Vehicle Path Tracking Control with Yaw Moment Stability Feedback
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Solution Overview
Problem
Intelligent electric vehicles face stability issues during path tracking, particularly in emergency obstacle-avoiding situations, leading to potential accidents due to violent lateral movements and deviations from the expected trajectory.
Innovation Solution
A path tracking control method that determines the lateral stability state of the vehicle and adjusts front wheel steering and yaw moment increments based on stability states, using objective functions and reinforcement learning algorithms to maintain stability and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If path tracking control is performed with high speed and large steering angle during emergency obstacle avoidance, then the vehicle can quickly avoid obstacles, but the lateral movement becomes violent causing vehicle destabilization
Solution Approach 1:
The control method dynamically adjusts the additional yaw moment based on real-time vehicle stability states (stable, critical-destabilized, destabilized). When the vehicle enters a critical or destabilized state during emergency avoidance, the system automatically modifies the yaw moment to counteract violent lateral movements, thereby maintaining stability while allowing high-speed operation
Solution Approach 2:
The system continuously monitors vehicle stability states through sensors and feedback loops. Based on the detected stability state, the control method adjusts the additional yaw moment in real-time, creating a closed-loop control system that prevents destabilization during high-speed emergency maneuvers
2Stability of the object's composition
If additional yaw moment control is applied to maintain vehicle stability, then vehicle destabilization is prevented, but path tracking accuracy deteriorates due to violent swing movements
Solution Approach 1:
The control method dynamically adjusts the additional yaw moment based on real-time vehicle stability states (stable, critical-destabilized, destabilized). When the vehicle enters a critical or destabilized state during emergency avoidance, the system automatically modifies the yaw moment to counteract violent lateral movements, thereby maintaining stability while allowing high-speed operation
Solution Approach 2:
The system continuously monitors vehicle stability states through sensors and feedback loops. Based on the detected stability state, the control method adjusts the additional yaw moment in real-time, creating a closed-loop control system that prevents destabilization during high-speed emergency maneuvers
3Manufacturing precision
If front wheel steering control is used for path tracking, then trajectory following is achieved, but vehicle stability is compromised during emergency obstacle-avoiding states
Solution Approach 1:
The control method merges path tracking control with stability control by introducing an additional yaw moment controller that works in conjunction with the front wheel steering system. This combined control approach ensures that path tracking accuracy is maintained while vehicle stability is preserved during emergency maneuvers
Solution Approach 2:
The control method dynamically adjusts the additional yaw moment based on real-time vehicle stability states (stable, critical-destabilized, destabilized). When the vehicle enters a critical or destabilized state during emergency avoidance, the system automatically modifies the yaw moment to counteract violent lateral movements, thereby maintaining stability while allowing high-speed operation
Data Source
AI summary
A path tracking control method for an intelligent electric vehicle. The method includes the following steps. A lateral stability state of a vehicle is determined, where the lateral stability state includes a stable state, a critical-destabilized state, and a destabilized state. Path tracking control is performed on the vehicle according to the lateral stability state of the vehicle. This application also provides a path tracking control device for an intelligent electric vehicle, which includes a lateral stability state determination module and a path tracking control module.

