Vehicle with model-based route energy prediction, correction, and optimization

• US 10,464,547 B2
• Filed: 07/13/2017
• Issued: 11/05/2019
• Est. Priority Date: 07/13/2017
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations LLC (General Motors Company)
• Inventors: Park, David S., Smith, Kevin J., Meehan, Terence L., Lindemann, Todd P., Weinberg, Richard B., Nicholson, James B., Liu, Chia-Hsiang, Zettel, Andrew M., Alonso, Ramon A.
• Primary Examiner(s): Patel, Shardul D
• Application Number:
  US15/648,964
• Publication Number:
  US 20190016329A1
• Time in Patent Office: 845 Days
• Field of Search: 701 22, 903902, 903944, 180 6529
• CPC Class Codes: B60K 6/32 characterised by the fuel cells
• CPC Class Codes: B60K 6/46 Series type
• CPC Class Codes: B60L 15/2045 for optimising the use of energy
• CPC Class Codes: B60L 2210/10 DC to DC converters
• CPC Class Codes: B60L 2210/42 Voltage source inverters
• CPC Class Codes: B60L 2240/12 Speed
• CPC Class Codes: B60L 2240/485 Temperature
• CPC Class Codes: B60L 2240/622 by satellite navigation
• CPC Class Codes: B60L 2240/662 Temperature
• CPC Class Codes: B60L 2240/665 Light intensity
• CPC Class Codes: B60L 2240/667 Precipitation
• CPC Class Codes: B60L 2240/68 Traffic data
• CPC Class Codes: B60L 2250/16 by display
• CPC Class Codes: B60L 2260/26 Transition between different drive modes
• CPC Class Codes: B60L 2260/48 by fuzzy logic
• 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 3/12 Recording operating variables ; Monitoring of operating variables
• CPC Class Codes: B60L 58/12 responding to state of charge [SoC]
• CPC Class Codes: B60W 20/00 Control systems specially adapted for hybrid vehicles hybrid vehicle design, B60K6/00; electric vehicles B60L
• CPC Class Codes: B60W 20/12 : using control strategies taking into account route information estimation or calculation of non-directly measurable driving parameters B60W40/00
• CPC Class Codes: B60W 20/13 : in order to stay within battery power input or output limits; in order to prevent overcharging or battery depletion
• CPC Class Codes: B60W 20/40 : Controlling the engagement or disengagement of prime movers, e.g. for transition between prime movers power-up or power-down of the driveline B60W30/192
• CPC Class Codes: B60W 2050/146 : Display means
• CPC Class Codes: B60W 2510/107 : Temperature
• CPC Class Codes: B60W 2510/244 : Charge state
• CPC Class Codes: B60W 2510/305 : Power absorbed by auxiliaries
• CPC Class Codes: B60W 2520/105 : Longitudinal acceleration
• CPC Class Codes: B60W 2552/00 : Input parameters relating to infrastructure
• CPC Class Codes: B60W 2554/00 : Input parameters relating to objects
• CPC Class Codes: B60W 2555/20 : Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 2555/60 : Traffic rules, e.g. speed limits or right of way
• CPC Class Codes: B60W 2556/45 : External transmission of data to or from the vehicle
• CPC Class Codes: B60W 2556/50 : of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 2710/244 : Charge state
• CPC Class Codes: B60W 50/14 : Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: Y02T 10/62 : Hybrid vehicles
• 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: Y02T 10/84 : Data processing systems or methods, management, administration
• CPC Class Codes: Y02T 90/16 : Information or communication technologies improving the operation of electric vehicles
• CPC Class Codes: Y02T 90/40 : Application of hydrogen technology to transportation, e.g. using fuel cells

Abstract

A vehicle includes drive wheels, an energy source having an available energy, a torque-generating device powered by the energy source to provide an input torque, a transmission configured to receive the input torque and deliver an output torque to the set of drive wheels, and a controller. The controller, as part of a programmed method, predicts consumption of the available energy along a predetermined travel route using onboard data, offboard data, and a first logic block, and also corrects the predicted energy consumption using the onboard data, offboard data, and an error correction loop between a second logic block and the first logic block. The controller also executes a control action with respect to the vehicle using the corrected energy consumption, including changing a logic state of the vehicle.

Claims

1. A vehicle comprising:

a set of drive wheels;

an energy source configured to store available energy;

a torque-generating device powered by the energy source and configured to generate an input torque;

a transmission configured to receive the input torque and deliver an output torque to one or more of the drive wheels to thereby propel the vehicle; and

a controller that is configured, as the vehicle travels along a predetermined travel route, to;

predict, via a first logic block of the controller, an energy consumption of the available energy using onboard data and offboard data, the first logic block predicting the energy consumption including calculating a summation of a propulsion system energy consumption and an auxiliary device energy consumption for the travel route based on the onboard and offboard data;

calculate, via a second logic block of the controller, a correction factor using real-time vehicle data, including actual vehicle speed data and actual auxiliary device load data, and driver technique data, including data indicative of a demonstrated driving behavior of an operator of the vehicle;

determine a corrected energy consumption as a function of the predicted energy consumption and the correction factor using an error correction loop between the second logic block and the first logic block; and

execute a control action with respect to the vehicle using the corrected energy consumption, the control action including changing a logic state of the vehicle.

2. The vehicle of claim 1, wherein the energy source includes an energy storage system (ESS) and the torque-generating device includes an electric machine that is electrically connected to the ESS.

