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The deployment of small unmanned aircraft systems (UAS) to collect routine in situ vertical profiles of the thermodynamic and kinematic state of the atmosphere in conjunction with other weather observations could significantly improve weather forecasting skill and resolution. High-resolution vertical measurements of pressure, temperature, humidity, wind speed and wind direction are critical to the understanding of atmospheric boundary layer processes integral to air–surface (land, ocean and sea ice) exchanges of energy, momentum, and moisture; how these are affected by climate variability; and how they impact weather forecasts and air quality simulations. We explore the potential value of collecting coordinated atmospheric profiles at fixed surface observing sites at designated times using instrumented UAS. We refer to such a network of autonomous weather UAS designed for atmospheric profiling and capable of operating in most weather conditions as a 3D Mesonet. We outline some of the fundamental and high-impact science questions and sampling needs driving the development of the 3D Mesonet and offer an overview of the general concept of operations. Preliminary measurements from profiling UAS are presented and we discuss how measurements from an operational network could be realized to better characterize the atmospheric boundary layer, improve weather forecasts, and help to identify threats of severe weather.
Power Line Communication (PLC) is used to transmit high-fidelity data on internal cell characteristics from within instrumented cells to an external Battery Management System (BMS). Using PLC is beneficial, as it avoids the need for a complex and heavyweight wiring harness within a battery. The use of advanced modulation, such as Quadrature Amplitude Modulation (QAM), is considered here. The existing experimental results of lithium-ion cell impedance characteristics for frequencies of 100 kHz-200 MHz are exploited in order to create a realistic battery model. This model is used to determine the effectiveness and optimal properties of PLC with QAM, as a means of in situ battery communication for Battery Electric Vehicles (BEVs) in combination with a real-world dynamic drive profile. Simulations reveal that the performance of the PLC system is heavily dependent on the selected carrier frequency due to the significant changes in reactance and internal resistance of the lithium-ion cells tested. Furthermore, cells placed in parallel display a decreased performance compared with cells in series. The results highlight that the optimal carrier frequency for in situ QAM-based PLC for a lithium-ion battery system is 30 MHz, and that additional signal conditioning is required for 4-QAM and higher modulation orders.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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