Method and apparatus for analyzing data related to vehicle range estimation

Patent metadata

Field	Value
Publication number	US-2016114698-A1
Application number	US-201514924566-A
Country	US
Kind code	A1
Filing date	Oct 27, 2015
Priority date	Oct 28, 2014
Publication date	Apr 28, 2016
Grant date	—

Abstract

A method of analyzing data related to a driving range estimation of a vehicle includes collecting attribute data related to the driving range estimation of the vehicle, analyzing a correlation between the attribute data and a driving range of the vehicle, generating a vehicle driving range estimation model based on the analyzed correlation, and analyzing a sensitivity between the vehicle driving range estimation model and the attribute data.

First claim

What is claimed is:

1 . A method of analyzing data related to a driving range estimation of a vehicle, the method comprising:
collecting attribute data related to the driving range estimation of the vehicle; analyzing a correlation between the attribute data and a driving range of the vehicle; generating a vehicle driving range estimation model based on the analyzed correlation; and analyzing a sensitivity between the vehicle driving range estimation model and the attribute data.

2 . The method of claim 1 , wherein the analyzing of the correlation comprises:
classifying the attribute data into a predefined category based on statistical data in response to the attribute data being non-deterministic data that varies as the vehicle is driven; and analyzing a correlation between the category and the driving range of the vehicle.

3 . The method of claim 1 , wherein the attribute data comprises any one or any combination of any two or more of standard data that is deterministic data that does not vary as the vehicle is driven, historical data based on a previous probabilistic behavior of a driver, and real-time data related to current driving data of the vehicle.

4 . The method of claim 1 , further comprising feeding back the analyzed sensitivity;
wherein the collecting of the attribute data comprises adjusting a frequency and a resolution for collecting the attribute data based on the fed-back sensitivity.

5 . The method of claim 4 , wherein the generating of the vehicle driving range estimation model comprises modifying the vehicle driving range estimation model based on the fed-back sensitivity.

6 . The method of claim 1 , wherein the generating of the vehicle driving range estimation model comprises:
generating the vehicle driving range estimation model by applying deterministic data that does not vary as the vehicle is driven as a coefficient of the vehicle driving range estimation model; and applying an influence of non-deterministic data on the vehicle driving range estimation model, the non-deterministic data varying as the vehicle is driven.

7 . The method of claim 6 , wherein the deterministic data comprises any one or any combination of any two or more of a drag coefficient of the vehicle, a front area of the vehicle, and battery charge data.

8 . The method of claim 6 , wherein the non-deterministic data comprises any one or any combination of any two or more of a speed of the vehicle, an acceleration of the vehicle, weather data, and a driving route.

9 . The method of claim 1 , wherein the analyzing of the sensitivity comprises calculating an estimation error occurring in estimating the driving range of the vehicle in response to the attribute data being insufficient for the vehicle driving range estimation model.

10 . The method of claim 1 , further comprising generating a power profile of the vehicle corresponding to route data using the vehicle driving range estimation model.

11 . The method of claim 10 , further comprising estimating remaining battery charge data by applying the power profile to a battery model of the vehicle.

12 . An apparatus for analyzing data related to a driving range estimation of a vehicle, the apparatus comprising:
a data collector configured to collect attribute data related to the driving range estimation of the vehicle; a correlation analyzer configured to analyze a correlation between the attribute data and a driving range of the vehicle; a model generator configured to generate a vehicle driving range estimation model based on the analyzed correlation; and a sensitivity analyzer configured to analyze a sensitivity between the vehicle driving range estimation model and the attribute data.

13 . The apparatus of claim 12 , wherein the correlation analyzer is further configured to classify the attribute data into a predefined category based on statistical data in response to the attribute data being non-deterministic data that varies as the vehicle is driven, and analyze a correlation between the category and the driving range of the vehicle.

14 . The apparatus of claim 12 , wherein the attribute data comprises any one or any combination of any two or more of standard data that is deterministic data that does not vary as the vehicle is driven, historical data based on a previous probabilistic behavior of a driver, and real-time data related to current driving data of the vehicle.

15 . The apparatus of claim 12 , wherein the sensitivity analyzer is further configured to feed back the analyzed sensitivity; and
the data collector is further configured to adjust a frequency and a resolution for collecting the attribute data based on the fed-back sensitivity.

16 . The apparatus of claim 15 , wherein the model generator is further configured to modify the vehicle driving range estimation model based on the fed-back sensitivity.

17 . The apparatus of claim 12 , wherein the model generator is further configured to generate the vehicle driving range estimation model by applying deterministic data that does not vary as the vehicle is driven as a coefficient of the vehicle driving range estimation model, and apply an influence of non-deterministic data on the vehicle driving range estimation model, the non-deterministic data varying as the vehicle is driven.

18 . The apparatus of claim 12 , wherein the sensitivity analyzer is further configured to calculate an estimation error occurring in estimating the driving range of the vehicle in response to the attribute data being insufficient for the vehicle driving range estimation model.

19 . The apparatus of claim 12 , further comprising a power profile generator configured to generate a power profile of the vehicle corresponding to route data using the vehicle driving range estimation model.

20 . The apparatus of claim 19 , further comprising a battery simulator configured to estimate remaining battery charge data by applying the power profile to a battery model of the vehicle.

21 . An apparatus for estimating a driving range of a vehicle, the apparatus comprising:
a model generator configured to generate a vehicle driving range estimation model based on attribute data affecting the driving range of the vehicle; a sensitivity analyzer configured to analyze a sensitivity between the vehicle driving range estimation model and the attribute data, and modify the vehicle driving range estimation model based on the sensitivity; and a battery simulator configured to estimate a remaining charge of a battery of the vehicle based on the vehicle driving range estimation model and the attribute data, the remaining charge being indicative of the driving range of the vehicle.

22 . The apparatus of claim 21 , wherein the sensitivity analyzer is further configured to modify the vehicle driving range estimation model to have a relatively greater sensitivity to attribute data having a relatively greater effect on the driving range of the vehicle among all of the attribute data, and to have a relatively lesser sensitivity to attribute data have a relatively lesser effect on the driving range of the vehicle among all of the attribute data.

23 . The apparatus of claim 21 , further comprising a correlation analyzer configured to analyze a correlation between the attribute data and the driving range of the vehicle; and
the model generator is further configured to generate the vehicle driving range estimation model based on the analyzed correlation.

Assignees

• Samsung Electronics Co Ltd
• Univ North Carolina State

Inventors

• Chow Mo-Yuen
• Jeon Paul Barom
• Rahimi Eichi Habiballah
• Yeo Taejung

Classifications

• B60L11/1861 Primary

  Operations & Transport · mapped topic

• B60L3/12 Primary

  Recording operating variables {; Monitoring of operating variables} · CPC title

• B60L58/12 Primary

  responding to state of charge [SoC] · CPC title

• Y02T10/72

  Electric energy management in electromobility · CPC title

• Y02T10/70

  Energy storage systems for electromobility, e.g. batteries · CPC title