一种电动汽车行驶时的平坦路面快速识别方法
By establishing a longitudinal dynamics model of the vehicle in an electric vehicle and using an unscented Kalman filter algorithm, combined with chassis CAN network signals to identify flat road surfaces, the problems of inaccurate identification and high cost in existing technologies are solved, and fast and accurate flat road surface identification and braking force distribution control are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING INST OF TECH
- Filing Date
- 2023-11-28
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies struggle to accurately identify flat road surfaces when electric vehicles are in motion, leading to reduced control efficiency of the brake force distribution system and increased equipment costs due to reliance on additional sensors.
Based on the vehicle's longitudinal dynamics model, the road gradient and vehicle mass are estimated by combining the unscented Kalman filter algorithm with the vehicle chassis CAN network signals (drive motor output torque, brake master cylinder pressure, and non-drive wheel speeds). Flat road surfaces are then identified using a dual unscented Kalman filter algorithm.
It enables rapid and accurate identification of flat road surfaces, reduces reliance on additional sensors, improves the control efficiency of the brake force distribution system, and reduces costs.
Smart Images
Figure CN117601872B_ABST