Method and apparatus for controlling a railway consist

• US 20050065674A1
• Filed: 09/24/2003
• Published: 03/24/2005
• Est. Priority Date: 09/24/2003
• Status: Active Grant

• Current Assignee: GE Global Sourcing LLC (Westinghouse Air Brake Technologies Corporation)
• Original Assignee: General Electric Company
• Inventors: Mathews, Harry Kirk Jr., Shah, Sunil Shirish, Houpt, Paul Kenneth
• Granted Patent: US 7,127,336 B2
• Time in Patent Office: Days
• US Class Current: 701/19
• CPC Class Codes: B61L 15/0058 On-board optimisation of vehicle or vehicle train operation
• CPC Class Codes: B61L 15/0072 On-board train data handling
• CPC Class Codes: B61L 15/0094 Recorders on the vehicle
• CPC Class Codes: B61L 2205/02 Global system for mobile communication - railways [GSM-R]
• CPC Class Codes: B61L 25/00 Recording or indicating positions or identities of vehicles or trains or setting of track apparatus
• CPC Class Codes: B61L 25/021 Measuring and recording of train speed
• CPC Class Codes: B61L 27/20 Trackside control of safe travel of vehicle or train, e.g. braking curve calculation
• CPC Class Codes: B61L 27/40 Handling position reports or trackside vehicle data
• CPC Class Codes: B61L 27/57 for vehicles or trains, e.g. trackside supervision of train conditions
• CPC Class Codes: B61L 3/002 Recorders on the vehicle
• CPC Class Codes: B61L 3/006 On-board optimisation of vehicle or vehicle train operation track-side optimisation of operation B61L27/16

Abstract

An apparatus for controlling a railway consist, the apparatus comprising: a consist model adapted for computing an objective function from a set of candidate driving plans and a set of model parameters; a parameter identifier adapted for calculating the model parameters from a set of consist measurements; and a trajectory optimizer adapted for generating the candidate driving plans and for selecting an optimal driving plan to optimize the objective function subject to a set of terminal constraints and operating constraints.

Claims

1. An apparatus for controlling a railway consist, said apparatus comprising:

a consist model adapted for computing an objective function from a set of candidate driving plans and a set of model parameters;

a parameter identifier adapted for calculating said model parameters from a set of consist measurements; and

a trajectory optimizer adapted for generating said candidate driving plans and for selecting an optimal driving plan to optimize said objective function subject to a set of terminal constraints and operating constraints.

2. The apparatus of claim 1 further comprising a pacing control system adapted for generating a set of throttle commands from said optimal driving plan and said consist measurements.

3. The apparatus of claim 1 further comprising a display module adapted for displaying a formatted driving plan from said optimal driving plan and said consist measurements.

4. The apparatus of claim 1 wherein said parameter identifier comprises an extended Kalman filter.

5. The apparatus of claim 4 wherein:

said extended Kalman filter has an extended filter state vector comprising a consist position estimate, a consist speed estimate, and said model parameters; and

said consist measurements comprise a consist position measurement and a consist speed measurement.

6. The apparatus of claim 1 wherein said parameter identifier comprises:

a Kalman filter adapted for generating a set of filter outputs from said consist measurements; and

a least squares estimator adapted for estimating said model parameters from said filter outputs and said consist measurements.

7. The apparatus of claim 6 wherein:

said Kalman filter has a filter state vector comprising a consist position estimate, a consist speed estimate, and a consist acceleration estimate;

said filter outputs comprise said consist speed estimate and said consist acceleration estimate; and

said consist measurements comprise a consist position measurement, a consist speed measurement, a tractive effort signal, and a track grade signal.

8. The apparatus of claim 1 wherein said objective function is a quantity or linear combination of quantities selected from the group consisting of fuel consumption, travel time, integral squared input rate, and summed squared input difference.

9. An apparatus for controlling a railway consist, said apparatus comprising:

a consist model adapted for computing an objective function from a set of candidate driving plans and a set of model parameters;

a parameter identifier adapted for calculating said model parameters from a set of consist measurements;

a trajectory optimizer adapted for generating said candidate driving plans and for selecting an optimal driving plan to optimize said objective function subject to a set of terminal constraints and operating constraints; and

a display module adapted for displaying a formatted driving plan from said optimal driving plan and said consist measurements,

said objective function being a quantity or linear combination of quantities selected from the group consisting of fuel consumption, travel time, integral squared input rate, and summed squared input difference.

