Fuel management system capable of improving accuracy of calibration data for converting output value of fuel gauge into remaining amount of fuel in fuel tank
US-2023020594-A1 · Jan 19, 2023 · US
US12286009B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12286009-B2 |
| Application number | US-202318380853-A |
| Country | US |
| Kind code | B2 |
| Filing date | Oct 17, 2023 |
| Priority date | Jun 29, 2021 |
| Publication date | Apr 29, 2025 |
| Grant date | Apr 29, 2025 |
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Estimating fuel consumptions of a vehicle is disclosed. A first fuel consumption value in a first time interval is estimated using fuel-sender resistance data. A second fuel consumption value in a second time interval is estimated using fuel-injected mass data. At least the first fuel consumption value and the second fuel consumption value are combined to obtain a fuel consumption value. The fuel consumption value is then output.
Opening claim text (preview).
What is claimed is: 1. A method for estimating fuel consumptions of a vehicle, comprising: 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; combining at least the first fuel consumption value and the second fuel consumption value to obtain a fuel consumption value; and outputting the fuel consumption value. 2. The method of claim 1 , wherein the first time interval and the second time interval are consecutive, non-overlapping intervals of a same driving session. 3. The method of claim 1 , further comprising: calibrating the fuel-sender resistance data based on a benchmark obtained from a liter-by-liter fuel fill test. 4. The method of claim 1 , further comprising: obtaining the fuel-injected mass data from a fuel injection system of the vehicle in real-time. 5. The method of claim 1 , wherein estimating the second fuel consumption value in the second time interval using the fuel-injected mass data comprises: adjusting the second fuel consumption value based on torque data. 6. The method of claim 1 , wherein estimating the first fuel consumption value in the first time interval using the fuel-sender resistance data comprises: in response to receiving an ignition start signal, determining whether to apply a cold-start calibration factor based on an engine temperature of the vehicle. 7. The method of claim 1 , further comprising: analyzing driving behavior data to identify instances of sudden accelerations; and adjusting, prior to the outputting, the fuel consumption value to account for an increased fuel usage associated with the sudden accelerations. 8. A vehicle, comprising: a fuel tank; a fuel sender; and a processor configured to obtain an estimate of a fuel level at a time instant in the fuel tank by instructions to: identify an unreliable instant fuel sender resistance value; determine, using history data, a start time of an unreliable period associated with the unreliable instant fuel sender resistance value; retrieve a reliable fuel sender resistance value from the history data corresponding to the start time of the unreliable period; calculate a first fuel level from the reliable fuel sender resistance value using lookup data; compute a second fuel consumed level from fuel-injected mass data during the unreliable period; and combine the first fuel level with the second fuel consumed level to provide an estimated current fuel level in the fuel tank. 9. The vehicle of claim 8 , wherein the processor is further configured to: use first derivatives of the fuel-injected mass data to determine the start time of the unreliable period. 10. The vehicle of claim 8 , wherein the processor is further configured to: use second derivatives of the fuel-injected mass data to determine the start time of the unreliable period. 11. The vehicle of claim 8 , wherein the processor is further configured to: adjust the estimated current fuel level based on torque data, wherein higher torque is correlated with increased fuel consumption. 12. The vehicle of claim 8 , wherein the processor is further configured to: identify driving events associated with higher fuel consumption; and adjusting the estimated current fuel level to account for the higher fuel consumption. 13. The vehicle of claim 12 , wherein the driving events correspond to sudden accelerations. 14. The vehicle of claim 8 , wherein the processor is further configured to: adjusting the estimated current fuel level based on an identification of a cold start accounting for increased fuel consumption experienced during an initial engine start in low-temperature conditions. 15. The vehicle of claim 14 , wherein the processor is further configured to: detect a cold-start condition based on an engine coolant temperature being less than a predetermined cold start temperature. 16. A non-transitory computer-readable storage medium, comprising instructions executable by a processor to perform operations for estimating fuel consumptions of a vehicle, the operations comprising: 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; combining at least the first fuel consumption value and the second fuel consumption value to obtain a fuel consumption value; and outputting the fuel consumption value. 17. The non-transitory computer-readable storage medium of claim 16 , further comprising: obtaining the fuel-injected mass data from a fuel injection system of the vehicle in real-time. 18. The non-transitory computer-readable storage medium of claim 16 , wherein estimating the second fuel consumption value in the second time interval using fuel-injected mass data comprises: adjusting the second fuel consumption value based on torque data. 19. The non-transitory computer-readable storage medium of claim 16 , wherein estimating the first fuel consumption value in a first time interval using the fuel-sender resistance data comprises: in response to receiving an ignition start signal, determining whether to apply a cold-start calibration factor based on an engine temperature of the vehicle. 20. The non-transitory computer-readable storage medium of claim 16 , wherein the operations further comprise: analyzing driving behavior data to identify instances of sudden accelerations; and adjusting, prior to the outputting, the fuel consumption value to account for an increased fuel usage associated with the sudden accelerations.
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