Fraunhofer Institute for Integrated Circuits IIS, Division Engineering of Adaptive Systems EAS

The Functional Mockup Interface (FMI) is a tool independent standard for the exchange of dynamic models and for co-simulation. The development of FMI was initiated and organized by Daimler AG within the ITEA2 project MODELISAR. The primary goal is to support the exchange of simulation models between suppliers and OEMs even if a large variety of different tools are used. The FMI was developed in a close collaboration between simulation tool vendors and research institutes. In this article an overview about FMI is given and technical details about the solution are discussed.

The Functional Mockup Interface (FMI) is a tool independent standard for the exchange of dynamic models and for Co-Simulation. The first version, FMI 1.0, was published in 2010. Already more than 30 tools support FMI 1.0. In this paper an overview about the upcoming version 2.0 of FMI is given that combines the formerly separated interfaces for Model Exchange and Co-Simulation in one standard. Based on the experience on using FMI 1.0, many small details have been improved and new features introduced to ease the use and increase the performance especially for larger models. Additionally, a free FMI compliance checker is available and FMI models from different tools are made available on the web to simplify testing.

The industrial wireless automation sector exhibits a huge market growth in the last years. Today, many applications already use wireless technologies. However, the existing wireless solutions do not yet offer sufficient performance with respect to real-time and reliability requirements, particularly for closed-loop control applications. As a result, low latency wireless communication technologies will bridge the gap and can become a key factor for the wide-spread penetration of wireless in industrial communication systems. It is therefore the main goal of this paper to provide a comprehensive overview on requirements, current solutions, and challenges as well as opportunities for future wireless industrial systems. Thereby, presented requirement figures, analysis results, and performance evaluations are based on numerous practical examples from industry.

Co-Simulation is a general approach to simulate coupled technical systems. In a master-slave concept the slaves simulate sub-problems whereas the master is responsible for both coordinating the overall simulation as well as transferring data. To unify the interface between master and slave the FMI for Co-Simulation was developed. Using FMI a master was implemented with simple and advanced algorithms which can be applied depending on the properties of the involved slave simulators. The master was tested amongst others by coupling with SimulationX.

The paper presents a methodology for simulating the static and dynamic performance of integrated circuits in the presence of electro-thermal interactions on the integrated circuit die. The technique is based on the coupling of a finite element method (FEM) program with a circuit simulator. In contrast to other known simulator couplings a time step algorithm is used, Its implementation in simulation tools is described. The thermal modeling of the die/package structure and the extended modeling of the electronic circuit is discussed. Simulation results which indicate the capabilities of the methodology for electro-thermal simulation are compared to experimental results.

Complex multi-disciplinary models in system dynamics are typically composed of subsystems. This modular structure of the model reflects the modular structure of complex engineering systems. In industrial applications, the individual subsystems are often modelled separately in different mono-disciplinary simulation tools. The Functional Mock-Up Interface (FMI) provides an interface standard for coupling physical models from different domains and addresses problems like export and import of model components in industrial simulation tools (FMI for Model Exchange) and the standardization of co-simulation interfaces in nonlinear system dynamics (FMI for Co-Simulation), see [10]. The renewed interest in algorithmic and numerical aspects of co-simulation inspired some new investigations on error estimation and stabilization techniques in FMI for Model Exchange and Co-Simulation v2.0 compatible co-simulation environments. In the present paper, we focus on reliable error estimation for communication step size control in this framework.

Smart manufacturing aims to overcome the limitations of today's rigid assembly lines by making the material flow and manufacturing process more flexible, versatile, and scalable. The main economic drivers are higher resource and cost efficiency as the manufacturers can more quickly adapt to changing market needs and also increase the lifespan of their production sites. The ability to close feedback loops fast and reliably over long distances among mobile robots, remote sensors, and human operators is a key enabler for smart manufacturing. Thus, this article provides a perspective on control and coordination over wireless networks. Based on an analysis of real-world use cases, we identify the main technical challenges that need to be solved to close the large gap between the current state of the art in industry and the vision of smart manufacturing. We discuss to what extent existing control-over-wireless solutions in the literature address those challenges, including our own approach toward a tight integration of control and wireless communication. In addition to a theoretical analysis of closed-loop stability, practical experiments on a cyber-physical testbed demonstrate that our approach supports relevant smart manufacturing scenarios. This article concludes with a discussion of open challenges and future research directions.

