Autonomous Vehicle Power Distribution Fault Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous and drive-by-wire vehicles face challenges in maintaining a robust electrical distribution system, prone to faults such as open circuitry and wiring issues, which can compromise safety-critical components like braking and steering systems during motion.
Innovation Solution
A system that continuously monitors power distribution systems in autonomous vehicles, using vehicle control modules to compare input voltages and currents with real-time waveforms from inertial events, and executes mitigating actions if correlations indicate faults, such as issuing health warnings or navigating the vehicle to a service center.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle uses a robust electrical distribution system for safety-critical components, then reliability is improved, but the system becomes more complex and prone to faults during motion
Solution Approach 1:
The system performs preliminary correlation analysis between inertial waveforms and power signals to identify potential faults before they manifest as actual failures. By continuously comparing expected inertial events with observed power signal variations, the system can detect intermittent or latent faults in wiring and connectors before they compromise safety-critical components.
Solution Approach 2:
The diagnostic ECU establishes a feedback loop that continuously monitors power signals, compares them with inertial waveform data, and adjusts diagnostic thresholds based on learned patterns. This feedback mechanism enables the system to adapt to normal operational variations while maintaining sensitivity to actual faults, thereby improving reliability without proportionally increasing complexity.
2Measurement precision
If the system continuously monitors power signals and inertial waveforms in real-time, then fault detection capability is improved, but computational resources and processing time are consumed
Solution Approach 1:
The system applies partial monitoring by focusing computational resources on detecting specific correlation patterns between inertial waveforms and power signals rather than analyzing all possible fault modes equally. The correlation function computes only the necessary metrics to identify faults during motion, avoiding excessive processing of normal operational variations.
Solution Approach 2:
The continuous monitoring is implemented through periodic sampling and correlation analysis rather than continuous computation. The system periodically compares inertial waveform segments with power signal segments, updating diagnostic status at intervals that balance detection precision with computational efficiency, thereby reducing processing time while maintaining fault detection capability.
3Measurement precision
If the system correlates inertial waveforms with power signals to detect faults, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The inertial waveform data and power signal correlation framework serves multiple diagnostic functions simultaneously: detecting wiring faults, connector issues, and latent failures across different electrical systems. This universal approach improves measurement precision without proportionally increasing complexity by using a single correlation methodology for multiple diagnostic purposes.
Solution Approach 2:
The correlation function acts as an intermediary that bridges inertial waveform data and power signal analysis. Rather than requiring separate diagnostic systems for different fault types, the correlation mechanism mediates between these data sources to identify faults, thereby improving detection precision while managing complexity through a unified analytical approach.
Data Source
AI summary
The disclosed systems and methods monitor power distribution systems for autonomous and drive-by-wire vehicles. The system can monitor input voltage, current, and other power signals, and reporting the input voltages and currents to a diagnostic engine control unit (ECU). The ECU compares the power signals with real-time (or substantially real-time) waveforms associated with vibrations, acceleration, road bumps, and other phenomena normally encountered in on-road operation, and evaluates any determined correlation between inertial events (e.g., bumps or acceleration, etc.) and changes in the power signals. If the diagnostic ECU determines a correlation between the inertial waveform, the diagnostic ECU map perform mitigating steps, such as issuing a vehicle health warning, generate instructions that cause the vehicle to navigate to a service center, or perform other mitigating actions.