Efficient dual source battery pack system for an electric vehicle

• US 8,543,270 B2
• Filed: 12/10/2010
• Issued: 09/24/2013
• Est. Priority Date: 08/10/2010
• Status: Active Grant

• Current Assignee: Tesla Inc.
• Original Assignee: Tesla Motors Incorporated (Tesla Inc.)
• Inventors: Kelty, Kurt Russell, Mehta, Vineet Haresh, Straubel, Jeffrey Brian
• Primary Examiner(s): BEHNCKE, CHRISTINE M
• Application Number:
  US12/964,767
• Publication Number:
  US 20120041625A1
• Time in Patent Office: 1,019 Days
• Field of Search: 701/22, 701/99, 180/65.1, 180/65.29, 180/65.265, 180/65.8, 903/903, 903/907, 320/125, 320/135, 320/136
• US Class Current: 701/22
• CPC Class Codes: B60L 15/2045 for optimising the use of energy
• 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 58/20 having different nominal voltages
• CPC Class Codes: H01M 10/48 Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte constructional details of current conducting connections for detecting conditions inside cells or batteries, e.g. details of voltage sensing terminals, H01M50/569
• CPC Class Codes: H01M 12/06 with one metallic and one gaseous electrode
• CPC Class Codes: H01M 16/00 Structural combinations of different types of electrochemical generators
• CPC Class Codes: H01M 2220/20 Batteries in motive systems, e.g. vehicle, ship, plane
• CPC Class Codes: Y02E 60/10 Energy storage using batteries
• CPC Class Codes: Y02T 10/64 Electric machine technologies in electromobility
• 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: Y10S 903/903 having energy storing means, e.g. battery, capacitor
• CPC Class Codes: Y10S 903/907 Electricity storage, e.g. battery, capacitor

Abstract

A method of optimizing the operation of the power source of an electric vehicle is provided, where the power source is comprised of a first battery pack (e.g., a non-metal-air battery pack) and a second battery pack (e.g., a metal-air battery pack). The power source is optimized to minimize use of the least efficient battery pack (e.g., the second battery pack) while ensuring that the electric vehicle has sufficient power to traverse the expected travel distance before the next battery charging cycle.

Claims

1. A method of optimizing a power source utilized by an electric vehicle, the power source including at least a first battery pack and a second battery pack, wherein the first and second battery packs are comprised of different battery types, the method comprising the steps of:

a) determining a first state-of-charge (SOC) of the first battery pack and a second SOC of the second battery pack;

b) determining a vehicle efficiency, wherein said vehicle efficiency corresponds to an estimated efficiency for converting an output from said power source to miles traveled;

c) obtaining a travel distance, wherein said travel distance corresponds to an expected distance to travel before a subsequent charging cycle;

d) determining an optimal split between said first and second battery packs based on said vehicle efficiency and said first and second SOCs, wherein said step of determining said optimal split further comprises the step of minimizing use of said second battery pack while still providing the electric vehicle with sufficient power to traverse said travel distance;

e) providing power to said electric vehicle from said power source in accordance with said optimal split;

f) monitoring a first battery pack current SOC and a second battery pack current SOC;

g) comparing said first battery pack current SOC to a first battery pack predicted use profile and said second battery pack current SOC to a second battery pack predicted use profile;

h) determining a revised optimal split between said first and second battery packs to reach said travel distance if said first battery pack current SOC does not match said first battery pack predicted use profile within a first preset tolerance or said second battery pack current SOC does not match said second battery pack predicted use profile within a second preset tolerance, wherein said step of determining said revised optimal split further comprises the step of updating said vehicle efficiency and said travel distance; and

i) providing power to said electric vehicle from said power source in accordance with said revised optimal split.

2. The method of claim 1, wherein said first battery pack is comprised of a plurality of non-metal-air cells and said second battery pack is comprised of a plurality of metal-air cells.

3. The method of claim 1, wherein said step of determining said optimal split further comprises the step of maintaining a minimum SOC within said first battery pack.

