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Excellence in IT is both a driver and a key enabler of the digital transformation. The digital transformation changes the way we live, work, learn, communicate, and collaborate. The Internet of Things (IoT) fundamentally influences today’s digital strategies with disruptive business operating models and fast changing markets. New business information systems are integrating emerging Internet of Things infrastructures and components. With the huge diversity of Internet of Things technologies and products organizations have to leverage and extend previous Enterprise Architecture efforts to enable business value by integrating Internet of Things architectures. Both architecture engineering and management of current information systems and business models are complex and currently integrating beside the Internet of Things synergistic subjects, like Enterprise Architecture in context with services & cloud computing, semantic-based decision support through ontologies and knowledge-based systems, big data management, as well as mobility and collaboration networks. To provide adequate decision support for complex business/IT environments, we have to make transparent the impact of business and IT changes over the integral landscape of affected architectural capabilities, like directly and transitively impacted IoT-objects, business categories, processes, applications, services, platforms and infrastructures. The paper describes a new metamodel-based approach for integrating Internet of Things architectural objects, which are semi-automatically federated into a holistic Digital Enterprise Architecture environment.
The complexity of supply chains increases, especially due to the geographical spread of supplier and customer networks. In the connected and automated supply chains of the industry 4.0, even more nodes are incorporated in supply chains. This paper discusses the possible improvement of process quality in the industry 4.0 through the different blockchain and distributed ledger technologies. We derived hypotheses from a literature review and asked German blockchain experts from the industry to validate and discuss the hypotheses. We find that the different blockchain technologies and consensus algorithms have different strength with regard to quality improvement. One central finding is that IOTA, developed especially for the IoT and deemed the ’next evolutionary step’ is scalable and hence may increase the process efficiency, but at the same time is more vulnerable than other blockchain implementations, which again may reduce the overall process quality.
Analog integrated circuit sizing still relies heavily on human expert knowledge as previous automation approaches have not found wide-spread acceptance in industry. One strand, the optimization-based automation, is often discarded due to inflated constraining setups, infeasible results or excessive run times. To address these deficits, this work proposes a alternative optimization flow featuring a designer’s intuition for feasible design spaces through integration of expert knowledge based on the gm/ID-method. Moreover, the extensive run times of simulation-based optimization flows are overcome by incorporating computationally efficient machine learning methods. Neural network surrogate models predicting eleven performance parameters increase the evaluation speed by 3 400× on average compared to a simulator. Additionally, they enable the use of optimization algorithms dependent on automatic differentiation, that would otherwise be unavailable in this field. First, an up to 4× more efficient way for sampling training data based on the aforementioned space is detailed. After presenting the architecture and training effort regarding the surrogate models, they are employed as part of the objective function for sizing three operational amplifiers with three different optimization algorithms. Additionally, the benefits of using the gm/ID-method become evident when considering technology migration, as previously found solutions may be reused for other technologies.
In this paper we describe the design and development process of an electromagnetic picker for rivets. These rivets are used in a production process of leather or textile design objects like riveted waist belts or purses. The picker is designed such that it replaces conventional mechanical pickers thus avoiding mechanical wear problems and increasing the process quality. The paper illustrates the challenges in the design process of this mechatronic system. The design process was based on both simulation and experiments leading to a prototype that satisfies the requirements.
The design process for a single phase, smart, universal charger for light electric vehicles, is presented. With a step up, power factor correction circuit, followed by a phase shifted, full bridge converter, with synchronous rectification on the secondary side. Due to the resistor-capacitor-diode snubber on the secondary side, the current peak at the start of power transfer, leads to false triggering during light load control with peak current mode control. The solution developed for light loads, is to change from peak current control to voltage control. This is achieved by limiting the maximum phase shift, instead of changing the reference value. For the power factor correction stage, measured and calculated efficiencies are compared as a function of the output power. The voltage and current waveforms are shown for the power factor correction circuit, and for the phase shifted bridge, the measured current waveform is compared with simulation.
In this work design rules for a novel brushless excitation system for externally excited synchronous machines are discussed. The concept replaces slip rings with a fullbridge active rectifier and a controller mounted on the rotor. An AC signal induced from the stator is used to charge the rotor DC link. The DC current for the rotor excitation is provided from this DC link source. Finite element analysis of an existing machine is used to analyze the practicability of the excitation system.
This paper presents the design and simulation processes of an Equiangular Spiral Antenna for the extremely high frequencies between 65 GHz and 170 GHz. A new approach for the analysis of the antenna’s electrical parameters is described. This approach is based on formalism proposed by Rumsey to determine the EM field produced by an equiangular spiral antenna. Analytical expressions of the electrical parameters such as the gain or the directivity are then calculated using well sustained mathematical approximations. The comparison of obtained results with those from numerical integration methods shows a good agreement.
