A method and system for estimating vehicle cornering stiffness and moment of inertia
By using Kalman filter fusion technology to calculate the fused values of vehicle lateral stiffness and rotational inertia under different driving scenarios, the problem of vehicle instability in autonomous driving is solved, and higher driving stability and lateral control precision are achieved.
CN116394956BActive Publication Date: 2026-07-03ZHEJIANG SMART INTELLIGENCE TECH CO LTD +1
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ZHEJIANG SMART INTELLIGENCE TECH CO LTD
- Filing Date
- 2023-04-24
- Publication Date
- 2026-07-03
AI Technical Summary
Technical Problem
In existing technologies, the large fluctuations in vehicle lateral stiffness and rotational inertia lead to instability in autonomous driving.
Method used
Kalman filtering fusion technology is adopted to select appropriate filtering windows and parameters under different driving scenarios. The fused values of vehicle lateral stiffness and rotational inertia are calculated through state-space equations and output to the dynamic model.
Benefits of technology
It improves the stability of autonomous driving in different driving scenarios, reduces data fluctuations in lateral stiffness and rotational inertia, and enhances the accuracy of lateral control.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN116394956B_ABST
Abstract
The application provides a vehicle side stiffness and moment of inertia estimation method and estimation system, and belongs to the field of automatic driving. The method comprises the following steps: acquiring the current vehicle speed of the ego vehicle, the road curvature of the road where the ego vehicle is located, the tire deflection stiffness, the moment of inertia estimation value, the front and rear axle equivalent side stiffness and the moment of inertia reference value; when the current vehicle speed is greater than the first preset vehicle speed and the road curvature of the road is greater than the preset curvature, the first fusion value of the tire deflection stiffness and the front and rear axle equivalent side stiffness after Kalman filtering fusion, and the second fusion value of the moment of inertia estimation value and the moment of inertia reference value after Kalman filtering fusion are output to the power model of the ego vehicle. The application solves the problem that the deflection stiffness and the moment of inertia fluctuate greatly in the prior art, and the automatic driving of the vehicle is unstable.
Need to check novelty before this filing date? Find Prior Art