Vehicle Yaw Rate Sensor Abnormality Detection
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Solution Overview
Problem
Existing vehicle behavior control systems face challenges in accurately judging abnormalities in yaw rate detection means, particularly when a vehicle is turning, which can affect vehicle behavior and safety.
Innovation Solution
A vehicle behavior control apparatus that includes a steering angle detection means, a lateral acceleration detection means, and a yaw rate detection means, with a control section that estimates turning directions from both sensors and judges abnormalities by comparing these directions with the actual yaw rate, using threshold values to determine accurate turning directions and prevent erroneous judgments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the yaw rate detection means is used to control vehicle behavior, then the vehicle behavior control is improved, but the risk of erroneous judgment due to sensor abnormality increases
Solution Approach 1:
The patent introduces an intermediary abnormality judgment device that acts as a mediator between the yaw rate detection means and the vehicle behavior control system. This intermediary component monitors the yaw rate sensor output and compares it with expected values based on steering angle and vehicle speed, detecting abnormalities before they affect vehicle control. This resolves the contradiction by filtering out harmful sensor abnormalities while preserving reliable sensor data for control purposes.
Solution Approach 2:
The patent implements a feedback mechanism where the abnormality judgment device continuously monitors the yaw rate detection means and provides feedback about sensor health status. The system compares actual yaw rate with estimated yaw rate (calculated from steering angle and vehicle speed) and feeds back abnormality information to prevent erroneous control actions. This feedback loop ensures reliable vehicle behavior control while protecting against sensor failures.
2Speed
If the abnormality judgment is based on simple threshold comparison, then the judgment speed is improved, but the accuracy of abnormality detection deteriorates
Solution Approach 1:
The patent transitions from one-dimensional threshold comparison to multi-dimensional analysis by introducing multiple comparison criteria: comparing yaw rate sign with steering angle sign, comparing magnitude relationships, and using multiple threshold levels (first threshold for sign comparison, second threshold for magnitude comparison). This dimensional expansion maintains fast judgment speed while significantly improving detection accuracy by considering multiple aspects of sensor behavior simultaneously.
Solution Approach 2:
The abnormality judgment process is segmented into multiple independent comparison steps: first comparing signs of yaw rate and steering angle, then comparing magnitudes using different thresholds, and finally综合 (comprehensive) evaluation. This segmentation allows each comparison to be performed quickly with simple operations while the combination of multiple comparisons achieves high overall accuracy, resolving the contradiction between speed and precision.
3Measurement precision
If multiple sensors and comparison methods are used to improve judgment accuracy, then the abnormality detection precision is improved, but the system complexity increases
Solution Approach 1:
The patent makes the existing steering angle sensor and vehicle speed sensor serve multiple functions: they are used for both normal vehicle behavior control and for abnormality detection of the yaw rate sensor. By making these components multi-functional, the system achieves high abnormality detection precision without adding dedicated hardware, thus improving precision while minimizing complexity increase.
Solution Approach 2:
The system uses its own existing sensors (steering angle sensor, vehicle speed sensor) to monitor and detect abnormalities in the yaw rate sensor. The vehicle's operational parameters serve to self-diagnose sensor health. This self-service approach enables accurate abnormality detection without requiring external monitoring equipment, maintaining system simplicity while achieving high detection precision.
Data Source
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AI summary
A control section 20 includes a first turning direction estimating means 25a for estimating a first yaw rate according to an output of a steering angle sensor 92 and estimating a first turning direction from the positive and the negative of the first yaw rate when an absolute value of the first yaw rate concerned is not less than a first threshold value, a second turning direction estimating means 25b for estimating a second yaw rate according to an output of the lateral acceleration detection sensor 93 and estimating a second turning direction from the positive and the negative of a difference between the second yaw rate and the second threshold value when the second yaw rate is not less than or not more than the second threshold value; a vehicle turning direction judging means 25c for judging that the direction when the first turning direction and the second turning direction are the same is judged to be a turning direction of the vehicle and an abnormality judging means 25d for judging that the yaw rate sensor 94 is abnormal when the turning direction of the vehicle and the direction of the actual yaw rate differs from each other.