This paper presents a permanent magnet tubular linear generator system for powering passive sensors using vertical vibration harvesting energy. The system consists of a permanent magnet tubular linear vibration generator and electric circuits. By using the design of mechanical resonant movers, the generator is capable of converting low frequencies small amplitude vertical vibration energy into more regular sinusoidal electrical energy. The distribution of the magnetic field and electromotive force are calculated by Finite Element Analysis. The characteristics of the linear vibration generator system are observed. The experimental results show the generator can produce about 0.4W~1.6W electrical power when the vibration source's amplitude is fixed on 2mm and the frequencies are between 13Hz and 22Hz.
Fault diagnosis of rolling bearings is an essential process for improving the reliability and safety of the rotating machinery. It is always a major challenge to ensure fault diag- nosis accuracy in particular under severe working conditions. In this article, a deep adversarial domain adaptation (DADA) model is proposed for rolling bearing fault diagnosis. This model con- structs an adversarial adaptation network to solve the commonly encountered problem in numerous real applications: the source domain and the target domain are inconsistent in their distribution. First, a deep stack autoencoder (DSAE) is combined with representative feature learning for dimensionality reduction, and such a combination provides an unsupervised learning method to effectively acquire fault features. Meanwhile, domain adaptation and recognition classification are implemented using a Softmax classifier to augment classification accuracy. Second, the effects of the number of hidden layers in the stack autoencoder network, the number of neurons in each hidden layer, and the hyperparameters of the proposed fault diagnosis algorithm are analyzed. Third, comprehensive analysis is performed on real data to vali- date the performance of the proposed method; the experimental results demonstrate that the new method outperforms the existing machine learning and deep learning methods, in terms of classification accuracy and generalization ability.
Digitization fosters the development of IT environments with many rather small structures, like Internet of Things (IoT), microservices, or mobility systems. They are needed to support flexible and agile digitized products and services. The goal is to create service-oriented enterprise architectures (EA) that are self optimizing and resilient. The present research paper investigates methods for decision-making concerning digitization architectures for Internet of Things and microservices. They are based on evolving enterprise architecture reference models and state of the art elements for architectural engineering for microgranular systems. Decision analytics in this field becomes increasingly complex and decision support, particularly for the development and evolution of sustainable enterprise architectures, is sorely needed. The challenging of the decision processes can be supported with in a more flexible and intuitive way by an architecture management cockpit.
In the present tutorial we perform a cross-cut analysis of database systems from the perspective of modern storage technology, namely Flash memory. We argue that neither the design of modern DBMS, nor the architecture of flash storage technologies are aligned with each other. The result is needlessly suboptimal DBMS performance and inefficient flash utilisation as well as low flash storage endurance and reliability. We showcase new DBMS approaches with improved algorithms and leaner architectures, designed to leverage the properties of modern storage technologies. We cover the area of transaction management and multi-versioning, putting a special emphasis on: (i) version organisation models and invalidation mechanisms in multi-versioning DBMS; (ii) Flash storage management especially on append-based storage in tuple granularity; (iii) Flash-friendly buffer management; as well as (iv) improvements in the searching and indexing models. Furthermore, we present our NoFTL approach to native Flash access that integrates parts of the flash-management functionality into the DBMS yielding significant performance increase and simplification of the I/O stack. In addition, we cover the basics of building large Flash storage for DBMS and revisit some of the RAID techniques and principles.
This work is a report on practical experiences with the issue of interoperability in German practice management systems (PMSs) from an ongoing clinical trial on teledermatology, the TeleDerm project. A proprietary and established web-platform for store-and-forward telemedicine is integrated with the IT in the GPs’ offices for automatic exchange of basic patient data. Most of the 19 different PMSs included in the study sample lack support of modern health data exchange standards, therefore the relatively old but widely available German health data exchange interface “Gerätedatentransfer” (GDT) is used. Due to the lack of enforcement and regulation of the GDT standard, several obstacles to interoperability are encountered. As a partial, but reusable working solution to cope with these issues, we present a custom middleware which is used in conjunction with GDT. We describe the design, technical implementation and observed hindrances with the existing infrastructure. A discussion on health care interfacing standards and the current state of interoperability in German PMS software is given.
The diversity of energy prosumer types makes it difficult to create appropriate incentive mechanisms that satisfy both prosumers and energy system operators alike. Meanwhile, European energy suppliers buy guarantees of origin (GoO) which allow them to sell green energy at premium prices while in reality delivering grey energy to their customers. Blockchain technology has proven itself to be a robust paying system in which users transact money without the involvement of a third party. Blockchain tokens can be used to represent a unit of energy and, just as GoOs, be submitted to the market. This paper focuses on simulating marketplace using the ethereum blockchain and smart contracts, where prosumers can sell tokenized GoOs to consumers willing to subsidize renewable energy producers. Such markets bypass energy providers by allowing consumers to obtain tokenized GoOs directly from the producers, which in turn benefit directly from the earnings. Two market strategies where tokens are sold as GoOs have been simulated. In the Fix Price Strategy prosumers sell their tokens to the average GoO price of 2014. The Variable Price Strategy focuses on selling tokens at a price range defined by the difference between grey and green energy. The study finds that the ethereum blockchain is robust enough to functions as a platform for tokenized GoO trading. Simulation results have been compared and the results indicate that prosumers earn significantly more money by following the Variable Price
Strategy.