4. The method of claim 1, wherein said step of determining said optimal split further comprises the step of maximizing power source efficiency.

5. The method of claim 1, wherein prior to performing step h), said method further comprises the steps of monitoring traffic conditions and adjusting said vehicle efficiency based on said traffic conditions.

6. The method of claim 1, further comprising the step of determining first battery pack operational parameters and second battery pack operational parameters prior to performing step d).

7. The method of claim 1, wherein said vehicle efficiency is defined as an average conversion efficiency for said electric vehicle.

8. The method of claim 1, wherein said vehicle efficiency is given as a function of vehicle speed and vehicle acceleration.

9. The method of claim 1, wherein said vehicle efficiency corresponds to a particular driver, wherein said particular driver is currently operating said electric vehicle.

10. The method of claim 1, wherein said travel distance corresponds to a preset distance, said preset distance corresponding to an average distance traveled between charge cycles for said electric vehicle.

11. The method of claim 1, wherein said step of obtaining said travel distance further comprises the step of determining said travel distance from a destination input into a navigation system corresponding to said electric vehicle.

12. The method of claim 1, wherein said step of obtaining said travel distance further comprises the step of determining said travel distance from a travel itinerary input into a navigation system corresponding to said electric vehicle.

13. The method of claim 12, wherein prior to performing step d), said method further comprises the steps of estimating variations in vehicle elevation expected by said travel itinerary and adjusting said vehicle efficiency based on said variations in vehicle elevation.

14. The method of claim 12, wherein prior to performing step d), said method further comprises the steps of estimating traffic conditions expected by said travel itinerary and adjusting said vehicle efficiency based on said traffic conditions.

15. The method of claim 1, wherein said step of obtaining said travel distance further comprises the step of inputting said travel distance into a user interface corresponding to said electric vehicle.

16. The method of claim 1, wherein prior to performing step d), said method further comprises the steps of determining ambient temperature, estimating first and second battery pack cooling demands based on said ambient temperature, and adjusting said vehicle efficiency based on said first and second battery pack cooling demands.

17. The method of claim 1, wherein prior to performing step d), said method further comprises the steps of estimating vehicle weight and adjusting said vehicle efficiency based on said vehicle weight.

18. The method of claim 1, wherein prior to performing step d), said method further comprises the steps of determining ambient lighting conditions, estimating driving light requirements based on said ambient lighting conditions, estimating first and second battery pack loading to meet said driving light requirements, and adjusting said vehicle efficiency based on said first and second battery pack loading.

19. The method of claim 1, wherein prior to performing step d), said method further comprises the steps of determining weather conditions and adjusting said vehicle efficiency based on said weather conditions.

20. The method of claim 1, wherein prior to performing step d), said method further comprises the steps of identifying a driver for said electric vehicle, estimating auxiliary battery pack loading corresponding to said driver based on prior use of said electric vehicle by said driver, and adjusting said vehicle efficiency based on said estimated auxiliary battery pack loading.

21. A method of optimizing a power source utilized by an electric vehicle, the power source including at least a first battery pack and a second battery pack, wherein the first and second battery packs are comprised of different battery types, the method comprising the steps of:

a) determining a first state-of-charge (SOC) of the first battery pack and a second SOC of the second battery pack;

b) determining a vehicle efficiency, wherein said vehicle efficiency corresponds to an estimated efficiency for converting an output from said power source to miles traveled;

c) obtaining a travel distance, wherein said travel distance corresponds to an expected distance to travel before a subsequent charging cycle;

d) determining an optimal split between said first and second battery packs based on said vehicle efficiency and said first and second SOCs, wherein said step of determining said optimal split further comprises the step of minimizing use of said second battery pack while still providing the electric vehicle with sufficient power to traverse said travel distance;

e) providing power to said electric vehicle from said power source in accordance with said optimal split;

f) monitoring a first battery pack current SOC and a second battery pack current SOC;

