ESTIMATING AND PREDICTING FUEL USAGE WITH SMARTPHONE

• US 20160123752A1
• Filed: 10/30/2014
• Published: 05/05/2016
• Est. Priority Date: 10/30/2014
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Kandula, Srikanth, Bahl, Paramvir, Patro, Ashish, Shoaib, Mohammed
• Application Number:
  US14/529,100
• Publication Number:
  US 20160123752A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01C 21/3469 Fuel consumption; Energy use; Emission aspects

Abstract

Examples are disclosed herein that relate to estimating and predicting vehicular fuel use. One example estimates fuel usage by a vehicle during a trip by obtaining sensor measurements from one or more sensors of a mobile computing device during the trip, determining a plurality of trip features from the sensor measurements, each trip feature representing an aspect of one or more of energy produced and energy consumed during the trip, obtaining vehicle-specific parameters of the vehicle, and determining an estimated fuel usage from the vehicle-specific parameters and the plurality of trip features for output by the computing device.

Claims

1. On a computing device, a method for predicting fuel usage for a vehicle, the method comprising:

obtaining map information for a trip having a route;

obtaining road characteristic information for the route from the map information, the road characteristic information defining road features for the route;

obtaining a plurality of trip features from the map information and road characteristic information, the plurality of trip features comprising effects of the road features on a vehicle traveling the route;

obtaining vehicle-specific parameters for the vehicle;

determining a predicted fuel usage for the trip from the vehicle-specific parameters and the plurality of trip features; and

outputting the predicted fuel usage.

2. The method of claim 1, wherein obtaining road characteristic information comprises obtaining the road features for each road segment of a plurality of road segments for the route and obtaining the plurality of trip features for each road segment.

3. The method of claim 1, further comprising, for each of the plurality of trip features, updating a model relating the road features to each trip feature.

4. The method of claim 1, wherein the road features comprise one or more of a road length, a road speed limit, a road grade, a road rolling resistance, a road change in potential energy, a road aerodynamic drag, rush hour velocity multipliers, and a number of stops.

5. The method of claim 1, wherein the plurality of trip features comprises one or more of an energy from burning fuel, an energy generated by an engine of the vehicle, a change in kinetic energy, a change in potential energy, an aerodynamic drag, a rolling resistance, and a standby energy.

6. The method of claim 1, wherein the vehicle-specific parameters comprise one or more of a vehicle mass, a frontal effective area, and an efficiency of an engine of the vehicle.

7. The method of claim 1, further comprising obtaining vehicle-specific parameters from vehicle specifications.

8. A machine-readable storage device comprising instructions executable by a mobile computing device to estimate fuel usage by a vehicle during a trip by:

obtaining sensor measurements from one or more sensors of the mobile computing device during the trip,

determining a plurality of trip features from the sensor measurements, each trip feature representing an aspect of one or more of energy produced and energy consumed during the trip;

obtaining vehicle-specific parameters of the vehicle;

determining an estimated fuel usage from the vehicle-specific parameters and the plurality of trip features;

outputting the estimated fuel usage; and

presenting feedback relating driving behaviors of a driver of the trip to the estimated fuel usage for the trip.

9. The device of claim 8, wherein the instructions executable to determine the plurality of trip features are executable to

segment the sensor measurements over time into epochs, wherein a duration of each epoch is sufficient to include a plurality of sensor measurements from each sensor;

sum over the sensor measurements from each sensor for each epoch, wherein the sum is performed based upon a fixed rate change between consecutive sensor measurements for each sensor,

and determine the plurality of trip features for each epoch based upon the sum.

10. The device of claim 9, wherein the instructions executable to determine the plurality of trip features are executable to omit epochs having sensor measurements for less than a threshold fraction of the epoch and to omit epochs having a time difference between two of the consecutive sensor measurements larger than a threshold time.

11. The device of claim 8, wherein the plurality of trip features comprises one or more of an energy from burning fuel, an energy generated by an engine of the vehicle, a change in kinetic energy, a change in potential energy, an aerodynamic drag, a rolling resistance, and a standby energy.

12. The device of claim 8, wherein the sensor measurements comprise one or more of a vehicular speed, a location of the vehicle, a slope of a road segment of the trip, a fuel injection rate, an engine revolutions-per-minute speed, and a torque.

13. The device of claim 8, wherein the vehicle-specific parameters comprise one or more of a vehicle mass, a frontal effective area, and an efficiency of an engine of the vehicle.

14. The device of claim 8, wherein the instructions executable to obtain the vehicle-specific parameters are executable to learn the vehicle-specific parameters from a relationship between the plurality of trip features and the estimated fuel usage.

15. The device of claim 8, wherein the instructions executable to present feedback are executable to present comparative feedback comprising the feedback for the driver compared to additional feedback for a second driver, the additional feedback comprising relation of driving behavior of the second driver to a second estimated fuel usage for the second driver.

16. A mobile computing device, comprising:

a logic subsystem;

a data-holding subsystem comprising instructions executable by the logic subsystem to estimate fuel usage by a vehicle during a trip by

obtaining sensor measurements from one or more sensors of the mobile computing device during the trip,

determining a plurality of trip features from the sensor measurements, each trip feature representing an aspect of one or more of energy produced and energy consumed during the trip;

obtaining vehicle-specific parameters of the vehicle;

determining an estimated fuel usage from the vehicle-specific parameters and the plurality of trip features; and

receiving from an on-board diagnostics device information related to a current energy generated by an engine of the vehicle;

determining an estimated fuel usage from the vehicle-specific parameters and the plurality of trip features;

outputting the estimated fuel usage; and

presenting feedback relating driving behaviors of a driver of the trip to the estimated fuel usage for the trip.

17. The mobile computing device of claim 16, further comprising instructions executable by the logic subsystem to obtain the sensor measurements from the on-board diagnostics device and to update a function of the mobile computing device to learn the on-board diagnostics device information based upon the sensor measurements obtained from the on-board diagnostics device.

18. The mobile computing device of claim 16, wherein the on-board diagnostics device information comprises one or more of a fuel injection rate, a vehicular speed, an engine revolutions-per-minute speed, and a torque.

19. The mobile computing device of claim 16, wherein the plurality of trip features comprises one or more of an energy from burning fuel, an energy generated by an engine of the vehicle, a change in kinetic energy, a change in potential energy, an aerodynamic drag, a rolling resistance, and a standby energy.

20. The mobile computing device of claim 16, wherein the instructions executable to present feedback are executable to present comparative feedback comprising the feedback for the driver compared to additional feedback for a second driver, the additional feedback comprising relation of driving behavior of the second driver to a second estimated fuel usage for the second driver.