The automotive industry faces three major challenges – shortage of fossil fuels, politics of global warming and rising competition from new markets. In order to remain competitive companies have to develop more efficient and alternative fuel vehicles that meet the individual requirements of the customers. Functional Integration combined with new Technologies and materials are the key to stable success in this industry. The sustaining upward trend to system innovations within the last ten years confirms this. The development of complex products like automobiles claim skills of various disciplines e.g. engineering, chemistry. Furthermore, these skills are spread all over the supply chain. Hence the only way to stay successful in the automotive industry is cooperation and collaborative innovation. Interdisciplinary and interorganizational development has high demands on cooperation models especially in the automotive industry. In this case study cooperation models are analyzed and evaluated according to their applicability to interdisciplinary, interorganizational development projects in the automotive industry. Following, the research campus ARENA2036 is analyzed. ARENA2036 is an interdisciplinary, interorganizational development project housing automobile manufacturers, suppliers, research establishments and university institutes. Finally, based on interviews with the partners and the precede analyses of cooperation models, suggestions for implementation are given to ARENA2036.
In networked operating room environments, there is an emerging trend towards standardized non-proprietary communication protocols which allow to build new integration solutions and flexible human-machine interaction concepts. The most prominent endeavor is the IEEE 11073 SDC protocol. For some uses cases, it would be helpful if not just medical devices could be controlled based on SDC, but also building automation systems like light, shutters, air condition, etc. For those systems, the KNX protocol is widely used. We build an SDC-to-KNX gateway which allows to use the SDC protocol for sending commands to connected KNX devices. The first prototype system was successfully implemented at the demonstration operating room at Reutlingen University. This is a first step toward the integration of a broader variety of KNX devices.
Rapid value delivery requires a company to utilize empirical evaluation of new features and products in order to avoid unnecessary product risks. This helps to make data-driven decisions and to ensure that the development is focused on features that provide real value for customers. Short feedback loops are a prerequisite as they allow for fast learning and reduced reaction times. Continuous experimentation is a development practice where the entire R&D process is guided by constantly conducting experiments and collecting feedback. Although principles of continuous experimentation have been successfully applied in domains such as game software or SAAS, it is not obvious how to transfer continuous experimentation to the business to-business domain. In this article, a case study from a medium-sized software company in the B2B domain is presented. The study objective is to analyze the challenges, benefits and organizational aspects of continuous experimentation in the B2B domain. The results suggest that technical challenges are only one part of the challenges a company encounters in this transition. The company also has to address challenges related to the customer and organizational culture. Unique properties in each customers business play a major role and need to be considered when designing experiments. Additionally, the speed by which experiments can be conducted is relative to the speed by which production deployments can be made. Finally, the article shows how the study results can be used to modify the development in the case company in a way that more feedback and data is used instead of opinions.
Due to frequently changing requirements, the internal structure of cloud services is highly dynamic. To ensure flexibility, adaptability, and maintainability for dynamically evolving services, modular software development has become the dominating paradigm. By following this approach, services can be rapidly constructed by composing existing, newly developed and publicly available third-party modules. However, newly added modules might be unstable, resource-intensive, or untrustworthy. Thus, satisfying non-functional requirements such as reliability, efficiency, and security while ensuring rapid release cycles is a challenging task. In this paper, we discuss how to tackle these issues by employing container virtualization to isolate modules from each other according to a specification of isolation constraints. We satisfy non-functional requirements for cloud services by automatically transforming the modules comprised into a container-based system. To deal with the increased overhead that is caused by isolating modules from each other, we calculate the minimum set of containers required to satisfy the isolation constraints specified. Moreover, we present and report on a prototypical transformation pipeline that automatically transforms cloud services developed based on the Java Platform Module System into container-based systems.
Fitting 3D Morphable Face Models (3DMM) to a 2D face image allows the separation of face shape from skin texture, as well as correction for face expression. However, the recovered 3D face representation is not readily amenable to processing by convolutional neural networks (CNN). We propose a conformal mapping from a 3D mesh to a 2D image, which makes these machine learning tools accessible by 3D face data. Experiments with a CNN based face recognition system designed using the proposed representation have been carried out to validate the advocated approach. The results obtained on standard benchmarking data sets show its promise.
