Torque Steer Mitigation via Learned Pinion Torque Estimation
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Solution Overview
Problem
In front wheel drive vehicles, driveline geometry imbalances cause torque steer, leading to directional changes during hard acceleration, which existing technologies struggle to consistently mitigate, especially in quasi-steady state conditions.
Innovation Solution
A system comprising a base gain generation module, a learning module, and a command generation module that generate motor torque commands based on transmission and estimated pinion torque to counteract torque steer forces, utilizing sensors and algorithms to adjust motor torque accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional torque sensors are installed to accurately measure pinion torque for torque steer mitigation, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent introduces a learning module as an intermediary that estimates pinion torque by establishing a linear relationship with transmission torque. Instead of directly measuring pinion torque with additional sensors, the system uses the learning module to infer pinion torque values based on the relationship: pinion torque = transmission torque × learned gain. This mediator approach achieves accurate torque estimation without adding physical sensors.
Solution Approach 2:
The patent replaces the mechanical sensing approach (additional torque sensors) with a computational approach (learning module with linear relationship). The learning module uses algorithms to establish and apply the linear relationship between transmission torque and pinion torque, substituting physical measurement devices with mathematical modeling and computation.
2Device complexity
If a simple base gain approach is used for torque steer mitigation, then device complexity is reduced, but mitigation effectiveness especially in quasi-steady state conditions deteriorates
Solution Approach 1:
The patent transforms the static base gain approach into a dynamic adaptive system by introducing a learning module that continuously updates the learned gain based on operating conditions. The system adapts the torque relationship in real-time, allowing effective mitigation across varying driving conditions including quasi-steady state conditions where transient approaches fail.
Solution Approach 2:
The learning module performs preliminary learning during normal operation to establish the linear relationship between transmission torque and pinion torque. This preliminary action of learning and storing the gain relationship enables accurate torque steer mitigation to occur automatically during subsequent operation without requiring complex real-time calculations.
Data Source
AI summary
A system for mitigation of a torque steer includes a base gain generation module that generates a base gain based on a transmission torque, a learning module that generates a learned gain based on the transmission torque and the estimated pinion torque, and a command generation module that generates a motor torque command from the learned gain, the transmission torque, and the base gain.