10. The apparatus of claim 9 further comprising a pacing control system adapted for generating a set of throttle commands from said optimal driving plan and said consist measurements.

11. The apparatus of claim 9 wherein said parameter identifier comprises an extended Kalman filter.

12. The apparatus of claim 11 wherein:

said extended Kalman filter has an extended filter state vector comprising a consist position estimate, a consist speed estimate, and said model parameters, and

said consist measurements comprise a consist position measurement and a consist speed measurement.

13. The apparatus of claim 9 wherein said parameter identifier comprises:

a Kalman filter adapted for generating a set of filter outputs from said consist measurements; and

a least squares estimator adapted for estimating said model parameters from said filter outputs and said consist measurements.

14. The apparatus of claim 13 wherein:

said Kalman filter has a filter state vector comprising a consist position estimate, a consist speed estimate, and a consist acceleration estimate;

said filter outputs comprise said consist speed estimate and said consist acceleration estimate, and

said consist measurements comprise a consist position measurement, a consist speed measurement, a tractive effort signal, and a track grade signal.

15. A method for controlling a railway consist, said method comprising:

computing an objective function from a set of candidate driving plans and a set of model parameters;

calculating said model parameters from a set of consist measurements; and

generating said candidate driving plans and selecting an optimal driving plan to optimize said objective function subject to a set of terminal constraints and operating constraints.

16. The method of claim 15 further comprising generating a set of throttle commands from said optimal driving plan and said consist measurements.

17. The method of claim 15 further comprising displaying a formatted driving plan from said optimal driving plan and said consist measurements.

18. The method of claim 15 wherein said act of calculating said model parameters comprises using an extended Kalman filter.

19. The method of claim 18 wherein:

said extended Kalman filter has an extended filter state vector comprising a consist position estimate, a consist speed estimate, and said model parameters; and

said consist measurements comprise a consist position measurement and a consist speed measurement.

20. The method of claim 15 wherein said act of calculating said model parameters comprises:

using a Kalman filter for generating a set of filter outputs from said consist measurements; and

using a least squares estimator for estimating said model parameters from said filter outputs and said consist measurements.

21. The method of claim 20 wherein:

said Kalman filter has a filter state vector comprising a consist position estimate, a consist speed estimate, and a consist acceleration estimate;

said filter outputs comprise said consist speed estimate and said consist acceleration estimate; and

said consist measurements comprise a consist position measurement, a consist speed measurement, a tractive effort signal, and a track grade signal.

22. The method of claim 15 wherein said objective function is a quantity or linear combination of quantities selected from the group consisting of fuel consumption, travel time, integral squared input rate, and summed squared input difference.

23. A method for controlling a railway consist, said method comprising:

computing an objective function from a set of candidate driving plans and a set of model parameters;

calculating said model parameters from a set of consist measurements;

generating said candidate driving plans and selecting an optimal driving plan to optimize said objective function subject to a set of terminal constraints and operating constraints; and

displaying a formatted driving plan from said optimal driving plan and said consist measurements,

said objective function being a quantity or linear combination of quantities selected from the group consisting of fuel consumption, travel time, integral squared input rate, and summed squared input difference.

24. The method of claim 23 further comprising generating a set of throttle commands from said optimal driving plan and said consist measurements.

25. The method of claim 23 wherein said act of calculating said model parameters comprises using an extended Kalman filter.

26. The method of claim 25 wherein:

said extended Kalman filter has an extended filter state vector comprising a consist position estimate, a consist speed estimate, and said model parameters; and

said consist measurements comprise a consist position measurement and a consist speed measurement.

27. The method of claim 23 wherein said act of calculating said model parameters comprises:

using a Kalman filter for generating a set of filter outputs from said consist measurements, and

using a least squares estimator for estimating said model parameters from said filter outputs and said consist measurements.

28. The method of claim 27 wherein:

said Kalman filter has a filter state vector comprising a consist position estimate, a consist speed estimate, and a consist acceleration estimate;

said filter outputs comprise said consist speed estimate and said consist acceleration estimate; and

said consist measurements comprise a consist position measurement, a consist speed measurement, a tractive effort signal, and a track grade signal.