Silicon Austria Labs (Austria)

In this work, a self-synchronizing grid-supporting controller for three-phase inverter is proposed. The angle-forming block is cascaded with the current loop, with the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$q$</tex-math></inline-formula>-components of the back electromotive force regulated to zero by a proportional-integral controller. It contains the complementary advantages of both grid-following and grid-forming controlled converters. The grid-tied inverters with the proposed controller are stable under wide-range grid strength; and it can better deal with the current saturation issue under different faults, such as frequency and voltage amplitude dips. The control structure is very simple; it is obtained from the conventional phase-locked loop based grid-following algorithm by some minor modifications. The impedance model in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$dq$</tex-math></inline-formula> frame is derived to analyze its dynamics. The effectiveness of the proposed algorithm is verified by experiments in both grid-connected and island modes.

Automated uncertainty propagation (AUP) is a powerful tool that enables a shift in focus from computation to the interpretation and analysis of the uncertainty. A teaching concept based on a software toolbox for automated uncertainty propagation has been previously developed. This work extends that concept towards the use of uncertainty in statistical signal processing, where two advanced techniques, Bayesian Estimation and Compressive Sensing are presented in the context of uncertainty propagation. The Bayesian Linear Minimum Mean Square Estimation (BLMMSE) is introduced with AUP. It is demonstrated that concepts like the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF) are easily implemented following the same approach as for the already introduced uncertainty quantification, since the toolbox supports linearization, Unscented Transform and Monte Carlo methods and the code for these variants is compact and equivalent. Additionally, the uncertainty analysis of signals and parameters reconstructed from compressed measurements can be easily assessed, as well as the impact of uncertainty in the expected performance of the recovery technique. This approach facilitates the integration of complex topics—such as late fusion, posterior state estimation or sparse recovery—into measurement science education. Its applicability is demonstrated through three examples, highlighting the benefits of the Unscented Transform method for AUP in sensor and data fusion. • Uncertainty based approach for advanced signal processing techniques introduced in measurement science education. • Compact implementation of Extended and Unscented Kalman Filter using automated uncertainty propagation. • Uncertainty analysis of compressive sensing-based signal acquisition. • Broad applicability of software toolbox for automated uncertainty propagation demonstrated with application examples.

Industry 5.0 envisions the seamless integration of automation, human-machine collaboration, and intelligent systems to enable highly flexible and adaptive manufacturing. However, this puts stringent requirements on the communication systems extending beyond the capabilities of current 5G technologies. This gap motivates the adoption of the digital twin (DT) paradigm, where a digital replica of physical assets and networks enables continuous monitoring, simulation, and optimization of industrial processes. This paper investigates the optimization of network access protocols, which are critical to maintaining uninterrupted industrial production. Specifically, we develop a reinforcement learning (RL) algorithm embedded within the DT framework to ensure reliable communication and production flow continuity. In a congested factory environment, an autonomous guided vehicle (AGV) must transmit data to a base station (BS) using an ALOHA-like protocol at terahertz (THz) frequencies. The DT-enabled RL model dynamically learns traffic patterns and adaptively selects backoff (BO) times for network access, maximizing reliability without requiring prior knowledge of system topology. Extensive evaluations across diverse operating scenarios–ranging from static to mobile settings, varying traffic loads, and different data and action space sizes–confirm the robustness, scalability, and adaptability of the proposed solution in highly dynamic industrial environments against conventional and advanced baselines.

The modular multilevel type multi-port solid-state transformer (SST), is a promising topology to connect and control the bidirectional power flow among the MVAC grid, the MVDC grid, and LVDC bus simultaneously and with full degree of flexibility. Identical monolithic isolated DC-DC converters containing medium-frequency transformers are thereto embedded in the submodules to provide voltage conversion and galvanic isolation between medium-voltage and low-voltage sides. This work introduces a medium-voltage battery energy storage variant with battery packs directly integrated into each cell of the system. The basic operating principle and system control is discussed based on an analytical average model. And performance of the approach is demonstrated by simulations. Special focus is put on energy balancing control between the MMC cells, where leg circulating currents of the MMC are used. Finally, the converter operation, proposed energy balancing methods and control approaches are validated by simulation of the average model of a 3 MVA, 4kV MVAC, 8kV MVDC and 1500V LVDC system.

