Diesel Particulate Filters (DPFs) have become a required aftertreatment device for Compression Ignition engine exhaust cleanup of Particulate Matter (PM). Moreover, with the increased prevalence of Spark Ignition Direct Injection (SIDI) systems, discussions are currently underway regarding the need of Gasoline Particulate Filters to handle the PM emanating from their combustion process. In this area, the two-channel DPF model has been widely successful in predicting the temperature, pressure drop, and species conversion in these devices. Because of the need to simulate compressible flow through the channels and a porous wall, these models have a difficult time achieving real-time predictive results suitable for an Engine Control Unit (ECU). As a result, this effort describes the creation of a lumped DPF model intended for an ECU. Model formulation was based on the standard governing equations, but simplified in order to remove as much computational overhead as possible. This resulted in the requirement to solve only time-dependent Ordinary Differential Equations in the axial and radial zones of the DPF. The predictive capabilities include the temperature evolution in the device, pressure drop across the device, and chemical species conversion through the device. Even though the code was written in MATLAB, a high-level language, and no optimization was performed, faster than real time simulations were generated. The temperature results (evolution and axial dependency) compare favorably with experimental data and the previous DPF modeling efforts by the first author. However, the need to employ the assumption of incompressibility in order to remove the interdependency of the ideal gas law resulted in a significant difference between the pressure drop and species calculated and the literature standard compressible flow version. Furthermore, the additional reactions needed in order to handle catalyzed DPF devices still needs to be included along with soot propagation, which suggests a subsequent slow-down in processing time. Conversely, while the model does deviate, there is still potential for itsinclusion in an ECU by calibrating the parameters side-by-side with real-world tests on-board a vehicle.