Lane Centering State Estimation with Real-Time Tire Stiffness Updates
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Solution Overview
Problem
Existing vehicle lane centering algorithms are affected by changes in tire cornering stiffness and vehicle moment of inertia due to factors like tire pressure, aging, and load variations, leading to degradation in performance.
Innovation Solution
A vehicle system that includes an inertial navigation system module to detect yaw rates and lateral speeds, and a controller circuit that determines tire cornering stiffness and vehicle moment of inertia in real-time using vehicle physical and dynamic parameters, updating these values periodically with data from sensors such as speed, steering angle, and yaw rate sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional fixed parameter lane centering algorithms are used, then the algorithm structure is simple, but the performance degrades due to changes in tire cornering stiffness and vehicle moment of inertia
Solution Approach 1:
The patent applies the Dynamics principle by transitioning from fixed parameter algorithms to real-time dynamic parameter estimation. The system continuously updates tire cornering stiffness (Cf, Cr) and vehicle moment of inertia (Iz) based on actual vehicle operating conditions, allowing the lane centering algorithm to adapt to changing vehicle states such as tire pressure variations, aging, and load changes, thereby maintaining reliable performance without excessive complexity
Solution Approach 2:
The patent implements Feedback by using vehicle dynamic parameters (lateral acceleration, yaw rate, steering angle, longitudinal speed) to continuously estimate and update tire cornering stiffness and vehicle moment of inertia. This closed-loop feedback mechanism allows the system to self-adjust parameters based on actual vehicle behavior, improving lane centering reliability while keeping the algorithm structure manageable through systematic parameter updating
2Measurement precision
If real-time parameter updates are performed frequently, then the accuracy of vehicle dynamic parameters is improved, but the computational load and processing time increase
Solution Approach 1:
The patent applies Periodic action by updating vehicle dynamic parameters at regular sampling intervals (Ts) of less than 0.01 seconds. This periodic updating strategy balances measurement precision with processing efficiency, allowing the system to capture real-time vehicle state changes without excessive computational burden, as parameters are updated systematically at predetermined time intervals rather than continuously
Solution Approach 2:
The patent implements Partial action by storing and utilizing arrays of at least 200 samples for each dynamic parameter before performing updates. This approach allows the system to accumulate sufficient data for accurate parameter estimation while avoiding the need to process every single data point in real-time, thereby achieving good measurement precision without excessive processing time requirements
Data Source
AI summary
A system includes an inertial navigation system module (INS module) that detects vehicle yaw rates and vehicle lateral speeds, a controller circuit communicatively coupled with the INS module. The controller circuit determines a tire cornering stiffness (Cf, Cr) based on vehicle physical parameters and vehicle dynamic parameters. The controller circuit determines a vehicle moment of inertia (Iz) based on the vehicle physical parameters, the vehicle dynamic parameters, and the tire cornering stiffness (Cf, Cr).