基于类脑结构分区的车辆平稳性数字孪生构建方法及装置
By constructing a digital twin model of rail transit vehicles according to brain-like structural partitions, the problems of weak expression of functional partition coupling relationship and failure to incorporate wet and slippery environmental factors in existing technologies are solved. This enables unified evaluation of vehicle stability and closed-loop feedback adjustment, thereby improving vehicle operation stability and control effect.
Patent Information
- Application Number
- CN202610886137.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-18
- Publication Date
- 2026-07-17
AI Technical Summary
Existing vehicle digital twin models have limited ability to express the coupling relationship of functional zones, do not incorporate wheel-rail slippery environment factors into structural-level modeling, lack a top-level unified evaluation of stability performance, and lack structural-level closed-loop feedback regulation.
The physical system of rail transit vehicles is abstracted into the category of physical system. A digital twin category is constructed according to the brain-like structure partitioning. A mapping between the two categories is established through the structure-preserving functor. A comprehensive evaluation object for limit stability is constructed and closed-loop feedback regulation is carried out.
It achieves a unified evaluation of vehicle stability under combined operating conditions, enhances operational stability and control robustness, supports dynamic structural updates, and improves the matching degree and control effect of the digital twin model.
Smart Images
Figure CN122413587A_ABST