Abstract: ［Objective］ With the maturity of permanent magnet synchronous motor design and control technologies, PMTS (permanent magnet traction systems) have emerged as the developmental direction for next-generation rail transit traction systems. By leveraging digital twin technology, it is possible to enhance the reliability and intelligence of PMTS in urban rail transit trains. This requires targeting the realization of system digital design, state perception, fault inversion, health management, and performance prediction while exploring the key technologies for constructing a PMTS digital twin platform. ［Method］ First, a review of PMTS characteristics and current applications and digital twin technology is conducted. Then, considering the features of urban rail transit train traction system such as high-speed mobility, multi-physical field coupling, multi-time-scale interactions, and rich dynamic characteristics, a multi-time-scale digital twin architecture based on hybrid drive of model and data is proposed. Feasible technical solutions for achieving system integration and matching optimization design, improving the control performance of permanent magnet motors, and implementing system fault warning and inversion through digital twin technology are discussed. ［Result & Conclusion］ Digital twin technology can enhance reliability and safety of PMTS, optimize intelligent system perception, and provide strong technical support for system performance prediction, health management, and intelligent vehicle operation and maintenance. However, practical application of high-reliability urban rail transit PMTS based on digital twins still faces technical challenges such as physical field modeling and vehicle-wayside information interaction.