Torque Sensor Self-Calibration for Power Steering
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Solution Overview
Problem
Existing power steering systems face challenges in accurately calibrating torque sensors over the lifetime of a vehicle, leading to potential inaccuracies in driver input measurement and reduced steering comfort and safety.
Innovation Solution
A system and method that includes a torque sensor evaluation module to monitor conditions and detect situations where torque input is below a threshold, allowing for the estimation and correction of torque sensor errors, and the generation of corrected torque signals for the electric motor, using a mathematical learning model to account for errors such as offsets, rotational asymmetry, and vehicle vibrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If torque sensor calibration is performed manually over vehicle lifetime, then measurement accuracy can be maintained, but system complexity and ease of operation deteriorate due to requiring manual intervention and recalibration procedures
Solution Approach 1:
The system performs automatic self-calibration by detecting zero-torque conditions during normal operation and autonomously determining offset corrections without requiring manual intervention. The control module automatically monitors torque sensor signals, identifies when torque input is below thresholds, and executes calibration routines to maintain measurement accuracy throughout vehicle lifetime.
Solution Approach 2:
The system performs calibration actions in advance by continuously monitoring for zero-torque conditions and preparing correction values before they are needed. The control module accumulates torque sensor data during idle periods and pre-computes offset corrections that will be applied to maintain accuracy during subsequent steering operations.
2Measurement precision
If torque sensor calibration is performed frequently to maintain accuracy, then measurement precision improves, but loss of time increases due to repeated calibration procedures
Solution Approach 1:
The system performs calibration continuously during normal vehicle operation by utilizing zero-torque conditions that naturally occur during driving (such as when the vehicle is stationary or coasting). The control module continuously monitors torque sensor signals and accumulates calibration data over time, converting otherwise wasted idle time into productive calibration opportunities without requiring dedicated calibration periods.
Solution Approach 2:
The system performs calibration periodically whenever zero-torque conditions are detected during vehicle operation. The control module checks torque sensor signals at regular intervals and executes calibration routines whenever the torque input falls below predetermined thresholds, transforming the vehicle's operational cycles into repeated calibration opportunities that maintain accuracy without requiring separate calibration sessions.
3Measurement precision
If manual recalibration is required to correct torque sensor errors, then measurement precision can be maintained, but device complexity increases due to requiring manual calibration procedures and user intervention
Solution Approach 1:
The system automatically performs calibration by monitoring its own torque sensor signals and autonomously determining when zero-torque conditions occur. The control module independently executes the entire calibration process including data collection, offset calculation, and correction application without requiring external manual intervention, thereby maintaining accuracy while reducing system complexity.
Solution Approach 2:
The system uses feedback from the torque sensor signals themselves to detect zero-torque conditions and trigger calibration routines. The control module continuously monitors the torque sensor output, compares it against threshold values, and automatically initiates calibration when the feedback indicates appropriate conditions, creating a self-regulating calibration system that reduces complexity by eliminating manual decision-making.
Data Source
AI summary
An embodiment of a system for evaluating a torque sensor includes an input module configured to receive torque signals from a hand wheel torque sensor in a vehicle, and a sensor evaluation module configured to perform monitoring a condition affecting the hand wheel torque sensor, and determining whether the condition indicates a desired situation in which a probability of an input torque being applied to the hand wheel is below a selected threshold. The sensor evaluation module is also configured to perform, based on detecting the desired situation, automatically analyzing the torque signals received during a time duration of the desired situation to estimate one or more torque sensor error values, and outputting at least one of a corrected torque signal and the one or more error values to a torque command generation module, the torque command generation module configured to generate a torque command to an electric motor.