Hybrid Fuel Level Estimation for Saddle-Shaped Vehicle Tanks
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Solution Overview
Problem
Current fuel sender resistance techniques provide inaccurate fuel level estimates in vehicle fuel tanks, especially when the tank is filled beyond the full indicator, near empty, or has a saddle shape, leading to inefficiencies and costs for fleet operators.
Innovation Solution
A method that combines fuel sender resistance data with fuel-injected mass data and torque data to estimate fuel consumption, using lookup tables and calibration factors to correct for unreliable resistance readings, and integrates this information to provide accurate fuel level estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fuel sender resistance techniques are used to estimate fuel level, then the device complexity is reduced, but the measurement precision deteriorates
Solution Approach 1:
The patent combines fuel sender resistance data with fuel-injected mass data from the engine control unit to estimate fuel consumption. This merging of multiple data sources compensates for the limitations of resistance-only techniques, particularly in saddle-shaped tanks, while maintaining reasonable system complexity by utilizing existing vehicle sensors.
Solution Approach 2:
The system changes the parameter used for fuel level estimation from solely resistance-based to a hybrid approach incorporating mass-based fuel injection data. This parameter change allows accurate tracking of fuel consumption regardless of tank geometry, resolving the measurement precision issue without requiring complete system redesign.
2Ease of operation
If fuel sender resistance data alone is used, then the ease of operation is improved, but the reliability deteriorates
Solution Approach 1:
The system uses the fuel-injected mass data from the engine control unit for dual purposes: engine management and fuel consumption tracking. This multi-functionality approach improves reliability by leveraging existing data infrastructure while maintaining ease of operation through a unified data source that serves multiple functions.
Solution Approach 2:
The system continuously monitors both resistance data and fuel-injected mass data, comparing them to identify discrepancies and correct estimation errors. This feedback mechanism improves reliability by detecting when resistance-based estimation becomes unreliable and compensating using mass-based consumption data, while requiring minimal additional operational input from the user.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach results in more accurate fuel level estimates, reducing operational costs and ensuring fleet vehicles are properly fueled, thereby optimizing routes and service quality.
Implementation Method 1
a fuel sender that is configured to provide a signal indicative of a fuel level in the fuel tank
Data Source
AI summary
Estimating a fuel consumption includes receiving a request for estimating the fuel consumption between a first time and a second time; estimating a first fuel consumption value in a first time interval using fuel-sender resistance data; estimating a second fuel consumption value in a second time interval using fuel-injected mass data, where the first time interval and the second time interval are consecutive, non-overlapping intervals; and combining at least the first fuel consumption value and the second fuel consumption value to obtain a fuel consumption value.