SOOT MASS ESTIMATION FROM ELECTRICAL CAPACITANCE TOMOGRAPHY IMAGING FOR A DIESEL PARTICULATE FILTER
thesisposted on 16.03.2020 by Salah Eldin Karar Hassan, Dr. Sohel Anwar
In order to distinguish essays and pre-prints from academic theses, we have a separate category. These are often much longer text based documents than a paper.
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 research, 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. Firstly, ANSYS Electronic Desktop software is used to compute the capacitance matrix for diﬀerent amounts of soot ﬁlled in the DPF, furthermore it also analyzed diﬀerent soot distribution types applied to the DPF. The Analysis helped in constructing the sensitivity matrix which was used in the numerical estimation algorithm. Experimental data have been further used to verify the proposed soot estimation algorithm which compares the estimated values with the actual measured soot mass to validate the performance of the proposed algorithm.