Method and apparatus for starter motor diagnosis and prognosis using parameter estimation algorithm

• US 8,234,036 B2
• Filed: 04/29/2009
• Issued: 07/31/2012
• Est. Priority Date: 06/16/2008
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations LLC (General Motors Company)
• Inventors: Shin, Kwang-Keun
• Primary Examiner(s): Dunn, David
• Assistant Examiner(s): Allred, David E
• Application Number:
  US12/432,556
• Publication Number:
  US 20090309530A1
• Time in Patent Office: 1,189 Days
• Field of Search: 701/29, 324/765.01, 324/545, 318/490, 322/99
• US Class Current: 701/32.9
• CPC Class Codes: F02N 11/0859 specially adapted to the type of the starter motor or integrated into it
• CPC Class Codes: F02N 11/10 Safety devices F02N11/08 takes precedence
• CPC Class Codes: F02N 11/108 for diagnosis of the starter or its components
• CPC Class Codes: F02N 2300/2006 using prediction of future conditions
• CPC Class Codes: G01R 31/343 in operation

Abstract

A system and method for determining the state of health of a starter motor to notify a vehicle driver of a potential starter motor failure before the failure actually occurs. The starter motor includes an armature and motor brushes each providing a resistance, and an armature coil providing an armature inductance. Further, the starter motor has a back EMF because of the starter motor being coupled to a flywheel and the vehicle engine. The system and method monitor the combined resistance of the armature and the motor brushes, the inductance of the armature and a back EMF constant of the motor, and provide a signal indicating a potential starter motor failure if any of these three values significantly deviates from nominal values. In one embodiment, the analysis of the motor resistance, armature inductance and back EMF constant is provided by a regression model to determine estimated motor parameters.

Claims

1. A method for determining the state of health of a starter motor in a vehicle, said method comprising:

using a current sensor to determine a starter motor current of the starter motor;

using a voltage sensor to determine a starter motor voltage of the starter motor;

providing an engine speed of an engine of the vehicle;

identifying starter motor values that will be used to determine the state of health of the starter motor, wherein the starter motor values are a starter motor resistance that is the combination of a starter motor armature resistance and a starter motor brush resistance, a starter motor armature inductance and a back EMF motor constant;

identifying a time model of the starter motor using the starter motor voltage, the starter motor current, the engine speed and the starter motor values;

defining model parameters from the time model;

providing a regression model based on the time model;

using a controller to determine motor parameters based on the regression model;

using the controller to determine an error using the motor parameters; and

using the controller to compare the error to an error threshold to determine the state of health of the starter motor.

2. The method according to claim 1 wherein identifying a time model of the starter motor includes using the equation:

3. The method according to claim 2 wherein defining model parameters from the time model includes defining model parameters p₁, p₂ and p₃ as:

4. The method according to claim 1 wherein providing a regression model includes using a recursive least squares algorithm with exponential forgetting.

5. The method according to claim 4 wherein the regression model uses the equations:

y(t)=φ

^T(k)θ

where y(k)=I_a(k), φ

^T(k)={I_a(k−

1)V_m(k−

1),−

ω

_E(k−

1)}, y and φ

are regression model values, k is a sample, I_a is the starter motor current, V_m is the starter motor voltage, ω

_E is the engine speed and θ

represents model parameters p₁, p₂ and p₃.

6. The method according to claim 1 wherein providing a regression model includes using a batch least squares algorithm.

7. The method according to claim 6 wherein the regression model uses the equations:

8. The method according to claim 1 wherein the motor parameters R_m, K_m and L_m are defined by the equations:

9. The method according to claim 1 wherein the motor parameters are stored as a temperature in a look-up table.

10. The method according to claim 9 wherein determining an error includes determining an error using the equation:

11. A method for determining the state of health of a starter motor in a vehicle, said method comprising:

using a current sensor to determine a starter motor current of the starter motor;

using a voltage sensor to determine a starter motor voltage of the starter motor;

providing an engine speed of an engine of the vehicle;

identifying a starter motor resistance that is a combination of a starter motor armature resistance and a starter motor brush resistance;

identifying a starter motor armature inductance;

identifying a back EMF motor constant;

identifying a time model of the starter motor using the starter motor voltage, the starter motor current, the engine speed, the starter motor resistance, the starter motor armature inductance and the back EMF motor constant;

defining model parameters from the time model;

providing a regression model based on the time model;

using a controller to determine motor parameters R_m, K_m and L_m as

12. The method according to claim 11 wherein identifying a time model of the starter motor includes using the equation:

13. The method according to claim 11 wherein providing a regression model includes using a recursive least squares algorithm with exponential forgetting.

14. The method according to claim 11 wherein providing a regression model includes using a batch least squares algorithm.

15. A method for determining the state of health of a starter motor in a vehicle, said method comprising:

using sensors to determine a starter motor voltage and a starter motor current of the starter motor;

identifying a time model of the starter motor using a the starter motor voltage, a the starter motor current, an engine speed, a starter motor resistance, a starter motor armature inductance and a back EMF motor constant;

defining model parameters from the time model; and

using the model parameters in a controller to determine an error that is used to determine the state of health of the starter motor.

16. The method according to claim 15 further comprising providing a regression model based on the time model, said regression model being used to convert the model parameters to the error.

17. The method according to claim 16 wherein providing a regression model includes using a recursive least squares algorithm with exponential forgetting.

18. The method according to claim 16 wherein providing a regression model includes using a batch least squares algorithm.

19. The method according to claim 15 wherein identifying a time model of the starter motor includes using the equation:

20. A method for determining the state of health of a starter motor in a vehicle, said method comprising:

using a current sensor to determine a starter motor current of the starter motor;

using a voltage sensor to determine a starter motor voltage of the starter motor;

providing an engine speed of an engine of the vehicle;

identifying starter motor values that will be used to determine the state of health of the starter motor;

identifying a time model of the starter motor using the starter motor voltage, the starter motor current, the engine speed and the starter motor values;

defining model parameters from the time model;

providing a regression model based on the time model;

using a controller to determine motor parameters based on the regression model, wherein the motor parameters are stored as a temperature in a look-up table;

using the controller to determine an error using the motor parameters; and

using the controller to compare the error to an error threshold to determine the state of health of the starter motor.