Optimal electric vehicle battery recommendation system

• US 8,791,810 B2
• Filed: 12/28/2012
• Issued: 07/29/2014
• Est. Priority Date: 12/28/2012
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Richter, Jan, STEER, Kent C. B.
• Primary Examiner(s): HUNNINGS, TRAVIS R
• Application Number:
  US13/730,283
• Publication Number:
  US 20140188304A1
• Time in Patent Office: 578 Days
• Field of Search: None
• US Class Current: 340/455
• CPC Class Codes: B60L 2240/12 Speed
• CPC Class Codes: B60L 2240/14 Acceleration
• CPC Class Codes: B60L 2240/545 Temperature
• CPC Class Codes: B60L 2240/547 Voltage
• CPC Class Codes: B60L 2240/549 Current
• CPC Class Codes: B60L 2240/622 by satellite navigation
• CPC Class Codes: B60L 2240/64 Road conditions
• CPC Class Codes: B60L 2240/66 Ambient conditions
• CPC Class Codes: B60L 2250/10 by alarm
• CPC Class Codes: B60L 2250/16 by display
• CPC Class Codes: B60L 2250/18 by enquiring driving style
• CPC Class Codes: B60L 2250/26 by pedal actuation
• CPC Class Codes: B60L 2260/52 drive range estimation, e.g. of estimation of available travel distance
• CPC Class Codes: B60L 2260/54 Energy consumption estimation
• CPC Class Codes: B60L 3/00 Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption methods or circuit arrangements for monitoring or controlling batteries or fuel cells B60L58/00
• CPC Class Codes: B60L 3/12 Recording operating variables ; Monitoring of operating variables
• CPC Class Codes: B60L 58/12 responding to state of charge [SoC]
• CPC Class Codes: Y02T 10/70 Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/72 Electric energy management in electromobility
• CPC Class Codes: Y02T 90/16 Information or communication technologies improving the operation of electric vehicles

Abstract

An optimal vehicle battery recommendation system includes at least one sensor to detect a manipulation of the vehicle. A driver behavior module determines a driving behavior of a driver of the vehicle. A vehicle consumption module determines battery information of an on-board battery currently connected to the vehicle, and determines energy consumption of the vehicle. A battery capacity advisor module is in electrical communication with the driver behavior module and the vehicle consumption module. The battery capacity module determines a replacement battery option that changes at least one battery characteristic of the on-board battery based on the driver behavior model and the vehicle consumption model.

Claims

1. A method of optimizing a battery size of an electric vehicle, comprising:

detecting a manipulation of the vehicle;

determining a driving behavior of a driver of the vehicle based on the manipulation;

determining at least one battery characteristic among a set of battery characteristics of an on-board battery currently connected to the vehicle;

determining energy consumption of the vehicle; and

determining a replacement battery option that changes the at least one battery characteristic based on the driver behavior and the vehicle consumption model.

2. The method of claim 1, wherein the determining a replacement battery option includes at least one of determining a replacement battery to replace the on-board battery and determining a modification of battery layers of the on-board battery, the set of battery characteristics comprising energy storage capacity, specific energy, weight, size, charging and discharging properties and temperature dependence of the on-board battery.

3. The method of claim 2, wherein the at least one of a replacement battery and a modification of battery layers increases the first specific energy.

4. The method of claim 3, further comprising:

determining dynamic vehicle data in response to real time manipulation of the vehicle by the driver;

storing the dynamic vehicle data; and

generating a numerical model indicating a driving behavior of the driver and at least one driving preference of the driver.

5. The method of claim 4, wherein the dynamic vehicle data includes vehicle speed, vehicle acceleration, vehicle breaking, driving distance, and driving duration.

6. The method of claim 5, wherein the energy consumption model is based on predetermined specifications of the vehicle and the dynamic vehicle data.

7. The method of claim 6, further comprising determining at least one safety condition of the vehicle, the at least one safety condition including a distance between the vehicle and a nearest recharging station.

8. The method of claim 7, receiving at least one driver input and outputting at east one alert indicating the replacement battery option.

9. The method of claim 8, further comprising determining the replacement battery based on an input from the drover.

10. The method of claim 9, wherein the alert includes at least one of a sound, text describing the replacement battery option, and an image of the replacement battery option.

11. The method of claim 8, further comprising wirelessly communicating the replacement battery option with a terminal device, the terminal device including at least one of a cell phone, a personal computer, a laptop computer and a tablet computer.

12. The method of claim 11, further comprising receiving a driver profile input from the user interface and determining the replacement battery option based on the driver profile.

13. A method of optimizing an on-board battery of a vehicle, comprising:

receiving at least one driver profile corresponding to a driver of the vehicle;

determining dynamic vehicle data in response to operation of the vehicle according to the driver;

storing the dynamic vehicle data corresponding to the driver profile;

determining energy consumption of the vehicle; and

determining a replacement battery option that modifies at least one battery characteristic among a set of battery characteristics of the on-board battery based on the dynamic vehicle data of the input driver profile and the energy consumption of the vehicle.

14. The method of claim 13, wherein the battery capacity module determines the replacement battery in response to inputting the current driver profile among a plurality of driver profiles stored by the driver behavior module.

15. The method of claim 14, wherein the determining a replacement battery option includes at least one of determining a replacement battery to replace the on-board battery and determining a modification of battery layers of the on-board battery, the set of battery characteristics comprising energy storage capacity, specific energy, weight, size, charging and discharging properties and temperature dependence of the on-board battery.

16. The method of claim 15, wherein the at least one of a replacement battery and a modification of battery layers increases a specific energy realized by the vehicle.

17. The method of claim 16, wherein the driver behavior module comprises:

Determining dynamic vehicle data in response to real time manipulation of the vehicle by the driver; and

generating a numerical model of the driving behavior corresponding to the current driver profile.

18. The method of claim 17, further comprising storing a previous driver profile generated according to a previous driving event, and updating the previous driver profile based on a new driving event.