Application of Munich Agile Concept for MBSE for a Holistic Approach To Collect Vehicle Data Based on Board Diagnostic System
Vahid Salehi
Abstract
Abstract This paper is based on four different steps. In the first step, a literature review is provided on the topic of the application of on-board diagnostic systems and their connection to digital twins in a virtual environment. In the second step, some important research questions are addressed, which are dealt with in the following sections. Based on the research questions, this paper applies a systematic method to use generated data such as GPS position, gasoline engine parameters such as speed/revs, and the vehicle’s gasoline battery to enrich a digital data environment for virtualization and simulation. This technical paper explores the use of On-Board Diagnostic II (OBD-II) interfaces to collect data from gasoline vehicles and the subsequent analysis of this data using systems engineering methods. The paper will present the results of gasoline vehicle testing based on OBD-II data and Model Based Systems Engineering (MBSE) using the Munich Agile Concept for Systems Engineering (MAGIC) to design a system-of-systems approach based on Digital Twin Data. This paper and the corresponding research project will develop a consistent, traceable, holistic system-of-systems engineering approach for digital twins. MBSE is based on three important core pillars: 1) Methods/Processes, 2) Language and 3) Systems. The purpose of the newly developed Munich Agile Concept Approach is to manage complexity throughout the data collection, data processing and data virtualization process from a real environment to a virtual Digital Twin environment. The Munich Agile Concept contains six different levels: System Requirement, System Function, System Architecture, System Validation, System Test and System Usage Level. A graphical language called System Modeling Language (SysML) was used to define the first three levels. In the final step, this paper will report on the experiences made and the results of the applied MAGIC approach in Model Based Systems Engineering.