Signal Processing for Rough Road Detection 2010-01-0673
Misfire diagnostics are required to detect missed combustion events which may cause an increase in emissions and a reduction in performance and fuel economy. If the misfire detection system is based on crankshaft speed measurement, driveline torque variations due to rough road can hinder the diagnosis of misfire. A common method of rough road detection uses the ABS (Anti-Lock Braking System) module to process wheel speed sensor data. This leads to multiple integration issues including complexities in interacting with multiple suppliers, inapplicability in certain markets and lower reliability of wheel speed sensors.
This paper describes novel rough road detection concepts based on signal processing and statistical analysis without using wheel speed sensors. These include engine crankshaft and Transmission Output Speed (TOS) sensing information. Algorithms that combine adaptive signal processing and specific statistical analysis of this information are presented. Vehicle test results are shown to demonstrate the efficacy of these techniques to distinguish between rough road, smooth road, and misfire.
Tameem Assaf, David Mathews, Sanjeev Naik
General Motors Corp.
SAE 2010 World Congress & Exhibition
In-Vehicle Networks and Software, 2010-SP-2263, SAE International Journal of Passenger Cars - Electronic and Electrical Systems-V119-7, SAE International Journal of Passenger Cars - Electronic and Electrical Systems-V119-7EJ