# Integration of EMU Overall Design Model Based on Ontology-Knowledge Collaboration
## 2 Integrated Design Model for EMU  
The traditional overall design process of an EMU is often based on Traditional Systems Engineering, facing issues such as poor model readability, low reusability, and inconsistent data sources. Therefore, this paper introduces the modeling approach of MBSE into the overall design process of an EMU, employing a top-down forward design approach for EMUs and driving MBSE modeling through ontology and KG technologies. The MBSE-based overall design process of an EMU includes processes for requirements, functions, physical architecture, and traceability. Due to the involvement of multiple domains in the vehicle design process, there are semantic heterogeneities in each domain, leading to problems such as different data sources, low semantic integration efficiency, and semantic inconsistency. To address these issues, this paper proposes a bidirectional ontology-knowledge collaborative-driven integrated design model. In this method, the functions and physical architecture in the entire vehicle design process are collectively referred to as architecture, and the bidirectional ontology-knowledge drive is applied in requirements, architecture, and traceability. The technical route is shown in Figure 1. The MBSE model serves as input, dividing the entire EMU overall design into three parts: requirements, architecture, and traceability. Requirements are divided into the following three stages: requirement collection, requirement identification, and requirement analysis. During requirement identification, collected requirements are structured using the top-level ontology, and during requirement analysis, they are presented through the KG. In the architecture analysis process, the functional meta-model and physical architecture meta-model are constructed using the top-level ontology. Finally, in the traceability part, requirements and architecture are traced to ensure that the EMU design meets the requirements. Ontology and KG methods play vital roles in achieving semantic integration, effectively addressing the issue of semantic heterogeneity in systems engineering. Ontology offers a structured, formalized description that standardizes conceptual knowledge, facilitating better organization and representation of data. In this study, we opted to employ Basic Formal Ontology (BFO) [37] to construct the ontology framework. BFO, serving as a fundamental formal ontology, enables the description of concepts and relationships across various domains, offering high generality and flexibility suitable for modeling requirements in diverse fields. On the other hand, KG technology serves as a methodological toolset for representing, organizing, and managing knowledge. It organizes accumulated information into usable knowledge at minimal cost and enables precise data linkage for knowledge searches. This paper realizes the overall design of an EMU through bidirectional coordination of ontology and KG-driven model integration. Initially, we construct the ontology framework using a top-down approach to ensure project-wide consistency and integrity, thereby reducing omissions or errors in subsequent development phases. Subsequently, the KG fills  
Figure 1: Technological Roadmap. in the analysis and confirmation of requirements from the bottom-up, starting with detailed aspects and instances and gradually establishing an understanding and confirmation of requirements. In the overall design process of an EMU, the KG is leveraged to collect and organize various domain knowledge and corresponding requirements, leading to a deeper comprehension of the essence and specifics of requirements. Through continuous filling and refining of the KG, the team can progressively distill accurate requirement specifications, ensuring their alignment with real-world business scenarios.