IP Library › Granted Patent US 12,330,626
Granted Patent B2
US 12,330,626 · App. 17/969,359 · Granted Jun 17, 2025

Hierarchical optimal controller for predictive power split

Inventors: Kamil Dolinsky (Prague, CZ); Matej Pcolka (Prague, CZ)
Assignee: Garrett Transportation I Inc.
B60W20/15B60W10/06B60W10/08B60W10/10B60W20/30B60W2510/0657B60W2510/083B60W2710/0666B60W2710/083B60W2710/1005
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Quick Facts
Patent No.
US 12,330,626
App. No.
17/969,359
Granted
Jun 17, 2025
Kind
B2
Abstract

Methods and systems for hybrid vehicle control. A high-level controller and a low-level controller are provided. The high-level controller uses preview information and a model of the low-level controller to calculate optimized tuning parameters for the low-level controller. The low-level controller uses driver inputs and current operating states to calculate optimized torque split for the hybrid engine.

Claims (71)

1. A control system for a hybrid vehicle, the hybrid vehicle having a first power source that is a battery having a state of charge and a motor configured to provide a first torque, and a second power source configured to provide a second torque, the control system comprising:

a high-level controller having an associated first memory, the first memory storing one or more readable instruction sets for high-level controller tasks;

a low-level controller having an associated second memory, the second memory storing one or more readable instruction sets for low-level controller tasks;

wherein the high-level controller tasks comprise:

receiving preview information related to a travel path for the hybrid vehicle, and one or more current state variables for the hybrid vehicle;

using a model of the low-level controller, one or more models of system dynamics for the hybrid vehicle, and the one or more current state variables,

calculating a fuel consumption over a prediction horizon including a portion of the travel path, and calculating one or more low-level control variables including an equivalence factor for use by the low-level controller, wherein the equivalence factor is a conversion coefficient between fuel energy and electric energy; and

communicating the one or more low-level control variables including the equivalence factor to the low-level controller;

wherein the low-level controller tasks comprise:

receiving the one or more low-level control variables including the equivalence factor from the high-level controller and one or more current state variables for the hybrid vehicle;

calculating, based on the equivalence factor, the first torque and the second torque to provide fuel consumption within minimum and maximum limits for each of the first torque and second torque; and

issuing control signals to the first and second power sources based on the first torque and the second torque to control a power split between the first and second power sources based on the calculated fuel consumption and thereby minimize fuel consumption of the hybrid vehicle.

2. The control system of claim 1 , wherein:

the high-level controller is configured to calculate one or more control values at a first sampling rate;

the low-level controller is configured to calculate the first torque, second torque, and on/off signal at a second sampling rate; and

the second sampling rate is a faster sampling rate than the first sampling rate.

3. The control system of claim 1 , wherein the second power source uses a fuel, and the low-level controller tasks include instructions for determining on/off commands for the second power source.

4. The control system of claim 1 , wherein the hybrid vehicle further includes a transmission configured to receive the first and second torques and use one of at least two selectable gear ratios to deliver power to one or more drive wheels of the hybrid vehicle; wherein:

the low-level controller tasks comprise instructions for calculating a gear ratio request for delivery to the transmission; and

the model of the low-level controller used by the high-level controller includes a model of the low-level controller calculating a gear ratio request.

5. The control system of claim 4 , wherein the instructions for calculating a gear ratio request include:

identifying feasible gear ratios;

calculating wheel torque request to transmission torque request ratios;

finding a torque split for each feasible gear ratio;

calculating a cost for the torque split for each feasible gear ratio; and

selecting a gear ratio from the feasible gear ratios having the least cost.

6. The control system of claim 5 , wherein the instructions for calculating a gear ratio request are configured to calculate the cost for the torque split of each feasible gear ratio as a sum of a fuel power cost, electric power cost, and a change cost.

7. The control system of claim 1 , wherein the high-level controller tasks include:

using the preview information to estimate the hybrid vehicle speed in a prediction window;

combining the hybrid vehicle speed and preview information to estimate combined torque needed in the prediction window;

calculating the fuel consumption that meets the estimated combined torque needed in the prediction window to yield a fuel equivalence factor for the prediction window; and

communicating the fuel equivalence factor for the prediction window to the low-level controller.

8. The control system of claim 7 , wherein the low-level controller tasks include calculating a torque split between first and second power sources using the current state and the fuel equivalence factor.