Combining agile development and software product lines in automotive: challenges and recommendations
(2018)
Software product lines (SPLs) are used throughout the automotive industry. SPLs help to manage the large number of variants and to improve quality by reuse. In order to develop high quality software faster, agile software development (ASD) practices are introduced. From both the research and the management point of view it is still not clear how these two approaches can be combined. We derive recommendations to combine ASD and SPLs based on challenges identified for an automotive specific model. This study combines the outcome of a literature review and a qualitative interview study with 16 practitioners from the automotive domain. We evaluate the results and analyze the relationship between ASD and SPLs in the automotive domain. Furthermore, we derive recommendations to combine ASD and SPLs based on challenges identified in the automotive domain. This study identifies 86 individual challenges. Important challenges address supplier collaboration and faster software release cycles without loss of quality. The identified challenges and the derived recommendations show that the combination of ASD and SPL in the automotive industry is promising but not trivial. There is a need for an automotive-specific approach that combines ASD and SPL.
We present a new method for detecting gait disorders according to their stadium using cluster methods for sensor data. 21 healthy and 18 Parkinson subjects performed the time up and go test. The time series were segmented into separate steps. For the analysis the horizontal acceleration measured by a mobile sensor system was considered. We used dynamic time warping and hierarchical custering to distinguish the stadiums. A specificity of 92% was achieved.
Advanced power semiconductors such as DMOS transistors are key components of modern power electronic systems. Recent discrete and integrated DMOS technologies have very low area-specific on-state resistances so that devices with small sizes can be chosen. However, their power dissipation can sometimes be large, for example in fault conditions, causing the device temperature to rise significantly. This can lead to excessive temperatures, reduced lifetime, and possibly even thermal runaway and subsequent destruction. Therefore, it is required to ensure already in the design phase that the temperature always remains in an acceptable range. This paper will show how self-heating in DMOS transistors can be experimentally determined with high accuracy. Further, it will be discussed how numerical electrothermal simulations can be carried out efficiently, allowing the accurate assessment of self-heating within a few minutes. The presented approach has been successfully verified experimentally for device temperatures exceeding 500 ◦C up to the onset of thermal runaway.
Organizations identified the opportunities of big data analytics to support the business with problem-specific insights through the exploitation of generated data. Sociotechnical solutions are developed in big data projects to reach competitive advantage. Although these projects are aligned to specific business needs, common architectural challenges are not addressed in a comprehensive manner. Enterprise architecture management is a holistic approach to tackle complex business and IT architectures. The transformation of an organization’s EA is influenced by big data transformation processes and their data-driven approach on all layers. In this paper, we review big data literature to analyze which requirements for the EA management discipline are proposed. Based on a systematic literature identification, conceptual categories of requirements for EA management are elicited utilizing an inductive category formation. These conceptual categories of requirements constitute a category system that facilitates a new perspective on EA management and fosters the innovation-driven evolution of the EA management.
discipline.
Non-fungible tokens (NFTs) are unique digital assets that have recently gained significant popularity, particularly in the digital art sector. The success of NFTs and other blockchain-based innovations depends on their ac-acceptance and use by consumers. This study aims to understand the impact of moral values on the acceptance of NFTs. Based on a quantitative survey with over 800 complete responses, the analysis shows that moral aspects of NFTs are indeed important for potential users. However, there is an attitude-behavior gap, as the positive impact of moral values on the intention to use NFTs is not reflected in the actual current usage of NFTs by the respondents. This study contributes to knowledge by providing new empirical data on the acceptance of NFTs and highlighting the role of moral values on the acceptance decision.
Bootstrap circuits are mainly used for supplying a gate driver circuit to provide the gate overdrive voltage for a high-side NMOS transistor. The required charge has to be provided by a bootstrap capacitor which is often too large for integration if an acceptable voltage dip at the capacitor has to be guaranteed. Three options of an area efficient bootstrap circuit for a high side driver with an output stage of two NMOS transistors are proposed. The key idea is that the main bootstrap capacitor is supported by a second bootstrap capacitor, which is charged to a higher voltage and connected when the gate driver turns on. A high voltage swing at the second capacitor leads to a high charge allocation. Both bootstrap capacitors require up to 70% less area compared to a conventional bootstrap circuit. This enables compact power management systems with fewer discrete components and smaller die size. A calculation guideline for optimum bootstrap capacitor sizing is given. The circuit was manufactured in a 180nm high-voltage BiCMOS technology as part of a high-voltage gate driver. Measurements confirm the benefit of high-voltage charge storing. The fully integrated bootstrap circuit including two stacked 75.8pF and 18.9pF capacitors results in a voltage dip lower than 1V. This matches well with the theory of the calculation guideline.
