Soot Mass Estimation From Electrical Capacitance Tomography Imaging for a Diesel Particulate Filter

Abstract

The Electrical capacitance tomography (ECT) method has recently been adapted to obtain tomographic images of the cross section of a diesel particulate filter (DPF). However, a soot mass estimation algorithm is still needed to translate the ECT image pixel data to obtain soot load in the DPF. In this paper, we propose an estimation method to quantify the soot load in a DPF through an inverse algorithm that uses the ECT images commonly generated by a back-projection algorithm. The grayscale pixel data generated from ECT is used in a matrix equation to estimate the permittivity distribution of the cross section of the DPF. Since these permittivity data has direct correlation with the soot mass present inside the DPF, a permittivity to soot mass distribution relationship is established first. A numerical estimation algorithm is then developed to compute the soot mass accounting for the mass distribution across the cross-section of the DPF as well as the dimension of the DPF along the exhaust flow direction. Experimental data has been used to validate the proposed soot estimation algorithm which compared the estimated values with the actual measured soot mass. The estimated soot mass for various soot load amounts were found to correlate reasonably well with the measured soot masses in those cases.