Autonomous Brake Wear Estimation Through Deceleration Feedback
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Solution Overview
Problem
Brake wear in autonomous vehicles is not adequately accounted for in existing brake tables, leading to potential safety and performance issues due to reduced braking effectiveness over time.
Innovation Solution
A system that estimates brake wear by generating and analyzing vehicle deceleration data during braking events, using a learning model to modify brake tables to adjust brake requests accordingly, ensuring optimal braking performance and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional brake tables are used without wear compensation, then the brake system structure remains simple and operation is straightforward, but braking performance deteriorates over time as brakes wear down
Solution Approach 1:
The system implements feedback by continuously monitoring actual deceleration during braking events and comparing it with expected deceleration from the brake table. This feedback loop enables the system to detect brake wear and automatically adjust brake requests to compensate, maintaining reliable braking performance without requiring complex manual intervention or replacement schedules
Solution Approach 2:
The brake control system performs self-adjustment by automatically modifying brake requests based on detected wear conditions. The system serves itself by detecting its own performance degradation and correcting for it through learned compensation factors, eliminating the need for external monitoring or manual calibration
2Productivity
If brake wear is not accounted for, then the brake system operates with simple control logic, but stopping distance increases and stopping power decreases over time
Solution Approach 1:
The system performs preliminary action by proactively detecting brake wear through continuous monitoring of deceleration data and pre-computing compensation factors before performance degradation becomes critical. This allows the system to maintain optimal braking effectiveness by applying learned adjustments in advance, rather than reacting only when performance drops below acceptable thresholds
Solution Approach 2:
The system ensures continuity of useful action by continuously collecting deceleration data during braking events and continuously updating wear compensation models. This ongoing process ensures that braking effectiveness is maintained throughout the brake component's service life, with adjustments being made progressively rather than in discrete intervals
Data Source
AI summary
Methods and systems for estimating autonomous brake wear in a vehicle. A brake table includes a correspondence between a desired brake request and an applied brake force. Vehicle deceleration data is generated during several braking events of the vehicle. The vehicle deceleration data includes (i) desired brake requests issued during the braking events, and (ii) vehicle speeds during the brake request. A learning model is executed on the deceleration data. The learning model is configured to estimate a brake wear based on changes in differences between (a) the desired brake requests issued during the braking events and (b) the vehicle speeds during the brake requests. Based on the estimated brake wear, the brake table is modified in order to yield a modified brake table. A new desired brake request is generated using the modified brake table.