# Integration of EMU Overall Design Model Based on Ontology-Knowledge Collaboration
###### Abstract  
The whole train design of an Electric Multiple Unit (EMU) involves multiple domains and scenarios, thus requiring comprehensive consideration of various factors during the design process. Traditional design methods often utilize text-based approaches to model systems; however, such documentation-based designs often suffer from semantic heterogeneity, inconsistent data sources, and also struggle to provide a more intuitive overview of the overall design process. To address these issues, this paper proposes a method based on ontology-knowledge collaborative drive to achieve integration of the overall EMU design. Firstly, we employ the System Modeling Language (SysML) to construct the Model-Based Systems Engineering (MBSE) model of the EMU, establishing functional and physical architecture element models, with the EMU MBSE model serving as input. Subsequently, in the requirement model, architecture model, and traceability model, we utilize top-level ontology to construct the EMU ontology framework in a top-down manner. Lastly, leveraging the Neo4j database, we employ a knowledge graph (KG) approach to fill domain knowledge into each model in a bottom-up manner, thereby realizing the ontology-knowledge collaborative drive for the overall EMU design construction. The effectiveness of the proposed method is validated using the EMU Passenger Information System (PIS) and Traction transformer System (TS) as examples. EMU overall design; model-based systems engineering; meta-model; ontology; knowledge graph +
Footnote †: journal: Medicalas inconsistent requirements analysis in manned spaceflight engineering [6], unresponsive aircraft management systems [7], and difficulty in test verification [8]. In the aviation field, MBSE has addressed challenges in civil aircraft forward design, including the high coupling of modeled objects [9], the low maturity of model traceability and reusability [10], the low maturity of aircraft intelligent fault prediction technology [11], and the insufficient decision-making capability in flight and ground support processes [12]. In the shipbuilding field, MBSE has addressed difficulties in verification and iteration in the overall design of power engineering [13], lack of experience in ship type and hydrodynamic performance design, and low knowledge conversion rates [14]. In the medical field, MBSE has addressed issues such as unbalanced deployment of emergency medical equipment [15] and complexity in hospital department management processes [16]. From the current research results, MBSE has shown advantages in improving design quality, increasing production efficiency, reducing development risks, enhancing team communication, and strengthening knowledge transfer [17]. As a complex piece of equipment, an EMU design features system complexity, long R&D cycles, significant manpower, capital investment, and strict requirements for safety and reliability, thus necessitating the use of system engineering methods [18]. In the MBSE-based design process of the EMU, the association between models ensures the traceability of information throughout the entire design process and helps designers optimize the iterative process of existing designs. In the design of key systems of an EMU, some scholars have conducted preliminary explorations utilizing MBSE. [PERSON] et al. [2; 5; 17; 19] used the MBSE concept to model, simulate, and verify the pantograph of an EMU, proposing a modeling method for requirement modeling and the Operational-Functional-Architecture-Physical (OFAP) modeling method applicable to the entire vehicle logic. In addition, MBSE-based design approaches have been applied to the door systems [18] and traction systems [20] of an EMU. [PERSON], [PERSON] et al. [19] built a domain meta-model for the high-voltage system of an EMU, improving the efficiency of the design. The construction of the overall EMU model based on the MBSE concept involves using the M-Design modeling tool and the SysML modeling language to perform MBSE modeling of requirements, architectures, and traceability.