3. The vehicle of claim 1, wherein the energy source includes a supply of combustible fuel and the torque-generating device includes an engine that is powered by combustion of the combustible fuel.

4. The vehicle of claim 1, wherein the energy source includes hydrogen and a hydrogen fuel cell stack, and wherein the torque-generating device includes an electric machine energized via an output current from the hydrogen fuel cell stack.

5. The vehicle of claim 1, further comprising a display screen, wherein changing the logic state includes updating a remaining range of the vehicle with respect to the predetermined travel route using the corrected energy consumption and then displaying the updated remaining range via the display screen.

6. The vehicle of claim 1, wherein the torque-generating device includes an engine and a motor, and the energy source includes an energy storage system (ESS), and wherein changing the logic state includes turning the engine on so as to transition the vehicle from a charge-depleting mode in which the ESS is discharged to a first threshold state of charge (SOC), to a charge-sustaining mode in which the SOC of the ESS is maintained above a second SOC that is higher than the first SOC.

7. The vehicle of claim 6, wherein the controller is further configured to divide the predicted energy consumption along the predetermined travel route into a plurality of power groups having different relative power levels, and to turn the engine on during a highest of the power groups to thereby enter the charge-sustaining mode.

8. The vehicle of claim 1, wherein the offboard data includes elevation data describing an elevation of the predetermined travel route, route speed data describing an estimated speed of the vehicle along the predetermined travel route, environmental data describing an environment of the predetermined travel route, position data describing coordinates of the vehicle, and real-time traffic data describing traffic conditions along the predetermined travel route.

9. The vehicle of claim 8, wherein the energy source includes an energy storage system (ESS), and wherein the onboard data includes a fluid temperature of the transmission, a heating, ventilation, and air conditioning (HVAC) usage data of the vehicle, and a state of charge of the ESS.

10. The vehicle of claim 9, wherein the controller includes a spin loss logic block configured to determine spin losses of the transmission using the fluid temperature, and is configured to predict the energy consumption of the vehicle using the spin losses.

11. The vehicle of claim 8, wherein the environmental data includes one or more of:

wind speed and direction, precipitation, and solar load.

12. The vehicle of claim 1, wherein the controller includes a delta speed logic block operable for calculating a delta speed value indicative of predicted acceleration of the vehicle along the predetermined travel route, and for predicting the energy consumption of the vehicle using the delta speed value.

13. A method for executing control actions of a vehicle having multiple drive wheels and a powertrain, the powertrain including an electric machine that is selectively energized by an energy storage system LESS) to generate motor torque, and a transmission configured to receive the motor torque from the electric machine and deliver output torque to one or more of the drive wheels to propel the vehicle, the method comprising:

receiving offboard and onboard data via a controller;

predicting, via a first logic block of the controller, an energy consumption of the vehicle using the offboard data and the onboard data as the vehicle travels along a predetermined travel route, wherein predicting the energy consumption includes calculating a summation of a propulsion system energy consumption and an auxiliary device energy consumption for the travel route based on the onboard and offboard data;

calculating, via a second logic block of the controller, a correction factor using real-time vehicle data, including actual vehicle speed data and actual auxiliary device load data, and driver technique data, including data indicative of a demonstrated driving behavior of an operator of the vehicle;

determine a corrected energy consumption as a function of the predicted energy consumption and the correction factor using an error correction loop between the second logic block and the first logic block; and

executing a control action with respect to the vehicle via the controller using the corrected energy consumption, the control action including changing a logic state of the vehicle by transmitting output signals to a display screen to thereby display an estimated electric range of the vehicle and/or controlling an operating mode of the powertrain.

14. The method of claim 13, wherein executing the control action includes:

updating an estimated electric range of the vehicle with respect to the predetermined travel route using the corrected energy consumption; and

displaying the updated estimated electric range via the display screen.

15. The method of claim 13, wherein the vehicle further includes an internal combustion engine that selectively powers the electric machine to generate the motor torque, and wherein changing the logic state includes turning the engine on so as to transition the vehicle from a charge-depleting mode, in which the ESS is discharged to a first threshold state of charge (SOC), to a charge-sustaining mode, in which the SOC of the ESS is maintained above a second SOC that is higher than the first SOC.

16. The method of claim 15, further comprising dividing the predicted energy consumption along the predetermined travel route into a plurality of power groups having different relative power levels, and turning the engine on during a highest of the power groups to thereby enter the charge-sustaining mode.

17. The method of claim 13, wherein receiving the offboard data includes receiving elevation data describing an elevation of the predetermined travel route, route speed data describing an estimated speed of the vehicle along the predetermined travel route, environmental data describing an environment of the predetermined travel route, position data describing coordinates of the vehicle, and real-time traffic data describing traffic conditions along the predetermined travel route, the environmental data including one or more of:

wind speed and direction, precipitation, and solar load.

18. The method of claim 17, wherein receiving the onboard data includes receiving a fluid temperature of the transmission, a heating, ventilation, and air conditioning (HVAC) usage data of the vehicle, and a state of charge of the ESS.

19. The method of claim 18, further comprising calculating spin losses of the transmission via a spin loss logic block using the fluid temperature, and predicting the energy consumption of the vehicle using the spin losses.

20. The method of claim 17, further comprising calculating a delta speed value via a delta speed logic block of the controller, the delta speed value being indicative of predicted acceleration of the vehicle along the predetermined travel route, and predicting the energy consumption of the vehicle using the delta speed value.