The growing need for bidirectional mobile satellite communications in the Ka-band necessitates the development of dedicated antenna systems. In this article, we describe two different solutions for mobile user-terminal antennas intended for an operation in emergency scenarios. The first solution, a high-gain antenna, consists of a Cassegrain reflector, fed from a multimode monopulse tracking system for circular polarization at a satellite downlink frequency of 20 GHz. The structure is operational at 30 GHz to cover the uplink frequency range. The antenna system is mounted on a high-performance mechanical positioner to facilitate a fast compensation of the movements of the carrier vehicle. The second solution, a low-profile antenna, consists of leaky-wave antenna (LWA) panels employing two-layer partially reflective surfaces (PRSs). A hybrid tracking technique is used, and a unique feature of this antenna is its dual-band operation, to overcome the challenge of widely separated uplink and downlink ranges in the Ka-band. This article describes the design of the two types of antennas and analyzes the measurement results. Furthermore, tracking issues considered from the view of control engineering are addressed, and an evaluation of tracking accuracy is presented.

Systems-on-Chip (SoCs) are heterogeneous by nature as they may integrate digital, analog, RF hardware as well as software components or non electrical parts such as sensors or actuators. The increasing level of complexity for designing SoCs in a reasonable amount of time and resources asks, among other capabilities, for powerful modeling and simulation means. SystemC is emerging as a de facto standard for digital system design, but is still lacking a standard support of continuous-time and mixed discrete-event/continuous-time systems. This paper presents the first elements of extensions to SystemC, called SystemC-AMS, that are proposed to fill the gap.

The paper presents a system-level approach for the modeling and simulation of a paradigmatic Wireless Sensor Network composed of two nodes using SystemC-AMS, an open-source C++ extension to the OSCI SystemC Standard dedicated to the description of heterogeneous systems containing digital, analog, RF hardware IPs as well as embedded software. The paper is composed of three parts. The first part details the modeled WSN (physical sensor, sigma-delta ADC, ATMEGA128 8-bit microcontroller running the embedded application, QPSK-based 2.4 GHz RF transceiver), presents the corresponding implementation in SystemC-AMS, and gives an insight on how multi-frequency simulation is handled in SystemC-AMS. The second part shows how to introduce several RF designer specifications (noise figure, IIP3, ...) into models and how to express them in SystemC-AMS. The third part proves that the combination of C++ and RF baseband equivalent dramatically reduces simulation time while keeping excellent accuracy and code readability. The paper concludes on the possibilities offered by this approach in terms of validation and optimization of heteregeneons systems through open-source simulation.

Analyzing vibration data using deep neural networks is an effective way to detect damages in rotating machinery at an early stage. However, the black-box approach of these methods often does not provide a satisfactory solution because the cause of classifications is not comprehensible to humans. Therefore, this work investigates the application of the explainable AI (XAI) algorithms to convolutional neural networks for vibration-based condition monitoring. Thus, the three XAI algorithms GradCAM, LRP and LIME with a modified perturbation strategy are applied to classifications based on the Fourier transform as well as the order analysis of the vibration signal. The following visualization as frequency-RPM maps and order-RPM maps allows for an effective assessment of saliency values for variable periodicity of the data, which translates to a varying rotation speed of a real-world machine. To compare the explanatory power of the XAI methods, investigations are first carried out with a synthetic data set with known class-specific characteristics. Both a visual and a quantitative analysis of the resulting saliency maps are presented. Then, a real-world data set for vibration-based imbalance classification on an electric motor, which runs at a broad range of rotation speeds, is used. The results indicate that the investigated algorithms are each partially successful in providing sample-specific saliency maps which highlight class-specific features and omit features which are not relevant for classification.

Systems on chip are more and more heterogeneous and include software, analog/RF and digital hardware, and non-electronic components, such as sensors or actuators. The design and verification of such systems require appropriate modeling means to deal with the increasing complexity and to achieve efficient simulation. SystemC, a set of C++ classes and methods, provides a modeling and simulation framework that supports digital (discrete) hardware and software systems from abstract specifications to register transfer level models. We propose a way to extend the capabilities of SystemC to support mixed discrete-continuous systems by implementing a synchronous dataflow (SDF) model of computation (MoC). The SDF MoC is used to embed continuous-time behavior in SDF modules and to support synchronization with the existing SystemC kernel. The paper presents an overview of the architecture and the syntax of the proposed extensions and gives modeling examples with simulation results.

This paper presents and discusses the foundations on which the analog and mixed-signal extensions of SystemC, named SystemC-AMS, will be developed. First, requirements from targeted application domains are identified. These are then used to derive design objectives and related rationales. Finally, some preliminary seed work is presented and the outline of the analog and mixed-signal extensions development work is given.