9. The control system of claim 1 , wherein the high-level controller tasks rely on a driver model to calculate the one or more low-level control variables, and the low-level controller tasks rely on driver control actions to calculate the first torque and the second torque.

10. The control system of claim 1 , wherein the high-level controller tasks use inputs from a navigation system to determine preview information, but not driver control actions, and the low-level controller tasks do not use inputs from the navigation system.

11. A method of controlling a hybrid vehicle powertrain, the hybrid vehicle powertrain having a first power source that is a battery having a state of charge and a motor configured to provide a first torque, and a second power source configured to provide a second torque, the hybrid vehicle powertrain being controlled with each of:

a high-level controller having an associated first memory, the first memory storing one or more readable instruction sets for high-level controller tasks;

a low-level controller having an associated second memory, the second memory storing one or more readable instruction sets for low-level controller tasks

wherein the method comprises the high-level controller:

receiving preview information related to a travel path for the hybrid vehicle, and one or more current state variables for the hybrid vehicle;

using a model of the low-level controller, one or more models of system dynamics for the hybrid vehicle, and the one or more current state variables, calculating a fuel consumption over a prediction horizon including a portion of the travel path, and calculating one or more low-level control variables include an equivalence factor for use by the low-level controller, wherein the equivalence factor is a conversion coefficient between fuel energy and electric energy; and

communicating the one or more low-level control variables including the equivalence factor to the low-level controller;

and the method further comprises the low-level controller:

receiving the one or more low-level control variables including the equivalence factor from the high-level

controller and one or more current state variables for the hybrid vehicle;

calculating, based on the equivalence factor, the first torque and the second torque to provide fuel consumption within minimum and maximum limits for each of the first torque and second torque; and

issuing control signals to the first and second power sources based on the

first torque and the second torque to control a power split between the first and second power sources based on the calculated fuel consumption and thereby minimize fuel consumption of the hybrid vehicle.

12. The method of claim 11 , wherein:

the high-level controller calculates one or more control values at a first sampling rate;

the low-level controller calculates the first torque, second torque, and on/off signal at a second sampling rate; and

the second sampling rate is a faster sampling rate than the first sampling rate.

13. The method of claim 11 , wherein the second power source uses a fuel, and the method includes the low-level controller determining and issuing on/off commands for the second power source.

14. The method of claim 11 , wherein the hybrid vehicle includes a transmission configured to receive the first and second torques and use one of at least two selectable gear ratios to deliver power to one or more drive wheels of the hybrid vehicle; wherein the method further includes:

the low-level controller calculating a gear ratio request for delivery to the transmission and issuing the gear ratio request to the transmission; and

the model of the low-level controller used by the high-level controller includes a model of the low-level controller calculating a gear ratio request.

15. The method of claim 11 , wherein the low-level controller calculates the gear ratio request by:

identifying feasible gear ratios;

calculating wheel torque request to transmission torque request ratios;

finding a torque split for each feasible gear ratio;

calculating a cost for the torque split for each feasible gear ratio; and

selecting a gear ratio from the feasible gear ratios having the least cost.

16. The method of claim 15 , wherein the low-level controller calculates the cost for the torque split of each feasible gear ratio as a sum of a fuel power cost, electric power cost, and a change cost.

17. The method of claim 11 , further comprising the high-level controller:

using the preview information to estimate the hybrid vehicle speed in a prediction window;

combining the hybrid vehicle speed and preview information to estimate combined torque needed in the prediction window;

calculating the fuel consumption that meets the estimated combined torque needed in the prediction window to yield a fuel equivalence factor for the prediction window; and

communicating the fuel equivalence factor for the prediction window to the low-level controller.

18. The method of claim 17 , further comprising the low-level controller calculating a torque split between first and second power sources using the current state and the equivalence factor.

19. The method of claim 11 , further comprising the high-level controller using a driver model to calculate the one or more low-level control variables, and the low-level using actual driver control actions to calculate the first torque and the second torque.

20. The method of claim 11 , further comprising the high-level controller using inputs from a navigation system to determine preview information, but not driver control actions.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 23, 2023
From: DOLINSKY, KAMIL; PCOLKA, MATEJ
To: GARRETT TRANSPORTATION I INC.
Reel/Frame 064683/0050 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 19, 2022
From: DOLINSKY, KAMIL; PCOLKA, MATEJ
To: GARRETT TRANSPORTATION I INC.
Reel/Frame 061473/0565 →
Continuity (2)
Related Publication 20240132048A1 · Apr 25, 2024
Related Publication 20240227775A9 · Jul 11, 2024
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