Steering Driver Torque Estimation With a Minimal Linear Observer
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing driver torque estimation methods in steering systems are complex, require extensive tuning, and are limited to torque sensor-based columns, making them unsuitable for various steering configurations and susceptible to failure.
Innovation Solution
A minimally realizable linear state observer with intuitive gain tuning strategies is employed for driver torque estimation, applicable to different steering configurations, including sensor-based and sensorless designs, using a simplified observer architecture and feedback mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex driver torque estimation methods are used, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential elements needed for torque estimation by using a linear state observer that relies solely on handwheel position measurements. This minimalistic approach eliminates the need for complex sensor arrays or multiple measurement points, achieving reliable torque estimation with the simplest possible system configuration.
Solution Approach 2:
The patent replaces complex mechanical torque sensing systems with a mathematical estimation approach using linear state observers. By substituting physical torque sensors and complex mechanical measurement systems with algorithm-based estimation using readily available position data, the system achieves accurate torque measurement without mechanical complexity.
2Measurement precision
If extensive tuning is performed, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The linear state observer is designed to be self-tuning by automatically adapting to system characteristics through its mathematical structure. The observer gains are determined by system parameters rather than requiring manual adjustment, allowing the system to maintain accurate torque estimation without operator intervention for tuning.
Solution Approach 2:
The patent uses parameter-based tuning where the observer characteristics are defined by mathematical parameters that can be set based on known system properties. This approach replaces iterative manual tuning with direct parameter specification, making the system easier to operate while maintaining precision.
3Measurement precision
If torque sensor-based methods are used, then measurement precision is improved, but adaptability deteriorates
Solution Approach 1:
The linear state observer is designed as a universal solution that can estimate driver torque across multiple steering system configurations including EPS, SbW, and hydraulic systems. By using handwheel position data that is universally available in all these systems, the same estimation algorithm adapts to different configurations without requiring configuration-specific sensors or complex conditional logic.
Solution Approach 2:
The patent uses handwheel position as an intermediary measurement that bridges different steering system types. Instead of relying on torque sensors specific to certain configurations, the position data serves as a universal intermediary from which torque can be estimated through the linear state observer, enabling cross-platform applicability.
4Measurement precision
If complex estimation architectures are used, then measurement precision is improved, but reliability deteriorates
Solution Approach 1:
By extracting only the essential dynamics needed for torque estimation through the linear state observer, the patent removes unnecessary system components and computational steps that could fail. This minimalistic architecture reduces the number of potential failure points while maintaining estimation accuracy through focused observation of critical system behavior.
Solution Approach 2:
The patent replaces complex mechanical torque sensing systems with a mathematical estimation approach that is inherently more reliable. By substituting physical sensors prone to failure with algorithm-based estimation using robust linear observer mathematics, the system achieves both accuracy and enhanced reliability.
Data Source
AI summary
A system for estimating driver torque in a steering system is configured to receive at least one handwheel position value; estimate a handwheel velocity value based on the at least one handwheel position value; receive at least one residual torque value; and estimate a driver torque based on the estimated handwheel velocity and the at least one residual torque value.