Steering System Road Friction Estimation via Rack Force
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Solution Overview
Problem
Existing vehicle control systems struggle to determine the road friction coefficient accurately and continuously, especially when the vehicle is turning, as they rely on steady-state conditions and binary or tri-state detection methods, which are not applicable during all driving maneuvers and cannot provide real-time updates.
Innovation Solution
A steering system that computes a model rack force value based on vehicle speed, steering angle, and road-friction coefficient, determining the difference between this value and a load rack force, and iteratively updates the road-friction coefficient using signal processing techniques, allowing for continuous detection and adaptation during various driving conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If steady-state conditions and binary or tri-state detection methods are used, then the detection system is simple, but the road friction coefficient cannot be determined accurately and continuously during turning maneuvers
Solution Approach 1:
The patent replaces traditional mechanical steady-state detection methods with a computational model-based approach. The controller computes a model rack force value using vehicle speed, steering angle, and road friction coefficient, then compares it with the actual load rack force to iteratively update the friction coefficient estimate. This substitution of mechanical detection with computational modeling enables continuous accurate detection during dynamic turning maneuvers without requiring steady-state conditions.
2Productivity
If iterative updating using model rack force and load rack force difference is implemented, then the road friction coefficient is updated continuously, but the computational complexity increases
Solution Approach 1:
The patent implements continuous iterative updating of the road friction coefficient by continuously computing the difference between model rack force and load rack force. The controller repeatedly updates the friction coefficient estimate using this difference until convergence or a maximum iteration limit is reached. This continuous action ensures real-time friction coefficient availability for vehicle control systems, maintaining high productivity despite the computational iterations required.
3Reliability
If real-time continuous detection is implemented during all driving maneuvers, then the road friction coefficient is always available for control, but the detection method becomes more complex than binary or tri-state methods
Solution Approach 1:
The patent employs a feedback mechanism where the controller continuously compares the computed model rack force with the measured load rack force, uses the difference to update the road friction coefficient estimate, and repeats the process. This closed-loop feedback approach ensures the friction coefficient is continuously refined and available for reliable vehicle control during all driving maneuvers, not just steady-state conditions, improving overall system reliability.
Data Source
AI summary
According to one or more embodiments, a method includes computing, by a steering system, a model rack force value based on a vehicle speed, steering angle, and a road-friction coefficient value. The method further includes determining, by the steering system, a difference between the model rack force value and a load rack force value. The method further includes updating, by the steering system, the road-friction coefficient value using the difference that is determined.