The ever-growing proliferation of wireless devices and technologies used for Internet of Things (IoT) applications, such as patient monitoring, military surveillance, and industrial automation and control, has created an increasing need for methods and tools for connectivity prediction, information flow monitoring, and failure analysis to increase the dependability of the wireless network. Indeed, in a safety-critical Industrial IoT (IIoT) setting, such as a smart factory, harsh signal propagation conditions combined with interference from coexisting radio technologies operating in the same frequency band may lead to poor network performance or even application failures despite precautionary measures. Analyzing and troubleshooting such failures on a large scale is often difficult and time-consuming. In this paper, we share our experience in troubleshooting coexistence problems in operational IIoT networks by reporting on examples that show the possible hurdles in carrying out failure analysis. Our experience motivates the need for a userfriendly, automated failure analysis system, and we outline an architecture of such system that allows to observe multiple communication standards and unknown sources of interference.

In this article, the static output feedback problem for linear time-invariant systems is considered. For arbitrary assignability of the roots of the characteristic polynomial by static output feedback, a new necessary and sufficient condition is derived. Although, the proof is based on simple analysis, the known sufficient conditions (derived by techniques of algebraic geometry) are directly covered. Furthermore, an algorithm for the calculation of feedback matrices assigning a desired set of eigenvalues is proposed. This algorithm does not require the desired eigenvalues to be distinct and it explicitly exploits the available degrees of freedom for reducing the feedback gain. The presented approach is illustrated on computational examples.

The new operator homotopy(..) was introduced in Modelica 3.2 to improve the solution of difficult initialization problems. The background and motivation for this approach is discussed and it is demonstrated how to apply it for mechanical, electrical and fluid systems. Furthermore, it is shown at hand of several examples how an inappropriate formulation might lead to ill-posed problems.

Functional Digital Mock-up (FDMU) and Functional Mock-up Interface (FMI) are two keywords arising in the last years in simulation technology. In this paper, we would like to show that both principles, aiming at a comprehensive investigation of heterogeneous systems, e.g. from mechatronics, are not necessarily competing with each other but may be combined to benefit from the ideas behind. The approaches are based on different ideas and cover different aspects of the interaction of modern simulation tools. For that reason different constraints have to be considered, which do not make things easier. Both principles have advantages and disadvantages. However, by combining both ways, a powerful framework for handling a broad variety of simulation tasks can be formed. In the paper, a possible approach for integrating both technologies will be shown.

Time reduction and quick geometrical changes of complex components and tools are currently the most important demands in product development. The manufacturing process presented in this paper is based on multiple additive and subtractive technologies such as laser cutting, laser welding, direct laser metal deposition and CNC milling. The process chain is similar to layer‐based Rapid Prototyping Techniques. In the first step, the 3D CAD geometry is sliced into layers by a specially developed software. These slices are cut by high speed laser cutting and then joined together. In this way laminated tools or parts are built. To improve surface quality and to increase wear resistance a CNC machining center is used. The system consists of a CNC milling machine, in which a 3 kW Nd:YAG laser, a coaxial powder nozzle and a digitizing system are integrated.

Process variations increasingly challenge the manufacturability of advanced devices and the yield of integrated circuits. Technology computer-aided design (TCAD) has the potential to make key contributions to minimize this problem, by assessing the impact of certain variations on the device, circuit, and system. In this way, TCAD can provide the information necessary to decide on investments in the processing level or the adoption of a more variation tolerant process flow, device architecture, or design on circuit or chip level. Five Fraunhofer institutes joined forces to address these issues. Their own software tools, e.g., for lithography/topography simulation, mixed-mode device simulation, compact model extraction, and behavioral modeling, have been combined with commercial tools to establish a hierarchical system of simulators in order to analyze process variations from their source, e.g., in a lithography step, through device fabrication up to the circuit and system levels.

Summary A secure and flexible communication infrastructure for the use of broadband and IP‐based services is becoming more and more important in the context of Public Protection and Disaster Relief (PPDR). Government agencies and emergency responders need to be able to react quickly to emergencies across the globe. In particular, satellite‐based 5G mobile networks can support government agencies during their critical tasks. To support the standardization committees and the industry, it is required to evaluate new architectures for such networks by utilizing testbeds and field trials. In this article, we propose and investigate architectures for mobile PPDR networks with satellite backhaul to ensure Communication on‐the‐Move. The flexibility within the architectures comes with the distribution of the core network nodes at the edge of the network applying the Core‐Edge Split concept. The presented results show that already existing interfaces of the Evolved Packet Core 3GPP standard allow satellite‐based 5G networks tailored to the needs of government authorities.