Size and cost of a boost converter can be minimized by reducing the voltage overshoot and fastening the transient response in case of load transient. The presented technique improves the transient response of a current mode controlled boost converter, which usually suffers from bandwidth limitation because of its right-half-plane zero (RHPZ). The proposed technique comprises a load current estimation which works as part of a digital controller without any additional measurements. Based on the latest load estimation the controller parameters are adapted, achieving small voltage overshoot and fast transient response. The presented technique was implemented in a digital control circuit, consisting of an ASIC in a 110 nm-technology, a Xilinx Spartan-6 field programmable gate array (FPGA), and a TI-ADS8422 analog to-digital-converter (ADC). Simulation and measurements of a 4V-to-6.3V, 500mA boost converter show an improvement of 50% in voltage overshoot and response time to load transient.
The EU funded project RobLog recently developed a system able to autonomously unload coffee sacks from a standard container. Being the first of its kind, a further development is needed in order for the system to be competitive against manual labor. Financing this development entails a risk, hence a justified skepticism, which can be overcome by the longsighted view of the existing market potential. This paper presents a method to estimate the market potential of autonomous unloading systems for heavy deformable goods. Starting from the analysis of the coffee trade, first the current coffee traffic is investigated in order to calculate the number of autonomous systems needed to handle the imported sacks; Results are validated and the method is extended for the calculation of the potential of other market segments, where the same unloading technology can be applied.
According to several surveys and statistics, the great majority of companies previously not accustomed to automation are piloting solutions to automate business processes. Those accustomed to automation also attempt to introduce more of it, focusing on automation-unfriendly processes that remained manual. However, when the decision on what and whether to automate is not trivial for evident reasons, even industry leaders may get stuck on an overwhelming question: where to begin automating? The question remains too often unanswered as state-of-the-art methods fail to consider the whole picture. This paper introduces a holistic approach to the decision-making for investments in automation. The method supports the iterative analysis and evaluation of operative processes, providing tools for a quantitative approach to the decision-making. Thanks to the method, a large pool of processes can be first considered and then filtered out in order to select the one that yields the best value for the automation in the specific context. After introducing the method, a case study is reported for validation before the discussion.
DMOS transistors often suffer from substantial self-heating during high power dissipation, which can lead to thermal destruction if the device temperature reaches excessive values. A successfully demonstrated method to reduce the peak temperature is the redistribution of power dissipation density from the hotter to the cooler device areas by careful layout modification. However, this is very tedious and time-consuming if complex-shaped devices as often found in industrial applications are considered.
This paper presents an approach for fully automatic layout optimization which requires only a few hours processing time. The approach is applied to complex shaped test structures which are investigated by measurements and electro-thermal simulations. Results show a significantly lower peak temperature and an energy capability gain of 84 %, offering potential for a 18 % size reduction of active area.
While Microservices promise several beneficial characteristics for sustainable long-term software evolution, little empirical research covers what concrete activities industry applies for the evolvability assurance of Microservices and how technical debt is handled in such systems. Since insights into the current state of practice are very important for researchers, we performed a qualitative interview study to explore applied evolvability assurance processes, the usage of tools, metrics, and patterns, as well as participants’ reflections on the topic. In 17 semi-structured interviews, we discussed 14 different Microservice-based systems with software professionals from 10 companies and how the sustainable evolution of these systems was ensured. Interview transcripts were analyzed with a detailed coding system and the constant comparison method.
We found that especially systems for external customers relied on central governance for the assurance. Participants saw guidelines like architectural principles as important to ensure a base consistency for evolvability. Interviewees also valued manual activities like code review, even though automation and tool support was described as very important. Source code quality was the primary target for the usage of tools and metrics. Despite most reported issues being related to Architectural Technical Debt (ATD), our participants did not apply any architectural or service-oriented tools and metrics. While participants generally saw their Microservices as evolvable, service cutting and finding an appropriate service granularity with low coupling and high cohesion were reported as challenging. Future Microservices research in the areas of evolution and technical debt should take these findings and industry sentiments into account.
For area reasons, NMOS transistors are preferred over PMOS for the pull-up path in gate drivers. Bootstrapping has to ensure sufficient NMOS gate overdrive. Especially in high-current gate drivers with large transistors, the bootstrap capacitor is too large for integration. This paper proposes three options of fully integrated bootstrap circuits. The key idea is that the main bootstrap capacitor is supported by a second bootstrap capacitor, which is charged to a higher voltage and ensures high charge allocation when the driver turns on. A capacitor sizing guideline and the overall driver implementation including a suitable charge pump for permanent driver activation is provided. A linear regulator is used for bootstrap supply and it also compensates the voltage drop of the bootstrap diode. Measurements from a testchip in 180 nm high-voltage BiCMOS confirm the benefit of high-voltage charge storing. The fully integrated bootstrap circuit with two stacked 75.8 pF and 18.9 pF capacitors results in an expected voltage dip of lower than 1 V. Both bootstrap capacitors require 70% less area compared to a conventional bootstrap circuit. Besides drivers, the proposed bootstrap can also be directly applied to power stages to achieve fully integrated switched mode power supplies or class-D output stages.
