一种基于简化车辆动力学模型的扭矩矢量预测方法
By simplifying the vehicle dynamics model and real-time data processing, the adaptability problem of the torque vector algorithm under different operating conditions was solved, achieving more stable and efficient torque vector control, and enhancing the performance of vehicle dynamic limits and passive driving assistance systems.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHENGDU PUWEI ELECTRONIC TECHNOLOGY CO LTD
- Filing Date
- 2025-03-12
- Publication Date
- 2026-07-17
AI Technical Summary
Existing torque vectoring algorithms exhibit open-loop control characteristics in vehicle dynamics control, making them unable to adapt to different operating conditions. This results in a narrow window for passive driving assistance systems, and the large AI model algorithms are resource-intensive and unstable, making it difficult to provide reliable torque vectoring control under complex driving conditions.
A torque vector prediction method based on a simplified vehicle dynamics model is adopted. By acquiring real-time vehicle data, a simplified dynamics model is constructed. Combined with suspension sensor and wheel speed data, the vehicle path is estimated. Combined with the driver's input prediction vector, the torque vector output is calculated, thereby enhancing the vehicle's dynamic adaptability and the functions of the passive driving assistance system.
It improves the vehicle's dynamic limits under a wide range of operating conditions, enhances the capabilities of passive driving assistance systems, reduces tuning costs, improves safety and controllability, adapts to different vehicle structures and external conditions, and reduces the resource consumption of large AI models.
Smart Images
Figure CN120396977B_ABST