Vehicle Wheel Angle Estimation Using Yaw Rate and Wheel Speed
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Solution Overview
Problem
Existing vehicle navigation systems rely heavily on steering components for wheel angle estimation, which can be inaccurate due to slippage, traction issues, and model inaccuracies, affecting safety and reliability.
Innovation Solution
The use of non-steering variables such as yaw rate, linear wheel speed, and vehicle dimensions to estimate wheel angles, providing redundancy and validation, and allowing for independent control of vehicle operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If steering components are used for wheel angle estimation, then the system structure is simple, but measurement precision deteriorates due to slippage and traction issues
Solution Approach 1:
The patent introduces an intermediary computational model that uses sensor measurements (yaw rate, linear velocity, wheel speed) to calculate wheel angles indirectly. This mediator transforms readily available sensor data into accurate wheel angle estimates without directly measuring steering component positions, thereby achieving high precision while maintaining system simplicity.
Solution Approach 2:
The patent replaces direct mechanical measurement of wheel angles with a computational approach using sensor data and mathematical models. Instead of relying on mechanical steering sensors that are prone to slippage and traction issues, the system uses inertial sensors and velocity measurements combined with kinematic models to compute wheel angles, substituting mechanical measurement with computational calculation.
2Reliability
If steering data is used for navigation, then the system is easy to operate, but reliability deteriorates due to steering-component slippage and loss of tire traction
Solution Approach 1:
The patent implements a feedback mechanism where the computational model continuously compares estimated wheel angles with actual vehicle motion (from inertial sensors and GPS). This feedback loop detects discrepancies caused by slippage or traction loss and adjusts the navigation calculations accordingly, maintaining high reliability while keeping the system easy to operate through automated correction.
Solution Approach 2:
The patent performs preliminary calculations of expected wheel angles based on steering commands before actual vehicle motion occurs. By comparing these pre-calculated angles with real-time sensor measurements, the system can detect and compensate for slippage or traction issues before they significantly impact navigation accuracy, ensuring reliability without adding operational complexity.
3Measurement precision
If steering-based wheel angle estimation is used, then device complexity is low, but measurement precision worsens due to model inaccuracies
Solution Approach 1:
The patent creates a universal computational framework that can estimate wheel angles for different vehicle types and steering configurations using the same core methodology. The model accepts various sensor inputs (yaw rate, linear velocity, wheel speed) and adapts to different vehicle geometries through configurable parameters, achieving high measurement precision without increasing fundamental device complexity.
Solution Approach 2:
The patent improves measurement precision by dynamically adjusting model parameters based on operating conditions. The computational model modifies parameters such as wheelbase, track width, and steering ratios in real-time based on sensor feedback, allowing accurate wheel angle estimation across varying vehicle loads, speeds, and road conditions without requiring a fundamentally more complex system.
Data Source
AI summary
Techniques for using a set of non-steering variables to estimate an angle of a wheel are described. For example, a yaw rate, a linear velocity of a wheel, and vehicle dimensions (e.g., offset between the wheel and a turn-center reference line), can be used to estimate the angle of the wheel. Among other things, estimating angles based on non-steering variables may provide redundancy (e.g., when determined in parallel with steering-based command angles or other commanded angles) and/or may be used to validate commanded angles based on steering components.