METHOD OF MONITORING SOOT MASS IN A PARTICULATE FILTER AND MONITORING SYSTEM FOR SAME

• US 20120000184A1
• Filed: 07/02/2010
• Published: 01/05/2012
• Est. Priority Date: 07/02/2010
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations Incorporated (Motors Liquidation Co. GUC Trust)
• Inventors: Li, Jianwen, Ardanese, Michelangelo, Ardanese, Raffaello
• Granted Patent: US 8,365,586 B2
• Time in Patent Office: Days
• US Class Current: 60/274
• CPC Class Codes: F01N 11/002 the diagnostic devices measuring or estimating temperature or pressure in, or downstream of the exhaust apparatus
• CPC Class Codes: F01N 2560/026 for measuring or detecting NOx
• CPC Class Codes: F01N 2560/06 the means being a temperature sensor
• CPC Class Codes: F01N 2560/08 the means being a pressure sensor
• CPC Class Codes: F02D 2200/0812 Particle filter loading
• CPC Class Codes: Y02T 10/40 Engine management systems

Abstract

A method of monitoring soot mass in a particulate filter of an exhaust system includes predicting soot mass in the particulate filter based at least partially on a pressure differential between exhaust flowing into the filter and exhaust flowing out of the filter. The predicted soot mass is then revised based at least partially on measured operating parameters indicative of mass flow rate of nitrogen oxides in exhaust flow of the exhaust system and temperature of the particulate filter.

Claims

1. A method of monitoring soot mass in a particulate filter of an exhaust system comprising:

predicting soot mass in the particulate filter based at least partially on a pressure differential between exhaust flowing into the filter and exhaust flowing out of the filter; and

revising the predicted soot mass based at least partially on measured operating parameters indicative of mass flow rate of nitrogen oxides in exhaust flow of the exhaust system and temperature of the particulate filter.

2. The method of claim 1, wherein the revising includes:

estimating a deviation between the predicted soot mass and actual soot mass in the filter by fitting the measured operating parameters and the predicted soot mass to a stored database of deviations between predicted soot mass and actual soot mass measured over multiple respective soot loading cycles of at least one particulate filter substantially identical to the particulate filter, with each deviation in the stored database being for a respective average modeled filter temperature and a respective average measured mass flow rate of nitrogen oxides in a respective one of the soot loading cycles.

3. The method of claim 2, further comprising:

repeating the measuring the operating parameters, the predicting soot mass, and the revising the predicted soot mass at predetermined time intervals; and

indicating a filter regeneration recommendation when the revised predicted soot mass reaches a predetermined value.

4. The method of claim 1, wherein the operating parameter indicative of mass flow rate of nitrogen oxides is measured using a nitrogen oxide sensor positioned at least partially in the exhaust flow upstream of the particulate filter.

5. The method of claim 1, wherein the operating parameter indicative of temperature of the particulate filter is measured using a temperature sensor positioned in fluid communication with the exhaust flow.

6. The method of claim 1, wherein the pressure differential is measured using a differential pressure sensor positioned in fluid communication with an inlet of the particulate filter and with an outlet of the particulate filter.

7. The method of claim 1, wherein the pressure differential is based on a pressure measured upstream of the particulate filter and a modeled pressure downstream of the particulate filter.

8. A method of monitoring soot mass in a particulate filter of an exhaust system comprising:

measuring a first operating parameter indicative of mass flow rate of nitrogen oxides in exhaust flow of the exhaust system;

measuring a second operating parameter indicative of temperature of the particulate filter;

predicting soot mass in the particulate filter based at least in part on a third operating parameter indicative of a pressure difference between pressure of exhaust flow entering the particulate filter and pressure of exhaust flow exiting the particulate filter;

estimating a deviation between the predicted soot mass and actual soot mass in the filter by fitting the measured first operating parameter, the measured second operating parameter and the predicted soot mass to a stored database of deviations between predicted soot mass and actual soot mass measured over multiple respective soot loading cycles of at least one filter that is substantially identical to the particulate filter, each of the deviations stored in the database being for a respective average modeled filter temperature and a respective average measured mass flow rate of nitrogen oxides over a respective one of the soot loading cycles; and

revising the predicted soot mass by the estimated deviation.

9. The method of claim 8, further comprising:

repeating the measuring the first operating parameter, the measuring the second operating parameter, the predicting soot mass, the estimating the deviation, and the revising the predicted soot mass at predetermined time intervals; and

indicating a filter regeneration recommendation when the revised predicted soot mass reaches a predetermined value.

10. The method of claim 8, wherein the first operating parameter is measured by a nitrogen oxide sensor positioned at least partially in the exhaust flow upstream of the particulate filter.

11. The method of claim 8, wherein the second operating parameter is measured by a temperature sensor positioned in the exhaust flow upstream of the particulate filter.

12. The method of claim 8, wherein the third operating parameter is measured by a differential pressure sensor positioned in fluid communication with an inlet of the particulate filter and with an outlet of the particulate filter.

13. The method of claim 8, wherein the pressure differential is based on a pressure measured upstream of the particulate filter and a modeled pressure downstream of the particulate filter.

14. A monitoring system for a particulate filter in an exhaust system for an engine comprising:

a nitrogen oxide sensor positioned at least partially in exhaust flow upstream of the particulate filter;

a temperature sensor positioned at least partially in exhaust flow upstream of the particulate filter;

a pressure sensor positioned in fluid communication with an inlet of the particulate filter;

a processor that executes

a first empirical algorithm that determines a predicted soot mass in the particulate filter based on a pressure measured by the pressure sensor;

a second empirical algorithm that determines an expected deviation of the predicted soot mass from an actual soot mass in the filter based on operating parameters measured by the temperature sensor and the nitrogen oxide sensor indicative of filter temperature and mass flow rate of nitrogen oxides, respectively.

15. The monitoring system of claim 14, wherein the first empirical algorithm fits the measured pressure to stored empirical data correlating the measured pressure with measured soot mass.

16. The monitoring system of claim 14, wherein the pressure sensor is a differential pressure sensor that is further positioned in fluid communication with an outlet of the particulate filter and the pressure measured by the pressure sensor is a differential pressure between the inlet and the outlet.

17. The monitoring system of claim 14, wherein the pressure sensor measures pressure upstream of the filter and the first empirical algorithm models pressure downstream of the filter and calculates a modeled differential pressure from the measured pressure and the modeled pressure downstream of the filter.

18. The monitoring system of claim 14, wherein the second empirical algorithm fits the operating parameters measured by the temperature sensor and the nitrogen oxide sensor to a stored database of deviations between predicted soot mass and actual soot mass measured over multiple respective soot loading cycles of at least one particulate filter substantially identical to the particulate filter, with each of the deviations stored in the database being for a respective average modeled filter temperature and a respective average measured mass flow rate of nitrogen oxides of a respective one of the soot loading cycles.