Real time trajectory optimization for hybrid energy management utilizing connected information technologies

Patent metadata

Field	Value
Publication number	US-11117567-B2
Application number	US-201816019512-A
Country	US
Kind code	B2
Filing date	Jun 26, 2018
Priority date	Jun 26, 2018
Publication date	Sep 14, 2021
Grant date	Sep 14, 2021

Abstract

The disclosure is directed to solving a full trajectory optimization problem in real-time for a hybrid electric vehicle (HEV) such that future driving conditions and energy usage may be fully considered in determining optimal engine energy usage and battery energy usage in real-time during a trip. An electronic control unit of the HEV may be configured to: receive route information for a route to be driven by the HEV; and after receiving the route information, iterating the operations of: measuring a current state of charge (SOC) of the battery; using at least the measured SOC and an initial co-state value stored in a memory, performing a process to iteratively update the co-state value to obtain an updated co-state value; using at least the updated co-state value, computing an updated control value; and applying the updated control value to control a usage of the battery and the internal combustion engine.

First claim

What is claimed is:

1. A hybrid electric vehicle, comprising:
an internal combustion engine;
a battery;
an electric motor operatively coupled to the battery; and
an electronic control unit to:
receive route information for a route to be driven by the hybrid electric vehicle; and
after receiving the route information, iterating operations of:
measuring a current state of charge (SOC) of the battery;
using at least the measured SOC and an initial co-state value stored in a memory, performing a process to iteratively update the initial co-state value to obtain an updated co-state value;
using at least the updated co-state value, computing an updated control value; and
applying the updated control value to control a usage of the battery and the internal combustion engine.

2. The hybrid electric vehicle of claim 1 , wherein performing the process to iteratively update the co-state value to obtain the updated co-state value, comprises further iteratively performing operations of:
using at least a current SOC, a current co-state value stored in a memory, and a control value stored in a memory, selecting a new control value;
storing the new control value in a memory;
using at least the current SOC and the new control value stored in memory, calculating a SOC one time step ahead in the future;
using at least the current SOC the new control value stored in memory, and a current co-state value, calculating a co-state value one time step ahead in the future; and
setting the one time step ahead SOC and the one time step ahead co-state values as a current SOC and a current co-state value.

3. The hybrid electric vehicle of claim 2 , wherein selecting the new control value comprises lowering a cost function of fuel consumption and battery SOC times the current co-state value.

4. The hybrid electric vehicle of claim 3 , wherein performing the process to iteratively update the co-state value to obtain the updated co-state value, comprises: after iteratively performing the operations of selecting, storing, calculating, calculating, and setting, further performing operations of:
computing a difference between the current SOC with a minimum battery SOC;
choosing a new co-state initial value to reduce the difference; and
replacing the co-state initial value stored in a memory with the new co-state initial value.

5. The hybrid electric vehicle of claim 2 wherein the operations of selecting, storing, calculating, calculating, and setting are iterated until the one time step ahead in the future reaches the expected end of the trip.

6. The hybrid electric vehicle of claim 1 , wherein computing an updated control value comprises using at least the measured SOC and updated co-state value to compute a control value that minimizes a sum of a current fuel consumption rate and a rate-of-change of battery SOC times the updated co-state value.

7. The hybrid electric vehicle of claim 1 , wherein the updated control value is to update the engine speed and the engine torque.

8. The hybrid electric vehicle of claim 7 , wherein the electronic control unit is to measure a velocity and power demand each time the SOC of the battery is measured.

9. The hybrid electric vehicle of claim 8 , wherein the electronic control unit is to measure traffic conditions prior to each time the co-state value is updated, wherein at least the measured current SOC, the initial co-state value stored in the memory, the measured velocity, the measured power demand, and the measured traffic conditions are used to update the co-state value.

10. A non-transitory computer-readable medium having executable instructions stored thereon that, when executed by a processor, cause the processor to perform operations of:
receiving route information for a route to be driven by a hybrid electric vehicle; and
after receiving the route information, further iterating operations of:
measuring a current state of charge (SOC) of a battery of the hybrid electric vehicle;
using at least the measured SOC and an initial co-state value stored in a memory, performing a process to iteratively update the initial co-state value to obtain an updated co-state value;
using at least the updated co-state value, computing an updated control value; and
applying the updated control value to control a usage of the battery and an internal combustion engine of the hybrid electric vehicle.

11. The non-transitory computer-readable medium of claim 10 , wherein performing the process to iteratively update the co-state value to obtain the updated co-state value, comprises further iteratively performing operations of:
using at least a current SOC, a current co-state value stored in a memory, and a control value stored in a memory, selecting a new control value;
storing the new control value in a memory;
using at least the current SOC and the new control value stored in memory, calculating a SOC one time step ahead in the future;
using at least the current SOC the new control value stored in memory, and a current co-state value, calculating a co-state value one time step ahead in the future; and
setting the one time step ahead SOC and the one time step ahead co-state values as a current SOC and a current co-state value.

12. The non-transitory computer-readable medium of claim 11 , wherein selecting the new control value comprises lowering a cost function of fuel consumption and battery SOC times the current co-state value.

13. The non-transitory computer-readable medium of claim 12 , wherein performing the process to iteratively update the co-state value to obtain the updated co-state value, comprises: after iteratively performing the operations of selecting, storing, calculating, calculating, and setting, further performing operations of:
computing a difference between the current SOC with a minimum battery SOC;
choosing a new co-state initial value to reduce the difference; and
replacing the co-state initial value stored in a memory with the new co-state initial value.

14. The non-transitory computer-readable medium of claim 11 , wherein the operations of selecting, storing, calculating, calculating, and setting are iterated until the one time step ahead in the future reaches the expected end of the trip.

15. The non-transitory computer-readable medium of claim 10 , wherein computing an updated control value comprises using at least the measured SOC and updated co-state value to compute a control value that minimizes a sum of a current fuel consumption rate and a rate-of-change of battery SOC times the updated co-state value.

16. The non-transitory computer-readable medium of claim 10 , wherein the updated control value is to update the engine speed and the engine torque.

17. The non-transitory computer-readable medium of claim 16 , wherein the instructions when executed by the processor, cause the processor to further perform an operation of: measuring a velocity and power demand each time the SOC of the battery is measured.

18. The non-transitory computer-readable medium of claim 17 , wherein the instructions when executed by the processor, cause the processor to further perform an operation of: measuring traffic conditions prior to each time the co-state value is updated, wherein at least the measured current SOC, the initial co-state value stored in the memory, the measured velocity, the measured power demand, and the measured traffic conditions are used to update the co-state value.

19. A method, comprising:
receiving route information for a route to be driven by a hybrid electric vehicle; and

Assignees

• Toyota Eng & Mfg North America
• Univ Michigan Regents

Inventors

• Huang Mike X
• Shibaike Yushi
• Zhang Shengqi
• Chen Di
• Stefanopoulou Anna G

Classifications

• B60W2710/0666

  Engine torque · CPC title

• B60W2710/0644

  Engine speed · CPC title

• B60W50/0097

  Predicting future conditions · CPC title

• B60W20/11

  using model predictive control [MPC] strategies, i.e. control methods based on models predicting performance {(utilising navigation and traffic information in the control strategy B60W20/12)} · CPC title

• B60W2050/0088

  Adaptive recalibration · CPC title