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Current progress in the development of diesel engines substantially contributes to the reduction of NOx and Particulate Matter (PM) emissions but will not succeed to eliminate the application of Diesel Particulate Filters (DPFs) in the future. In the past we have introduced a Multi-Functional Reactor (MFR) prototype, suitable for the abatement of the gaseous and PM emissions of the Low Temperature Combustion (LTC) engine operation. In this work the performance of MFR prototypes under both conventional and advanced combustion engine operating conditions is presented. The effect of the MFR on the fuel penalty associated to the filter regeneration is assessed via simulation. Special focus is placed on presenting the performance assessment in combination with the existing differences in the morphology and reactivity of the soot particles between the different modes of diesel engine operation (conventional and advanced). The effect of aging on the MFR performance is also presented.

Auto transformer rectifier units (ATRUs) are commonly used in aircraft applications such as electric actuation for harmonic mitigation due to their high reliability and relative low cost. However, those components and the magnetic filter components associated to it are the major contributors to the overall size and weight of the system. Optimization of the magnetic components is essential in order to minimize weight and size, which are major market drivers in aerospace industry today. This requires knowledge of the harmonic content of the current. This can be obtained by simulation, but the process is slow. In order to enable fast and efficient design space exploration of optimal solutions, an algebraic calculation process is proposed in this paper for multi-pulse ATRUs (e.g. 12-pulse and 18-pulse rectifiers), starting from existing solution proposed for 6 pulse rectifier in the literature.

Due to increasing demand for environment friendly vehicles with better fuel economy and strict legislations on greenhouse gas emissions, lightweight design has become one of the most important issues concerning the automobile industry. Within the scope of this work lightweight design potentials that a conventional single cylinder engine crankshaft offers are researched through utilization of structural optimization techniques. The objective of the study is to reduce mass and moment of inertia of the crankshaft with the least possible effect on the stiffness and strength. For precise definition of boundary conditions and loading scenarios multi body simulations are integrated into the optimization process. The loading conditions are updated at the beginning of each optimization loop, in which a multi body simulation of the output structure from the previous optimization loop is carried out.

The calibration of Engine Control Units (ECUs) for road vehicles is challenged by stringent legal and environmental regulations, coupled with short development cycles. The growing number of vehicle variants, although sharing similar engines and control algorithms, requires different calibrations. Additionally, modern engines feature increasingly number of adjustment variables, along with complex parallel and nested conditions within the software, demanding a significant amount of measurement data during development. The current state-of-the-art (White Box) model-based ECU calibration proves effective but involves considerable effort for model construction and validation. This is often hindered by limited function documentation, available measurements, and hardware representation capabilities. This article introduces a model-based calibration approach using Neural Networks (Black Box) for two distinct ECU functional structures with minimal software documentation.