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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.

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.

The addition of metal nanoparticles to standard coolant fluids dramatically increases the thermal conductivity of the liquid. The properties of the prepared nanofluids will allow for lighter, smaller, and higher efficiency spacecraft thermal control systems to be developed. Nanofluids with spherical or rod-shaped metal nanoparticles were investigated. At a volume concentration of 0.5%, the room temperature thermal conductivity of a 2 nm spherical gold nanoparticle-water solution was increased by more than 10% over water alone. Silver nanorods increased the thermal conductivity of ethylene glycol by 53% and water by 26%.