Hands-on-wheel detection via dynamic torque estimation
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Solution Overview
Problem
Existing steering systems, particularly hydraulic systems, face challenges in accurately determining whether an operator's hands are on the handwheel during rapid steering maneuvers, leading to errors due to the lack of consideration for inertia, damping, and friction effects.
Innovation Solution
A method and system for hands-on-wheel detection that generates handwheel speed and acceleration signals, synchronizes them by creating delayed signals, and calculates an operator torque estimation using damping, inertia, and friction values to determine if the operator's hands are on the handwheel, improving accuracy during rapid motions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional hands-on-wheel detection methods are used in hydraulic steering systems, then the system structure remains simple, but detection accuracy deteriorates during rapid steering maneuvers due to ignoring inertia, damping, and friction effects
Solution Approach 1:
The patent applies parameter changes by incorporating dynamic parameters (inertia, damping, friction) into the torque estimation model. The controller calculates operator torque by considering not only the basic steering torque but also the inertial torque (based on handwheel acceleration), damping torque (based on handwheel speed), and friction torque, thereby improving detection accuracy during rapid steering maneuvers without requiring additional hardware sensors
Solution Approach 2:
The patent replaces traditional mechanical detection methods with an electronic control-based torque estimation approach. Instead of using complex mechanical sensors to directly detect hand presence, the system uses the electronic controller to calculate operator torque by integrating dynamic parameters into the torque model, thereby achieving higher accuracy while maintaining relatively simple device structure
2Measurement precision
If dynamic effects (inertia, damping, friction) are considered in torque estimation, then detection accuracy during rapid maneuvers improves, but calculation complexity increases
Solution Approach 1:
The system uses self-service by leveraging existing handwheel angle sensor data and the controller's computational capabilities to automatically calculate dynamic effects. The controller continuously monitors handwheel position and derives speed and acceleration signals, then applies the dynamic torque model without requiring external input or additional complex processing units, making the enhanced calculation self-contained and manageable
Solution Approach 2:
The patent applies preliminary action by pre-establishing the torque estimation model that incorporates inertia, damping, and friction parameters. The controller is pre-programmed with the mathematical relationships and coefficient values needed to calculate dynamic torques, allowing it to rapidly compute accurate operator torque estimates during rapid steering maneuvers without real-time complexity
Data Source
AI summary
A method hands-on-wheel detection includes receiving a handwheel angle signal from a sensor associated with a handwheel of a vehicle and generating, based on a handwheel angle indicated by the handwheel angle signal, a handwheel speed signal and a handwheel acceleration signal. The method also includes synchronizing the handwheel speed signal and the handwheel acceleration signal by generating a delayed handwheel speed signal and a delayed handwheel acceleration signal. The method also includes generating an operator torque estimation signal based on, at least, the delayed handwheel speed signal and the delayed handwheel acceleration signal. The method also includes determining whether hands of an operator of the vehicle are on the handwheel based on the operator torque estimation signal.