This paper reports an analysis of application and impact of FMEA on susceptibility of generic IT-networks. It is not new that in communication system, the frequency and the data transmission rate play a very important role. The rapid increase in miniaturization of electronic devices leads to very sensitivity against electromagnetic interference. Since the IT network with the data transfer rate makes a huge contribution to this development it is very important to monitor their functionality. Therefore, tests are performed to observe and ensure the data transfer rate of IT networks against IEMI. A fault tree model is presented and observed effects during radiation of disturbance on complex system by a HPEM interference sources are described using a continuous and consistent model of the physical layer to the application layer.
Steady state efficiency optimization techniques for induction motors are state of the art and various methods have already been developed. This paper provides new insights in the efficiency optimized operation in dynamic regime. The paper proposes an anticipative flux modification in order to decrease losses during torque and speed transients. These trajectories are analyzed based on a numerical study for different motors. Measurement results for one motor are given as well.
Modern wide bandgap power devices promise higher power conversion performance if the device can be operated reliably. As switching speed increases, the effects of parasitic ringing become more prominent, causing potentially damaging overvoltages during device turn-off. Estimating the expected additional voltage caused by such ringing enables more reliable designs. In this paper, we present an analytical expression to calculate the expected overvoltage caused by parasitic ringing based on parasitic element values and operating point parameters. Simulations and measurements confirm that the expression can be used to find the smallest rise time of the switches’ drain-source voltage for minimum overvoltage. The given expression also allows the prediction of the trade off overvoltage amplitude in case of faster required rise times.
The possibility to bring the interference source, close to the potential target is characterized by the property of the source as stationary, portable, mobile, very mobile and highly mobile [3]. Starting from the existing and well-known IEME interference or IEMI (Intentional Electromagnetic Interference) and the already existing classifications an analysis of methods based on a comparative study of the methods used to classify the intentional EM environment is carried out, which takes into account the frequency, the cost, the amplitude of the noise signal, the radiated power and the energy of a pulse of radiation.
This paper enhances SWARM, a novel deterministic analog layout automation approach based on the idea of cellular automata. SWARM implements a decentralized interaction model in which responsive layout modules, covering basic circuit types, autonomously move, rotate and deform themselves to let constraint-compliant, compact layout solutions emerge from a synergetic flow of self-organization. With the ability to consider design constraints both implicitly and explicitly, SWARM joins the layout quality of procedural generators with the flexibility of optimization algorithms, combining these two kinds of automation into a “bottom-up meets top-down” flow. The new enhancements are demonstrated in an OTA example, depicting the power of SWARM and its enormous potential for future developments.
An ultra-low power capacitance extrema and ratio detector for electrostatic energy harvesters
(2015)
The power supply is one of the major challenges for applications like internet of things IoTs and smart home. The maintenance issue of batteries and the limited power level of energy harvesting is addressed by the integrated micro power supply presented in this paper. Connected to the 120/230 Vrms mains, which is one of the most reliable energy sources and anywhere indoor available, it provides a 3.3V DC output voltage. The micro power supply consists of a fully integrated ACDC and DCDC converter with one external low voltage SMD buffer capacitor. The micro power supply is fabricated in a low cost 0.35 μm 700 V CMOS technology and covers a die size of 7.7 mm2. The use of only one external low voltage SMD capacitor, results in an extremely compact form factor. The ACDC is a direct coupled, full wave rectifier with a subsequent bipolar shunt regulator, which provides an output voltage around 17 V. The DCDC stage is a fully integrated 4:1 SC DCDC converter with an input voltage as high as 17 V and a peak efficiency of 45 %. The power supply achieves an overall output power of 3 mW, resulting in a power density of 390 μW/mm2. This exceeds prior art by a factor of 11.
This paper presents a compact four-arm spiral antenna, which may be used in direction-finding applications but also mobile communication systems. The antenna is fed sequentially at its outside-ends using a sequential phase network embedded in grounded multilayer dielectric media. Sequential rotation is applied to generate the axial mode M1 but also the conical mode M2 in the same frequency band. The antenna exhibits good radiation characteristics in the frequency band of interest.
This paper presents a laboratory experiment integrating the fields of electronics design, power electronics and drive control. The aim of this experiment is first to illustrate the need for a deep knowledge and the challenges in power electronics and its applications, in this particular case for drive control. The different tasks in this experiment are executed on a complete setup for a brushless dc motor test bench. The tasks assigned to the students are designed such that, in some tasks the knowledge from a particular field, power electronics, electronic design or drive control is deepened, whereas in other tasks the knowledge from more than one of these fields is needed to solve the given problem. Thus, the experiment trains students in the particular domains but illustrates as well the links between power electronics, electronic design and drive control.