g) determining a first battery pack remaining SOC and a second battery pack remaining SOC;

h) comparing said first battery pack remaining SOC to a first battery pack predicted use profile and said second battery pack remaining SOC to a second battery pack predicted use profile;

i) determining a revised optimal split between said first and second battery packs to reach said travel distance if said first battery pack remaining SOC does not match said first battery pack predicted use profile within a first preset tolerance or said second battery pack remaining SOC does not match said second battery pack predicted use profile within a second preset tolerance, wherein said step of determining said revised optimal split further comprises the step of updating said vehicle efficiency and said travel distance; and

j) providing power to said electric vehicle from said power source in accordance with said revised optimal split.

22. The method of claim 21, wherein prior to performing step i), said method further comprises the steps of monitoring traffic conditions and adjusting said vehicle efficiency based on said traffic conditions.

23. The method of claim 21, wherein said first battery pack is comprised of a plurality of non-metal-air cells and said second battery pack is comprised of a plurality of metal-air cells.

24. The method of claim 21, wherein said step of determining said optimal split further comprises the step of maintaining a minimum SOC within said first battery pack.

25. The method of claim 21, wherein said step of determining said optimal split further comprises the step of maximizing power source efficiency.

26. The method of claim 21, further comprising the step of determining first battery pack operational parameters and second battery pack operational parameters prior to performing step d).

27. The method of claim 21, wherein said vehicle efficiency is defined as an average conversion efficiency for said electric vehicle.

28. The method of claim 21, wherein said vehicle efficiency is given as a function of vehicle speed and vehicle acceleration.

29. The method of claim 21, wherein said vehicle efficiency corresponds to a particular driver, wherein said particular driver is currently operating said electric vehicle.

30. The method of claim 21, wherein said travel distance corresponds to a preset distance, said preset distance corresponding to an average distance traveled between charge cycles for said electric vehicle.

31. The method of claim 21, wherein said step of obtaining said travel distance further comprises the step of determining said travel distance from a destination input into a navigation system corresponding to said electric vehicle.

32. The method of claim 21, wherein said step of obtaining said travel distance further comprises the step of determining said travel distance from a travel itinerary input into a navigation system corresponding to said electric vehicle.

33. The method of claim 32, wherein prior to performing step d), said method further comprises the steps of estimating variations in vehicle elevation expected by said travel itinerary and adjusting said vehicle efficiency based on said variations in vehicle elevation.

34. The method of claim 32, wherein prior to performing step d), said method further comprises the steps of estimating traffic conditions expected by said travel itinerary and adjusting said vehicle efficiency based on said traffic conditions.

35. The method of claim 21, wherein said step of obtaining said travel distance further comprises the step of inputting said travel distance into a user interface corresponding to said electric vehicle.

36. The method of claim 21, wherein prior to performing step d), said method further comprises the steps of determining ambient temperature, estimating first and second battery pack cooling demands based on said ambient temperature, and adjusting said vehicle efficiency based on said first and second battery pack cooling demands.

37. The method of claim 21, wherein prior to performing step d), said method further comprises the steps of estimating vehicle weight and adjusting said vehicle efficiency based on said vehicle weight.

38. The method of claim 21, wherein prior to performing step d), said method further comprises the steps of determining ambient lighting conditions, estimating driving light requirements based on said ambient lighting conditions, estimating first and second battery pack loading to meet said driving light requirements, and adjusting said vehicle efficiency based on said first and second battery pack loading.

39. The method of claim 21, wherein prior to performing step d), said method further comprises the steps of determining weather conditions and adjusting said vehicle efficiency based on said weather conditions.

40. The method of claim 21, wherein prior to performing step d), said method further comprises the steps of identifying a driver for said electric vehicle, estimating auxiliary battery pack loading corresponding to said driver based on prior use of said electric vehicle by said driver, and adjusting said vehicle efficiency based on said estimated auxiliary battery pack loading.