Vehicle Sensor Diagnosis System Predicting Performance Degradation
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Solution Overview
Problem
Existing vehicle sensor systems fail to reliably predict and assess sensor performance degradation, leading to sudden manual driving requirements, disabled automatic functions, and unplanned stops, which compromise safety and comfort.
Innovation Solution
A vehicle sensor diagnosis system that predicts upcoming surrounding conditions and estimates sensor performance based on retrieved and current data, comparing expected and detected performance levels to initiate diagnostic communications when thresholds are exceeded, ensuring safety and comfort by enabling proactive maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor performance monitoring is implemented without prediction capability, then sensor failures can be detected, but sudden manual driving requirements and unplanned stops occur due to inability to predict degradation
Solution Approach 1:
The system performs preliminary actions by predicting future sensor performance degradation trends based on historical data and current status. This allows the system to anticipate potential failures before they occur, enabling advance preparation for manual driving or maintenance activities, thus resolving the contradiction between reliability and loss of time.
Solution Approach 2:
The system implements continuous feedback loops where sensor performance data is collected, analyzed, and used to update prediction models. This feedback mechanism enables the system to adapt to actual sensor degradation patterns, improving prediction accuracy and allowing timely interventions before failures occur, thereby maintaining reliability while reducing unexpected downtime.
2Reliability
If sensor performance is monitored in real-time, then safety can be maintained, but system complexity increases due to additional processing and communication requirements
Solution Approach 1:
The system applies self-service by enabling sensors to perform self-diagnosis and self-monitoring of their own performance parameters. Each sensor monitors its own health status and communicates only critical information to the central processing unit, reducing the overall system complexity while maintaining continuous safety monitoring through distributed intelligence.
3Reliability
If continuous sensor performance assessment is performed, then sensor degradation can be detected early, but energy consumption increases due to continuous processing
Solution Approach 1:
The system implements periodic action by performing comprehensive sensor performance assessments at optimized intervals rather than continuously. The assessment frequency is dynamically adjusted based on sensor type, environmental conditions, and degradation rates, ensuring reliable detection of performance issues while significantly reducing energy consumption compared to continuous monitoring.
Data Source
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AI summary
A vehicle sensor diagnosis system (1) and method (100) and a vehicle (2) comprising such a system (1) are provided. The vehicle sensor diagnosis system (1) is arranged to; predict upcoming vehicle surrounding conditions along at least a section of a host vehicle route based on database (8) information on the host vehicle surroundings along said section and information on a current host vehicle surrounding, estimate an expected level of sensor performance for said route section based on the prediction, assess the level of sensor performance detected during host vehicle travel along said host vehicle route section, assess if a difference between the estimated level of sensor performance and the detected level of sensor performance for said host vehicle route section exceeds a first threshold difference and if so, initiate a diagnose result communication.