Adaptive Vehicle Prognostic System Bandwidth Optimization
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Solution Overview
Problem
Conventional vehicle prognostic systems continuously transmit data and execute algorithms at fixed frequencies, consuming valuable bandwidth and resources, especially when vehicle components are functioning properly after repair or replacement.
Innovation Solution
A system and method that adjust the frequency of data transmission and algorithm execution based on data indicating repair or replacement of vehicle components, reducing unnecessary resource usage by lowering transmission and processing frequencies when components are recently maintained.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data transmission frequency is increased to improve monitoring accuracy, then component condition assessment improves, but wireless bandwidth consumption increases
Solution Approach 1:
The system dynamically adjusts the data transmission frequency based on component health status. When components are healthy, transmission frequency is reduced to conserve bandwidth. When degradation is detected, frequency increases to improve monitoring precision. This dynamic adaptation resolves the contradiction between measurement precision and bandwidth consumption.
Solution Approach 2:
The system changes the transmission frequency parameter in response to component condition. By modifying this operational parameter based on real-time health assessment, the system optimizes the balance between monitoring accuracy and resource consumption, directly addressing the technical contradiction.
2Measurement precision
If prognostic algorithm execution frequency is increased to improve prediction accuracy, then component failure prediction improves, but processing resource consumption increases
Solution Approach 1:
The system dynamically adjusts algorithm execution frequency based on component risk levels. For healthy components, execution frequency is reduced to conserve processing resources. For at-risk components, frequency increases to improve prediction accuracy. This dynamic strategy resolves the contradiction between prediction accuracy and resource consumption.
Solution Approach 2:
The system modifies the algorithm execution frequency parameter according to component health status and risk assessment. This parameter adaptation allows the system to optimize the balance between prediction precision and processing resource utilization.
3Reliability
If continuous monitoring is maintained after component repair to ensure reliability, then component reliability improves, but data transmission costs increase
Solution Approach 1:
The system implements periodic monitoring with variable intervals based on component history and current status. After repairs, monitoring continues at reduced frequency rather than continuous levels, maintaining reliability while reducing transmission costs. This periodic approach with adaptive intervals resolves the contradiction between reliability and energy loss.
Solution Approach 2:
The system applies partial monitoring intensity after repairs - sufficient to ensure reliability but less than continuous full-intensity monitoring. This partial action approach maintains adequate reliability while significantly reducing data transmission costs and energy consumption.
Data Source
AI summary
A method and system are provided for generating prognostic information regarding a component in a vehicle. The method includes receiving a first set of data for one or more parameters corresponding to the component. The first set of data is obtained from a degradation signal wirelessly transmitted from the vehicle at a first predetermined frequency. The method further includes executing, at a second predetermined frequency, a set of executable instructions for assessing a condition of the component in response to the first set of data. The method further includes obtaining a second set of data indicative of repair or replacement of the component and adjusting at least one of the first predetermined frequency and the second predetermined frequency responsive to the second set of data.