Vehicle Data System Tuning Thresholds via Extended Kalman Filter
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Solution Overview
Problem
Existing vehicle diagnostic systems fail to accurately determine vehicle-specific thresholds for parameters like engine speed and braking aggressiveness due to variations across different vehicle models and upgrades, leading to incorrect assessments of vehicle performance.
Innovation Solution
A vehicle data system employing an Extended Kalman Filter (EKF) to generate tuned thresholds based on initial values and vehicle data, ensuring accurate modeling and normalization of vehicle features, with the ability to store these thresholds in both vehicle memory and external servers for future reference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard operating ranges are used for vehicle parameters, then the system is simple to operate, but the measurement precision is poor due to variations across different vehicle models and upgrades
Solution Approach 1:
The system dynamically adjusts threshold parameters based on vehicle-specific data rather than using fixed standard ranges. The processor modifies threshold values according to detected vehicle characteristics, model variations, and operational conditions, transforming static thresholds into adaptive parameters that match each vehicle's actual behavior patterns.
Solution Approach 2:
The system automatically determines and tunes thresholds using onboard vehicle data without requiring manual intervention or external calibration. The processor self-calibrates by analyzing vehicle performance characteristics and generating appropriate thresholds autonomously, eliminating the need for complex manual configuration while achieving high measurement precision.
2Measurement precision
If vehicle-specific thresholds are determined using complex analysis, then the measurement precision improves, but the loss of time increases due to data processing requirements
Solution Approach 1:
The system performs preliminary threshold determination during vehicle initialization or when data becomes available, rather than delaying analysis until needed. By pre-calculating and storing tuned thresholds in memory, the system eliminates real-time computational delays and provides instant access to accurate threshold values when required for diagnostic or monitoring operations.
Solution Approach 2:
The system creates and stores copies of tuned thresholds in vehicle memory for rapid retrieval and application. Instead of repeatedly performing complex calculations, the processed threshold data is cached and reused across multiple operations, significantly reducing time loss while maintaining the precision benefits of sophisticated threshold determination.
Data Source
AI summary
A vehicle data system may include an onboard diagnostic port configured to receive a request for a threshold relating to a vehicle parameter, the threshold indicating a limit in a standard operating range of the vehicle parameter, and a processor configured to receive the request for the threshold, receive vehicle data from at least one vehicle component, and apply a filter to the vehicle data to generate a tuned threshold for the requested threshold based on an initial value and the vehicle data.