Abstract Dielectric capacitors used as energy storage components in electrical and electronic systems offer ultrafast charge and discharge rates but have long faced the challenge of insufficient recoverable energy storage density. These materials are either lead-based, and/or their processing involves hazardous chemicals and expensive equipment, which hampers their scalability and limits their industrial applicability. We report here thin films with enhanced energy density (61 J cm -3 ) and efficiency (70%) from chemical solution deposition that are lead-free, scalable, comparably cheap in production and equipment costs and possess properties comparable to those of other high energy density dielectrics produced by costly high-vacuum deposition methods. This lead-free high-performance dielectric demonstrates a step toward implementation of dielectric thin films produced through an affordable, industrially scalable process, achieving improved energy densities.

Abstract Textile integrated electronics have emerged as a promising avenue for the development of innovative biosensors for vital function monitoring. This work presents an approach to integrate electronics and sensors by means of additive manufacturing, in particular inkjet printing and dispensing, for the direct fabrication of electronic board layouts onto textiles as substrates. Three sensor modules have been fabricated; a heart rate sensor, a breath rate sensor and an accelerometer. The process starts with printing dielectric islands, the insulating layer, followed by the layout using conductive ink. Finally, the integrated circuits are assembled using anisotropic conductive tape which facilitates the seamless integration and ensures robust electrical connections and mechanical stability. Lastly, an advanced readout and data logging scheme based on the Eclipse ThreadX real-time Operating System (RTOS) has been developed. The read-out electronics are based on the STM32L4+ microcontroller unit family. Its ultra-low power modes and computational power allow complex data processing which enables a new generation of wearable devices. The Eclipse ThreadX is an open source RTOS with considerable advantages over its counterparts, namely, its performance, determinism, code quality and functional safety. We present an advanced read-out software architecture for logging data from the three sensor modules. The integration of these cutting-edge components enhances computational capabilities but also ensures real-time data processing and communication for the proposed vital function monitoring system, opening new possibilities for wearable applications in healthcare.

This paper presents a quadrature voltage-controlled oscillator (QVCO) with an 8.8 % frequency tuning range (FTR) implemented in <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$28-\text{nm}$</tex> FDSOI process. It incorporates a fundamental VCO, a push-push frequency doubler, and an IQ (90 -degree) coupler with a power consumption of 63.8 mW. A novel stacked NMOS-based tuning network is implemented to achieve a wider FTR. The measured output power ranges from -16.7 to -11.9 dBm for frequencies between 151.9 and 165.9 GHz. The measured phase noises are -79.84 and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$-101.38 \text{dBc} / \text{Hz}$</tex> at 1 and 10 MHz offsets, respectively. The minimum IQ amplitude and phase imbalances are 0.25 dB and 2 degrees, respectively. The chip area, including probing pads, is <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{8 2 8} \times \mathbf{9 4 1} \mu \mathbf{m}^{2}$</tex>.

The development of D-band frequency extenders is one of the effective approaches toward radar miniaturization, facilitating the integration of radar and Light Detection and Ranging (LiDAR) in compact next-generation autonomous sensing platforms. This study presents a 150–157 GHz active down-conversion mixer, implemented in the 90 nm SiGe BiCMOS process. The circuit is based on a double balanced Gilbert cell mixer architecture, optimized to achieve high conversion gain and to function as a receive path frequency extender for 80 GHz frequency-modulated continuous-wave (FMCW) radar applications. The proposed mixer differs from conventional D-band receivers by providing an 80 GHz high-IF signal, rather than baseband output, to satisfy the receiver input frequency requirements of the radar chip. The circuit consists of a transconductance (Gm) stage, a switching (SW) stage connected by a differential inductor, and three transformers that convert the differential inputs/outputs to single-ended to ease on-wafer measurements. Measurements results show a peak conversion gain (CG) of 8 dB at 153 GHz, and an input-referred 1 dB compression point (P1dB) of -11.8 dBm. The down-conversion mixer consumes 46 mW power with 2.5 V of supply voltage, and chip area is 0.54 mm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> including all GSG and DC pads.