Virtual emissions monitor for automobile

• US 5,539,638 A
• Filed: 11/05/1993
• Issued: 07/23/1996
• Est. Priority Date: 08/05/1993
• Status: Expired due to Term

• Current Assignee: Rockwell Automation Technologies Incorporated (Rockwell Automation, Inc.)
• Original Assignee: Pavilion Technologies Incorporated (Rockwell Automation, Inc.)
• Inventors: Ferguson, Ralph B. II, Keeler, James D., Havener, John P., Godbole, Devendra
• Primary Examiner(s): Teska, Kevin J.
• Assistant Examiner(s): FREJD, RUSSELL WARREN
• Application Number:
  US08/149,216
• Time in Patent Office: 991 Days
• Field of Search: 364/424.03, 364/431.03, 364/431.05, 364/431.06, 364/149, 364/151, 364/497, 364/498, 364/499, 364/577, 364/578, 364/431.12, 364/571.01, 364/148 , 364/150, 73/117.2, 73/116, 250/339, 123/571, 123/672, 123/674, 60/274, 60/276, 340/439, 395/912, 395/913, 395/914, 395/915
• US Class Current: 701/29
• CPC Class Codes: F02D 2041/1433 using a model or simulation of the system
• CPC Class Codes: F02D 41/1401 characterised by the control or regulation method F02D41/1473, F02D41/1477 take precedence
• CPC Class Codes: G01N 33/0034 comprising neural networks or related mathematical techniques
• CPC Class Codes: G01N 33/0075 for multiple spatially distributed sensors, e.g. for environmental monitoring
• CPC Class Codes: G05B 13/027 using neural networks only
• CPC Class Codes: G05B 13/048 using a predictor
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G05B 23/0254 based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks
• CPC Class Codes: G05B 23/027 Alarm generation, e.g. communication protocol; Forms of alarm

Abstract

An internal combustion engine [(360)] is provided with a plurality of sensors to monitor the operation thereof with respect to various temperature measurements, pressure measurements, etc. A predictive model processor [(322)] is provided that utilizes model parameters stored in the memory [(324)] to predict from the sensor inputs a predicted emissions output. The model is trained with inputs provided by the sensor and an actual emissions sensor output. During operation, this predicted output on line [(326)] can be utilized to provide an alarm or to be stored in a history database in a memory [(328)]. Additionally, the internal combustion engine [(260)] can have the predicted emissions output thereof periodically checked to determine the accuracy of the model. This is effected by connecting the output of the engine to an external emissions sensor [(310)] and taking the difference between the actual output and the predicted output to provide an error. This is compared to a threshold and, if the error exceeds the threshold, the predictive model processor [(322)] can be placed in a training operation wherein new model parameters are generated. Additionally, retraining could take place external to the predictive model processor [(322)]. During runtime, a control network [(350)] can be utilized to predict control parameters for minimizing the emissions output.

Claims

1. A method for monitoring emissions in an internal combustion engine that emits noxious pollutants and provides a plurality of attached sensors for measuring select parameters of the engine operation as sensor output values, comprising the steps of:

storing in a predictive model a representation of the combined engine and a standard external emissions monitor, the standard external emissions monitor operable to measure the noxious pollutants output by the engine, the predictive model having an output that provides a prediction of the output of the standard external emissions monitor as a predicted emissions value and operable to receive as inputs select ones of the sensor output values;

inputting the select ones of the sensor output values to the predictive model; and

predicting the output of the combined engine and external emissions monitor to provide an indication of the noxious pollutants output by the emissions monitor without requiring the standard external emissions monitor to be present on the engine.

2. The method of claim 1 and further comprising:

attaching an external emissions monitor substantially similar to the standard external emissions monitor to the engine;

comparing the output of the external emissions monitor to the predicted emissions value of the predictive model; and

adjusting the stored representation in the predictive model whenever the predicted emissions value exceeds the actual output of the external emissions monitor by a predetermined amount.

3. The method of claim 2, wherein the stored representation in the predictive model is generated by training the predictive model on a training set of data comprised of actual sensor data received from the output of the sensors associated with the select ones of the sensor output values, and actual measured emissions output data from the external emissions monitor when connected to the engine.

4. The method of claim 3, wherein the step of adjusting comprises retraining the predictive model on a new set of training data utilizing the external emissions monitor to provide the actual output data.

5. The method of claim 3, wherein the step of adjusting comprises offsetting the predicted emissions value of the predictive model by a predetermined amount to minimize the error below a predefined level.

6. The method of claim 1, and further comprising:

comparing the predicted emissions value with an internal threshold value; and

generating an alarm when the predicted emissions value exceeds the internal threshold value.

7. The method of claim 6, wherein the alarm is a light on a display.

8. The method of claim 6, and further comprising, storing a plurality of stored threshold values in a memory and selecting only one of the plurality of threshold values for the threshold value to utilize in the step of comparing, the step of selecting performed in accordance with predetermined criteria.

9. The method of claim 1, and further comprising, storing a history of the predicted emissions values output by the predictive model as a function of time.

10. The method of claim 8, and further comprising, downloading the stored history on a periodic basis.

11. The method of claim 1, and further comprising:

determining if the select measured parameters are outside of acceptable limits in accordance with predetermined criteria; and

substituting a known value for the sensor output values when it is determined that they are outside of the acceptable limits.

12. The method of claim 11, wherein the step of substituting comprises predicting from a past history of the measured sensor output values to be substituted, a predicted value, the predicted value comprising the known values.

13. The method of claim 12, wherein the past history is a function of the other measured sensor output values.

14. The method of claim 11, wherein the step of determining comprises:

providing a sensor validation predictive network having as an input the actual sensor values of the engine, the sensor validation predictive network having associated therewith a stored representation of each of the actual sensor output values as a function of the other of the actual sensor output values to provide on the output thereof a predicted sensor output value for each of the actual sensor values input thereto;

predicting with the sensor validation predictive network the predicted sensor output value; and

comparing each of the differences of the input actual sensor output values in the predictive sensor output values with predetermined limits for those differences.

15. The method of claim 1, and further comprising:

comparing the predicted emissions value output by the predictive model with a desired emissions value;

providing an emissions control system for modifying the operation of the engine; and

controlling the emissions control system to operate in such a manner as to reduce any error between the predicted emissions value and the desired emissions value.