Robotic Digital Twin Modeling Method Integrating MBSE and Modelica

Authors

• Zaiwu Mei, School of Mechanical & Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, China; Hubei Research Center of Intelligent Welding Equipment and Software Engineering Technology, Wuhan 430205, China
• Jiangman Zhou, Wuhan Fenghuo Fuhua Electric Co., Ltd, Wuhan 430205, China
• Cong Zhang, School of Mechanical & Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, China; Hubei Research Center of Intelligent Welding Equipment and Software Engineering Technology, Wuhan 430205, China
• Yiping Gao, State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Wuhan 430074, China
• Zerun Zhu, School of Mechanical & Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, China; Hubei Research Center of Intelligent Welding Equipment and Software Engineering Technology, Wuhan 430205, China

Abstract

Abstract: To address the issues of disconnection between system architecture design and dynamic simulation, as well as the limited reusability and scalability of models in robotic digital twin modeling, a modular modeling approach integrating MBSE (model-based systems engineering) and Modelica is proposed. The method employs MBSE for system architecture design and requirement traceability, and combines Modelica for multi-domain dynamic simulation, forming a full-chain digital twin model from system design to physical behavior simulation. Standardized interfaces and a generic component model library are developed to decouple and integrate mechanical, electrical, and control subsystems, enabling rapid model assembly and functional expansion. A six-degree-of-freedom industrial robot is used as a case study for digital twin modeling and simulation verification. The simulation results show good consistency with experimental data, demonstrating the high fidelity of the proposed approach. This study (23QD46) provides an effective solution for standardized construction of robotic digital twins, significantly improving model development efficiency, maintainability, and scalability, and offering valuable reference for the application of digital twin technology in robotics.

Recommended Citation

Mei, Zaiwu; Zhou, Jiangman; Zhang, Cong; Gao, Yiping; and Zhu, Zerun (2026) "Robotic Digital Twin Modeling Method Integrating MBSE and Modelica," Journal of System Simulation: Vol. 38: Iss. 9, Article 20.
DOI: 10.16182/j.issn1004731x.joss.25-1081
Available at: https://dc-china-simulation.researchcommons.org/journal/vol38/iss9/20

First Page

2725

Last Page

2738

CLC

TP391

Recommended Citation

Mei Zaiwu, Zhou Jiangman, Zhang Cong, et al. Robotic Digital Twin Modeling Method Integrating MBSE and Modelica[J]. Journal of System Simulation, 2026, 38(9): 2725-2738.

Corresponding Author

Zhang Cong

DOI

10.16182/j.issn1004731x.joss.25-1081