The maintenance issue of batteries and the limited power level of energy harvesting is addressed by the presented integrated micropower supply. Connected to the 120/230-VRMS mains, it provides a 3.3-V ac output voltage, suitable for applications such as the Internet-of Things and smart homes. The micropower supply consists of a fully integrated ac–dc and dc–dc converter with one external low-voltage surface mount device buffer capacitor, resulting in an extremely compact size. Fabricated in a low-cost 0.35-μm 700-V complimentary metal-oxide-semiconductor technology, it covers a die size of 7.7 mm². The ac–dc converter is a direct coupled, full-wave rectifier with a subsequent series regulator. The dc–dc stage is a fully integrated capacitive 4:1 converter with up to 17-V input and 47.4% peak efficiency. The power supply comprises several high-voltage control circuits including level shifters and various types of charge pumps (CPs). A source supplied CP is utilized that supports a varying switching node potential. The overall losses are discussed and optimized, including flying capacitor bottom-plate losses. The power supply achieves an output power of 3 mW, resulting in a power density of 390 μW/mm². This exceeds prior art by a factor of 11.
For a long time, most discrete accelerators have been attached to host systems using various generations of the PCI Express interface. However, with its lack of support for coherency between accelerator and host caches, fine-grained interactions require frequent cache-flushes, or even the use of inefficient uncached memory regions. The Cache Coherent Interconnect for Accelerators (CCIX) was the first multi-vendor standard for enabling cache-coherent host-accelerator attachments, and already is indicative of the capabilities of upcoming standards such as Compute Express Link (CXL). In our work, we compare and contrast the use of CCIX with PCIe when interfacing an ARM-based host with two generations of CCIX-enabled FPGAs. We provide both low-level throughput and latency measurements for accesses and address translation, as well as examine an application-level use-case of using CCIX for fine-grained synchronization in an FPGA-accelerated database system. We can show that especially smaller reads from the FPGA to the host can benefit from CCIX by having roughly 33% shorter latency than PCIe. Small writes to the host have a latency roughly 32% higher than PCIe, though, since they carry a higher coherency overhead. For the database use-case, the use of CCIX allowed to maintain a constant synchronization latency even with heavy host-FPGA parallelism.
This paper presents an efficient implementation of a reconfigurable battery stack which allows full exploitation of the capacity of every single cell. Contrary to most other approaches, it is possible to electrically remove one or more cells from the battery stack. Therefore, the overall capacity of the system is not restricted by the weaker cells, and cells with very different states of health can be used, making the system very attractive for refurbished batteries. For the required switches, low-voltage high-current MOSFETs are used. A demonstrator has been built with a total capacity of up to 3.5 kWh, a nominal voltage of 35 V, and currents up 200 A.
DMOS transistors are often subject to high power dissipation and thus substantial self-heating. This limits their safe operating area because very high device temperatures can lead to thermal runaway and subsequent destruction. Because the peak temperature usually occurs only in a small region in the device, it is possible to redistribute part of the dissipated power from the hot region to the cooler device areas. In this way, the peak temperature is reduced, whereas the total power dissipation is still the same. Assuming that a certain temperature must not be exceeded for safe operation, the improved device is now capable of withstanding higher amounts of energy with an unchanged device area. This paper presents two simple methods to redistribute the power dissipation density and thus lower the peak device temperature. The presented methods only require layout changes. They can easily be applied to modern power technologies without the need of process modifications. Both methods are implemented in test structures and investigated by simulations and measurements.
An assessment model to foster the adoption of agile software product lines in the automotive domain
(2018)
A software product line is commonly used for the software development in large automotive organizations. A strategic reuse of software is needed to handle the increasing complexity of the development and to maintain the quality of numerous software variants. However, the development process needs to be continuously adapted at a fast pace to satisfy the changing market demands. Introducing agile software development methods promise the flexibility to react on customers’ change requests and market demands to deliver high quality software. Despite this need, it is still challenging to combine agile software development and product lines. The maturity of an agile adoption is often hard to determine. Assessing the current situation regarding the combination is a first step towards a successful inclusion of agile methods into automotive software product lines. Based on an interview study with 16 participants and a literature review, we build the so-called ASPLA Model allowing self-assessments within the team to determine the current state of agile software development in combination with software product lines. The model comprises seven areas of improvement and recommends a possibility to improve the current status.
Gallium nitride high electron mobility transistors (GaN-HEMTs) have low capacitances and can achieve low switching losses in applications where hard turn-on is required. Low switching losses imply a fast switching; consequently, fast voltage and current transients occur. However, these transients can be limited by package and layout parasitics even for highly optimized systems. Furthermore, a fast switching requires a fast charging of the input capacitance, hence a high gate current.
