Vehicle Fuel Level Estimation Using Stable Sensor Data
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Solution Overview
Problem
Existing methods for determining fuel level in vehicles face challenges with inaccurate readings due to non-ideal data conditions, particularly during unstable vehicle operations.
Innovation Solution
A method and system that collect operation data and raw fuel level data, identify stable data points within predefined criteria, and exclude unstable data points to determine a fuel level trend, which is then averaged or fitted to a best-fit trend, and output to a user interface or remote server for accurate fuel level management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all raw fuel level data points are used for determination, then data quantity is maximized, but measurement precision deteriorates due to inclusion of unstable data points
Solution Approach 1:
The patent segments the raw fuel level data into stable and unstable portions based on vehicle operation stability assessment. By dividing the data stream and selectively processing only stable segments, the system achieves accurate fuel level determination while filtering out noisy data points that would otherwise degrade measurement precision.
Solution Approach 2:
The patent applies different quality standards to different portions of the data stream. Stable data points collected during steady-state vehicle operations are included in fuel level determination, while unstable data points from transient operations are excluded. This local quality approach ensures high measurement precision by focusing on reliable data segments.
2Reliability
If fuel level data is collected continuously during all vehicle operations, then data collection completeness is improved, but data reliability deteriorates due to unstable vehicle conditions
Solution Approach 1:
The patent performs preliminary assessment of vehicle operation stability before incorporating fuel level data points into the final determination. By pre-evaluating whether the vehicle is in a stable operating state (steady speed, stable engine RPM, minimal acceleration), the system ensures that only reliable data is collected and processed, thereby maintaining high data reliability.
Solution Approach 2:
The patent implements a feedback mechanism where vehicle operation parameters (speed, acceleration, engine RPM) are continuously monitored and used to gate the inclusion of fuel level data. This feedback loop ensures that data collection efficiency is optimized by automatically excluding data points taken during unstable operations, thereby maintaining high reliability without manual intervention.
3Measurement precision
If stability criteria are applied to filter data points, then measurement precision is improved, but device complexity increases due to additional processing requirements
Solution Approach 1:
The patent transforms the complex problem of fuel level measurement accuracy into a series of simple parameter comparisons. By defining stability criteria based on easily measurable vehicle parameters (speed variation threshold, acceleration threshold, engine RPM stability), the system achieves high measurement precision through computationally simple operations that do not significantly increase device complexity.
Data Source
AI summary
Systems, methods, devices, and models determining fuel level in vehicles are described. Raw fuel sensor data tends to be noisy and of low quality. Herein, operational data is collected, which is used to determine times when motion of the vehicle is stable. Raw fuel sensor data for these times is collected in a data subset, which is used to determine fuel level. Quality fuel sensor data is thus obtained. Fuel data can be combined over different time periods to provide a prompt initial fuel level, and an intermittent fuel level during a trip.