communication primarily between electronic control units (ECUs) to reduce the complexity and cost of electrical wiring in automobiles through multiplexing. Towards developing the cloud-based electric vehicle battery data monitoring and digital-twinning of a battery management system (BMS), this paper introduced an online CAN data acquisition and visualization technique from an automotive grade BMS of NXP®<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup>. Python-based CAN data processing tool is developed to process the raw data from the NXP® BMS and an open-source platform Grafana<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> is utilized together with the InfluxDB for visualization of the time-series data in real-time from a battery module containing 14 SAMSUNG 21700 lithium-ion battery cells. Each of those elements is implemented through the Docker container platform to become a standardized unit called a container. Besides presenting the detailed architecture of the data acquisition and visualization platform and the python-based data processing tool, this paper demonstrated the capability of the proposed architecture through examples of visualizing individual cell voltage, current, and temperature in real-time and their applications and utility in implementing cloud-based BMS.