Torque Vectoring Selection for Vehicle Yaw Moment Path Tracking
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Solution Overview
Problem
Current advanced driving assist systems (ADAS) face challenges in effectively implementing path tracking control for self-driving vehicles, particularly in achieving desired yaw moments for lateral movement using torque vectoring techniques, which is crucial for lane centering, lane keeping, and evasive steering.
Innovation Solution
The method involves determining a desired yaw moment and identifying achievable yaw moment changes using different torque vectoring techniques, selecting the appropriate technique, and applying it to create lateral movement in the ego vehicle, leveraging processing devices and machine-readable instructions to execute the necessary algorithms for torque distribution across vehicle wheels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple torque vectoring techniques are evaluated and selected based on achievable yaw moment changes, then the precision of path tracking control is improved, but the computational complexity and control system complexity increase
Solution Approach 1:
The control system dynamically selects from multiple torque vectoring techniques based on current driving conditions and desired yaw moment requirements. The system evaluates achievable yaw moment changes for different techniques and adapts the selection in real-time, making the control approach flexible and condition-dependent rather than fixed
Solution Approach 2:
The yaw moment control is divided into multiple discrete torque vectoring techniques, each with specific achievable yaw moment characteristics. The control system segments the overall control task into evaluating and selecting from these distinct techniques based on current needs, allowing precise matching of control method to situation
2Ease of operation
If torque vectoring techniques are used to achieve desired yaw moments for lateral movement, then the vehicle's lateral control capability is improved, but the energy consumption increases
Solution Approach 1:
The system changes the control parameters by selecting different torque vectoring techniques based on the desired yaw moment and current vehicle state. By adjusting which technique is applied and at what torque level, the system optimizes the balance between lateral control performance and energy consumption
Solution Approach 2:
The control system applies torque vectoring selectively based on the achievable yaw moment changes and current control needs. Rather than continuously applying maximum torque, the system uses partial action by selecting techniques that provide sufficient yaw moment for the specific lateral control task at hand, reducing unnecessary energy consumption
Data Source
AI summary
A method includes determining a desired yaw moment to be applied to an ego vehicle during travel. The method also includes identifying yaw moment changes that are achievable using different torque vectoring techniques supported by the ego vehicle. The method further includes selecting at least one of the torque vectoring techniques based on the identified yaw moment changes. In addition, the method includes using the at least one selected torque vectoring technique to obtain the desired yaw moment and create lateral movement of the ego vehicle during the travel. In some cases, a desired response time associated with the lateral movement of the ego vehicle may be used, where steering control provides a faster response time and torque vectoring control provides a slower response time. The at least one torque vectoring technique may be selected based on different energy efficiencies associated with different ones of the torque vectoring techniques.