Process for deriving predictive model of crankshaft rotation of a combustion engine

• US 5,794,171 A
• Filed: 02/29/1996
• Issued: 08/11/1998
• Est. Priority Date: 02/29/1996
• Status: Expired due to Fees

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Marko, Kenneth Andrew, Bryant, Bruce David, Krishnaswami, Vasanth
• Primary Examiner(s): NGUYEN, TAN QUANG
• Application Number:
  US08/609,026
• Time in Patent Office: 894 Days
• Field of Search: 364/431.01, 364/431.03, 364/431.04, 364/431.08, 364/431.051, 364/431.07, 364/424.034, 364/424.04, 73/116, 73/117.3, 123/414, 123/416, 123/419, 123/436, 123/426, 123/428, 701/99, 701/101, 701/102, 701/111, 701/103, 701/110, 701/29, 701/35
• US Class Current: 701/99
• CPC Class Codes: G01M 15/11 by detecting misfire

Abstract

A predictive model is derived for subsequent use in a misfire detector in an internal combustion engine. Data collected using a test engine is curve-fitted using NARMAX techniques to obtain a computational formula for the predictive model which relates deviant acceleration at the accessible crankshaft section to deviant acceleration at the inaccessible crankshaft section. Thus, the model can be used during actual misfire detection to reduce the effects of the torsional oscillations.

Claims

1. A method of deriving a predictive model for use in a misfire detector for an internal combustion engine having a nonrigid crankshaft, said predictive model predicting motion of a remote section of said crankshaft which is relatively damped with respect to torsional oscillations, said predictive model being based on motion sensed at a non-remote section of said crankshaft which is relative undamped with respect to torsional oscillations, said method comprising the steps of:

operating a test engine with and without induced misfires over a range of speeds and loads;

measuring engine operating conditions over said range of speeds and loads, said engine operating conditions including crankshaft rotation intervals measured at both said non-remote section and said remote section of said crankshaft;

determining deviant acceleration values at said remote and non-remote crankshaft sections in response to said crankshaft rotation intervals; and

curve-fitting said measured engine operating conditions using nonlinear autoregressive moving average with exogenous inputs (NARMAX) techniques to obtain a computational formula for said predictive model, wherein said deviant acceleration values determined for said non-remote section of said crankshaft are related to said deviant acceleration values determined for said remote section of said crankshaft.

2. The method of claim 1 further comprising the step of filtering said deviant acceleration values for said remote crankshaft section prior to said curve-fitting step to reduce torsional oscillations in said deviant acceleration values.

3. The method of claim 2 wherein said filtering is comprised of subtracting torsional oscillation values measured during steady state operation of said test engine.

4. The method of claim 2 wherein said filtering is comprised of assigning a value of zero to said deviant acceleration values when no misfire occurred.

5. The method of claim 1 wherein said engine operating conditions which are measured and input to said NARMAX techniques for curve-fitting further include fuel pulse width of fuel supplied to said engine.

6. The method of claim 1 wherein said engine operating conditions which are measured and input to said NARMAX techniques for curve-fitting further include mass air flow into said engine.