Quadrant-Based Friction Compensation for Tire Load Estimation
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Solution Overview
Problem
Existing steering systems face challenges in accurately estimating tire load, particularly due to differences in forward and backward efficiencies of gear pairs, leading to mismatches in tire load estimates during motor reversals, which affects vehicle dynamics control and road surface friction estimation.
Innovation Solution
A control system for a steering system that includes a method to estimate tire load by computing an efficiency factor based on input torque and motor velocity, adjusting the input torque, and using a state observer with a quadrant-based friction efficiency module to account for asymmetric efficiency losses, replacing traditional LuGre friction models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional LuGre friction models are used in steering systems, then the system structure remains simple, but tire load estimation accuracy deteriorates during motor reversals due to asymmetric efficiency losses
Solution Approach 1:
The friction model is segmented into four quadrants based on motor velocity and torque directions. Each quadrant has its own efficiency factor calculation, allowing asymmetric efficiency losses to be captured without requiring a completely complex new model structure. This segmentation enables accurate tire load estimation during motor reversals while maintaining reasonable model complexity.
Solution Approach 2:
Different efficiency factors are applied locally to each quadrant of operation. The efficiency factor is not uniform across all operating conditions but is specifically tailored to each quadrant's characteristics. This local quality approach improves measurement precision for tire load estimation in reversal scenarios while keeping the overall system manageable.
2Stability of the object's composition
If asymmetric efficiency factors are computed for each quadrant, then tire load prediction consistency improves, but computational requirements increase
Solution Approach 1:
The efficiency factor is computed as a parameter that changes based on the operating quadrant (determined by signs of motor velocity and torque). By changing the efficiency parameter according to quadrant, the system achieves consistent tire load predictions across different operating conditions including reversals, while the computation remains relatively simple compared to full dynamic friction modeling.
3Measurement precision
If input torque is adjusted by scaling with efficiency factor, then the accuracy of state observer input improves, but the processing steps increase
Solution Approach 1:
The efficiency factor computation and torque scaling is performed as a preliminary action before feeding the adjusted torque to the state observer. This preliminary adjustment of the input torque using the quadrant-based efficiency factor improves the accuracy of the state observer's tire load estimation, while the additional processing step is minimal compared to the overall control system complexity.
Data Source
AI summary
According to one or more embodiments a control system for a steering system, includes a control module that estimates a tire load by performing a method that includes receiving, as an input torque, motor-torque that is generated by a motor of the steering system. The method further includes computing an efficiency factor for a gear of the steering system based on the input torque and a motor velocity. The method further includes adjusting the input torque by scaling the input torque with the efficiency factor. The method further includes estimating the tire load using the adjusted input torque as an input to a state observer for the steering system.