Brake Component Failure Prediction From Braking Response Patterns
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Solution Overview
Problem
Existing brake system monitoring technologies are limited to detecting failures after they occur, failing to predict future functional impairments or failures in brake system components, which is critical for ensuring reliable autonomous vehicle operation.
Innovation Solution
A predictive method and device that analyze brake system component behavior through coordinated monitoring of brake request, system reaction, and vehicle response parameters, using coordinate systems to detect deviations and predict impending failures, allowing for early diagnosis and proactive maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If brake system components are monitored manually or replaced based on fixed intervals, then maintenance simplicity is maintained, but component reliability deteriorates due to undetected wear and contamination
Solution Approach 1:
The brake system components perform self-diagnosis by equipping them with sensors that automatically monitor their own operational parameters such as wear state, contamination levels, and performance metrics. This eliminates the need for external manual inspection while maintaining high reliability through continuous self-monitoring.
Solution Approach 2:
The system implements continuous feedback loops where sensors monitor component parameters in real-time, transmit data to a control unit, and trigger alerts or maintenance notifications when thresholds are exceeded. This closed-loop feedback mechanism ensures reliable operation by immediately detecting and reporting degradation.
2Productivity
If brake system components are replaced based on fixed time intervals, then maintenance operation simplicity is maintained, but time efficiency deteriorates due to premature or delayed replacements
Solution Approach 1:
The system performs preliminary monitoring and assessment of component conditions before failure occurs. Sensors detect early signs of wear or contamination and predict remaining service life, allowing maintenance to be scheduled optimally based on actual component state rather than fixed intervals.
Solution Approach 2:
The system transitions from time-based maintenance parameters to condition-based parameters by continuously measuring actual component states such as wear thickness, contamination concentration, and performance degradation. Maintenance decisions are made based on these dynamic parameter changes rather than fixed time schedules.
3Measurement precision
If sensors are added to monitor brake system components, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system employs multi-functional sensors and evaluation units that can monitor multiple different parameters across various brake components using the same hardware platform. A single sensor system can measure wear, contamination, temperature, and pressure, reducing overall system complexity compared to dedicated sensors for each parameter.
Data Source
Figure 1a
Figure 1b~1c
Figure 1d~1e
AI summary
The invention relates to a prediction device and a prediction method for at least one brake system component (10, 12, 14, 16) of a brake system of a vehicle, having the steps of ascertaining value groups, each of which has values ascertained during multiple vehicle (12) braking processes that are induced by the driver and/or are autonomous and each of which comprises (SI) at least one requested brake specification variable (x, vx and I0) ascertained at a point in time, at least one brake system reaction variable (p12, I and p16) ascertained at the same point in time, and at least one vehicle reaction variable (F and a) ascertained at the same point in time; entering the ascertained value groups into coordinate systems, wherein each of the coordinate systems has at least two axes, each of which indicates the requested brake specification variable or at least one of the requested brake specification variables (x, vx and I0), the brake system reaction variable or at least one of the brake system reaction variables (p12, I and p16), and/or the vehicle reaction variable or at least one of the vehicle reaction variables (F and a); and estimating whether the occurrence of at least one functional impairment of the at least one brake system component (10, 12, 14, 16) of the brake system is probable at least during a specified prediction time interval (S4) using the coordinate system.