In this paper, the switching speed limitations of GaN-HEMTs due to the common source inductance and the gate driver supply voltage are discussed. The turn-on behavior of a GaN-HEMT is simulated and the impact of the parasitics and the gate driver supply voltage on the switching losses is described in detail. Furthermore, measurements are performed with an optimized layout for a drain-source voltage of 500 V and a drain-source current up to 60 A.
Enterprises and information societies confront crucial challenges currently, while Industry 4.0 becomes important in the global manufacturing industry and Society 5.0 should contribute to a supersmart society, especially for healthcare. Physical activity monitoring digital platforms are architected to improve the healthcare status of patients with diabetes and other lifestyle-related diseases. Furthermore, digital platforms are expected to generate profits for health technology companies and help control costs in the healthcare ecosystem. However, current digital enterprise architecture approaches are not well-established, and the potentials have not yet been realized. Design thinking approach and agile software development methodologies can overcome these limitations, beginning with proof of concept and pilot projects and then scaling to the production environment. In this paper, we describe how that the adaptive integrated digital architecture framework (AIDAF) for Design Thinking approach is proposed and verified in a case of a university hospital in the Americas. In addition, challenges and future activities for this area are discussed that cover the directions for Society 5.0.
We propose a novel technique to compensate the effects of R-C / gm-C time-constant (TC) errors due to process variation in continuous-time delta-sigma modulators. Local TC error compensation factors are shifted around in the modulator loop to positions where they can be implemented efficiently with tunable circuit structures, such as current-steering digital-to-analog converters (DAC). This approach constitutes an alternative or supplement to existing compensation techniques, including capacitor or gm tuning. We apply the proposed technique to a third-order, single-bit, low-pass continuous-time delta-sigma modulator in cascaded integrator feedback structure. A feedback path tuning scheme is derived analytically and confirmed numerically using behavioral simulations. The modulator circuit was implemented in a 0.35-μm CMOS process using an active feedback coefficient tuning structure based on current-steering DACs. Post-layout simulations show that with this tuning structure, constant performance and stable operation can be obtained over a wide range of TC variation.
A highly integrated synchronous buck converter with a predictive dead time control for input voltages >18 V with 10 MHz switching frequency is presented. A high resolution dead time of ˜125 ps allows to reduce dead time dependent losses without requiring body diode conduction to evaluate the dead time. High resolution is achieved by frequency compensated sampling of the switching node and by an 8 bit differential delay chain. Dead time parameters are derived in a comprehensive study of dead time depended losses. This way, the efficiency of fast switching DC-DC converters can be optimized by eliminating the body diode forward conduction losses, minimizing reverse recovery losses and by achieving zero voltage switching. High-speed circuit blocks for fast switching operation are presented including level shifter, gate driver, PWM generator. The converter has been implemented in a 180 nm high-voltage BiCMOS technology.
Large critical systems, such as those created in the space domain, are usually developed by a large number of organizations and, furthermore, they have to comply with standards. Yet, the different stakeholders often do not have a common understanding of the needed quality of requirements specifications. Achieving such a common understanding is a laborious process that is currently not sufficiently supported. Moreover, such a common understanding must be aligned with the standards. In this paper, we present an approach that can be used to align the different stakeholder perceptions regarding the quality of requirements specifications. Existing quality models for requirements specifications are analyzed for equivalences, and transferred into a common representation, the so-called Aligned Quality Map (AQM). Furthermore, a process is defined that supports the alignment of different stakeholder perspectives with regard to the quality of requirements specifications using AQM, which is validated in a case study in the context of European space projects. AQM has been created and populated with an initial set of quality models. It is designed in such way that it can be extended to include further quality models. The case study has shown that an alignment of different stakeholder perspectives and the quality model of the European Cooperation for Space Standardization using AQM is feasible. The approach allows for aligning different stakeholder perspectives for a common understanding of the quality of requirements specifications in the context of standards. Furthermore, AQM supports the assessment of requirements specifications.
Providing a digital infrastructure, platform technologies foster interfirm collaboration between loosely coupled companies, enabling the formation of ecosystems and building the organizational structure for value co-creation. Despite the known potential, the development of platform ecosystems creates new sources of complexity and uncertainty due to the involvement of various independent actors. For a platform ecosystem to succeed, it is essential that the platform ecosystem participants are aligned, coordinated, and given a common direction. Traditionally, product roadmaps have served these purposes during product development. A systematic mapping study was conducted to better understand how product roadmapping could be used in the dynamic environment of platform ecosystems. One result of the study is that there are hardly any concrete approaches for product roadmapping in platform ecosystems so far. However, many challenges on the topic are described in the literature from different perspectives. Based on the results of the systematic mapping study, a research agenda for product roadmapping in platform ecosystems is derived and presented.