Accurate range calculation for vehicles, computed outside of the vehicle

US9292257B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9292257-B2
Application numberUS-201213612373-A
CountryUS
Kind codeB2
Filing dateSep 12, 2012
Priority dateSep 12, 2012
Publication dateMar 22, 2016
Grant dateMar 22, 2016

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  1. Title

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  2. Abstract

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  5. First independent claim

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Abstract

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Example systems and methods for estimating range for a vehicle are provided. In an example, a server remotely located from a vehicle receives vehicle status information from the vehicle as well as reference data from sources other than the vehicle. An estimated range for the vehicle is computed based on both the vehicle status information and the reference data, and then this estimated range is transmitted to the vehicle.

First claim

Opening claim text (preview).

What is claimed is: 1. A method for providing an estimated operating range for a vehicle, the method comprising: receiving, at a server remotely located from the vehicle, vehicle status data from the vehicle via a communication network; accessing reference data derived from a source other than the vehicle; receiving a map information coefficient from output of a first algorithm at a map server; receiving a crowd-sourced data coefficient from output of a second algorithm at a crowd data server; calculating an estimated range for the vehicle using the vehicle status data and the reference data, the estimated range being a distance available to be traveled by the vehicle before a next fuel stop or recharge is needed; wherein the first and second algorithms being controlled independently from one another and the calculating comprises calculating the following formula: estimated range=maximum available range of vehicle+(map information coefficient+crowd-sourced data coefficient)*maximum available range of vehicle; and sending the estimated range back to the vehicle for display to the driver. 2. The method of claim 1 , wherein the reference data includes information from a driver model. 3. The method of claim 1 , wherein the reference data includes driver-specific data. 4. The method of claim 1 , wherein the reference data includes information about other vehicles and/or drivers. 5. The method of claim 1 , wherein the reference data includes map information. 6. The method of claim 1 , wherein the reference data includes traffic information. 7. The method of claim 1 , wherein the reference data includes weather information. 8. The method of claim 1 , further comprising: receiving a vehicle data coefficient from output of a third algorithm at a car data server; receiving a driver data coefficient from output of a fourth algorithm at a driver data server; receiving a real-time data coefficient from output of a fifth algorithm at a real-time data server; the first, second, third, fourth, and fifth algorithms being controlled independently from one another; the calculating comprising calculating the following formula: estimated range=maximum available range of vehicle+(map information coefficient+vehicle data coefficient+crowd-sourced data coefficient+driver data coefficient+real-time data coefficient)*maximum available range of vehicle. 9. The method of claim 8 , wherein the reference data includes weather information. 10. A cloud server comprising: a processor; memory; an interface to a plurality of range estimation servers, each of the range estimation servers designed to calculate a range for a vehicle for a particular route based on identical vehicle status information received from a vehicle but different reference data for each range estimation server, wherein the reference data comprises a map information coefficient from output of a first algorithm at a map server and a crowd-sourced data coefficient from output of a second algorithm at a crowd data server, the first and second algorithms being controlled independently from one another; an algorithm combination module designed to compute an estimated range for the vehicle based upon a combination of each of the calculated ranges from each of the plurality of range estimation servers, the estimated range being a distance available to be traveled by the vehicle before a next fuel stop or recharge is needed, wherein the computing comprises calculating the following formula: estimated range=maximum available range of vehicle+(map information coefficient+crowd-sourced data coefficient)*maximum available range of vehicle; and a vehicle communication module designed to transmit the estimated range back to the vehicle for display to the driver. 11. The cloud server of claim 10 , wherein at least one of the plurality of range estimation servers bases its calculated range on information received from other vehicles. 12. The cloud server of claim 10 , wherein the estimated range is an estimated range of travel before recharging of the vehicle is necessary. 13. The cloud server of claim 10 , wherein the estimated range is an estimated range of travel before refueling of the vehicle is necessary. 14. The cloud server of claim 10 , wherein the estimated range provided by the algorithm combination module includes a plurality of ranges at different confidence levels. 15. The cloud server of claim 14 , wherein the vehicle is designed to display the plurality of ranges as a heat map. 16. A non-transitory computer-readable storage medium comprising instructions that, when executed by at least one processor of a machine, cause the machine to perform operations comprising: receiving, at a server remotely located from the vehicle, vehicle status data from the vehicle via a communication network; accessing reference data derived from a source other than the vehicle; receiving a map information coefficient from output of a first algorithm at a map server; receiving a crowd-sourced data coefficient from output of a second algorithm at a crowd data server; calculating an estimated range for the vehicle using the vehicle status data and the reference data, the estimated range being a distance available to be traveled by the vehicle before a next fuel stop or recharge is needed; wherein the first and second algorithms being controlled independently from one another and the calculating comprises calculating the following formula: estimated range=maximum available range of vehicle+(map information coefficient+crowd-sourced data coefficient)*maximum available range of vehicle; and sending the estimated range back to the vehicle for display to the driver. 17. The non-transitory computer-readable storage medium of claim 16 , wherein the vehicle status information includes vehicle position. 18. The non-transitory computer-readable storage medium of claim 16 , wherein the vehicle status information includes vehicle speed. 19. The non-transitory computer-readable storage medium of claim 16 , wherein the vehicle status information includes air conditioning status. 20. The non-transitory computer-readable storage medium of claim 16 , wherein the vehicle status information includes tire pressure.

Assignees

Inventors

Classifications

  • G01F9/001Primary

    with electric, electro-mechanic or electronic means (G01F9/008 and G01F9/02 take precedence) · CPC title

  • G06F7/00Primary

    Methods or arrangements for processing data by operating upon the order or content of the data handled (logic circuits H03K19/00) · CPC title

  • with electric, electro-mechanic or electronic means · CPC title

  • communicating information to a remotely located station (transmission systems for measured values G08C) · CPC title

  • Measuring volume flow relative to another variable, e.g. of liquid fuel for an engine · CPC title

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What does patent US9292257B2 cover?
Example systems and methods for estimating range for a vehicle are provided. In an example, a server remotely located from a vehicle receives vehicle status information from the vehicle as well as reference data from sources other than the vehicle. An estimated range for the vehicle is computed based on both the vehicle status information and the reference data, and then this estimated range is…
Who is the assignee on this patent?
Williams Aaron, Long Mary, Paesler Henrik, and 7 more
What technology area does this patent fall under?
Primary CPC classification G01F9/001. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Mar 22 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).