Search Results

The stochastic properties of continuous time model parameters obtained through discrete least squares estimation are examined. Particular attention is given to the application of estimating the fuel evaporation dynamics of a V-8 SI engine. The continuous time parameter distributions in this case are biased. The bias is shown to be a function of both measurement noise and sampling rate selection. Analysis and experimental results suggest that for each particular model, there is a corresponding optimum sampling rate. A bias compensation formula is proposed that improves the accuracy of least squares estimation without iterative techniques.

A new and unique facility has been developed at the Turbulent Shear Flows Laboratory at Michigan State University for the study of automotive cooling fans. Performance data can be acquired for a variety of fan and component geometries using this facility. Additionally, detailed velocity measurements can be made in the wake of the fan. This paper describes the details of the facility with examples of the data that can be acquired.

To make electrical or electro-hydraulic gas exchange valve actuators more economically feasible for the production of cam-less engines, it is desirable to achieve valve position information from existing engine sensors rather than to develop and install new sensors for each gas exchange valve. Time and frequency domain characteristics of acoustic (knock) sensor signals were analyzed using both cross-correlation and Fourier analyses to determine characteristics that indicate valve position. The time-domain signatures for valve events were found to be inconsistent from cycle to cycle and thus difficult to identify using cross-correlation techniques. Frequency content of the engine vibration as it varied with crankshaft angle was analyzed to find valve position dependent patterns. Analysis revealed a wideband signal that correlates to intake and exhaust valve closing events.