311,142 research outputs found

    Towards Multidimensional Verification: Where Functional Meets Non-Functional

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    Trends in advanced electronic systems' design have a notable impact on design verification technologies. The recent paradigms of Internet-of-Things (IoT) and Cyber-Physical Systems (CPS) assume devices immersed in physical environments, significantly constrained in resources and expected to provide levels of security, privacy, reliability, performance and low power features. In recent years, numerous extra-functional aspects of electronic systems were brought to the front and imply verification of hardware design models in multidimensional space along with the functional concerns of the target system. However, different from the software domain such a holistic approach remains underdeveloped. The contributions of this paper are a taxonomy for multidimensional hardware verification aspects, a state-of-the-art survey of related research works and trends towards the multidimensional verification concept. The concept is motivated by an example for the functional and power verification dimensions.Comment: 2018 IEEE Nordic Circuits and Systems Conference (NORCAS): NORCHIP and International Symposium of System-on-Chip (SoC

    Towards a Systematic Approach for Smart Grid Hazard Analysis and Experiment Specification

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    The transition to the smart grid introduces complexity to the design and operation of electric power systems. This complexity has the potential to result in safety-related losses that are caused, for example, by unforeseen interactions between systems and cyber-attacks. Consequently, it is important to identify potential losses and their root causes, ideally during system design. This is non-trivial and requires a systematic approach. Furthermore, due to complexity, it may not possible to reason about the circumstances that could lead to a loss; in this case, experiments are required. In this work, we present how two complementary deductive approaches can be usefully integrated to address these concerns: Systems Theoretic Process Analysis (STPA) is a systems approach to identifying safety-related hazard scenarios; and the ERIGrid Holistic Test Description (HTD) provides a structured approach to refine and document experiments. The intention of combining these approaches is to enable a systematic approach to hazard analysis whose findings can be experimentally tested. We demonstrate the use of this approach with a reactive power voltage control case study for a low voltage distribution network.Comment: 2020 IEEE 18th International Conference on Industrial Informatics (INDIN

    Power-Electronic-Based DC Distribution Systems for Electrically Propelled Vessels: A multivariable Modeling Approach for Design and Analysis

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    The benefits of using power-electronic-based dc distribution systems in electrically propelled vessels are well known. However, some aspects must be deeply analyzed to guarantee a safe, robust, and stable system by design. This paper presents a multivariable dc distribution system mathematical model, where all the transmission lines and filters impedances are considered. The model has been tackled under a holistic approach in which the average small-signal model of the drives/converters can be easily added and “connected” to the main grid model. The stability and power quality analysis, as well as the design and tuning of controls and active damping strategies, can be conducted through this mathematical model at low computational cost. In this paper, the usefulness of this model in the early design stages is presented through its application over a realistic design scenario. Moreover, the performance of the proposed model is proven into a real test bench, which presents a configuration and architecture quite close to the one used in a real vessel. The carried out tests prove the suitability of the proposed model, becoming a significant tool to get an improved design

    Understanding multidimensional verification: Where functional meets non-functional

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    Abstract Advancements in electronic systems' design have a notable impact on design verification technologies. The recent paradigms of Internet-of-Things (IoT) and Cyber-Physical Systems (CPS) assume devices immersed in physical environments, significantly constrained in resources and expected to provide levels of security, privacy, reliability, performance and low-power features. In recent years, numerous extra-functional aspects of electronic systems were brought to the front and imply verification of hardware design models in multidimensional space along with the functional concerns of the target system. However, different from the software domain such a holistic approach remains underdeveloped. The contributions of this paper are a taxonomy for multidimensional hardware verification aspects, a state-of-the-art survey of related research works and trends enabling the multidimensional verification concept. Further, an initial approach to perform multidimensional verification based on machine learning techniques is evaluated. The importance and challenge of performing multidimensional verification is illustrated by an example case study

    A Multilevel Introspective Dynamic Optimization System For Holistic Power-Aware Computing

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    Power consumption is rapidly becoming the dominant limiting factor for further improvements in computer design. Curiously, this applies both at the "high end" of workstations and servers and the "low end" of handheld devices and embedded computers. At the high-end, the challenge lies in dealing with exponentially growing power densities. At the low-end, there is a demand to make mobile devices more powerful and longer lasting, but battery technology is not improving at the same rate that power consumption is rising. Traditional power-management research is fragmented; techniques are being developed at specific levels, without fully exploring their synergy with other levels. Most software techniques target either operating systems or compilers but do not explore the interaction between the two layers. These techniques also have not fully explored the potential of virtual machines for power management. In contrast, we are developing a system that integrates information from multiple levels of software and hardware, connecting these levels through a communication channel. At the heart of this system are a virtual machine that compiles and dynamically profiles code, and an optimizer that reoptimizes all code, including that of applications and the virtual machine itself. We believe this introspective, holistic approach enables more informed power-management decisions

    Modeling energy supply unit of ultra-low power devices with indoor photovoltaic harvesting

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    Challenges in the field of logistics have pushed development and integration of cyber-physical systems in these applications. PhyNode as one of these systems has shown promising results for enabling a transportation box with intelligence. However, engineering shortcomings during its development and implementation have shown potential for further research topics. Among them, balancing the Energy Supply Unit (ESU) to avoid periodic battery recharge is the main motivation of this work addressed by its modeling. For a systematic analysis of PhyNode's ESU, two types of models are developed for each of its three modules, including: Indoor photovoltaic harvesting (IPV), power management device and the battery. First type of models are computationally lightweight for on-board monitoring implementation. In contrary, system level detailed models are more advanced and computationally intensive. They are used to properly dimension the hardware or optimize the operational process during system design phase. At first IPV devices are analyzed extensively to highlight their differences from solar applications. In addition to the development of a high precision measurement platform for measurement of IPV behavior, collected data is used for model development. Due to wide range of signals, a normalized space is introduced in addition to guidelines for model's parameters estimation. Moreover, a new evaluation criteria is suggested enabling comparison of model's performance in different environmental situations. A battery measurement setup is introduced for analyzing battery with ultra-low power loads. In addition to the comparison of different battery identification methods, effect of aging on the battery performance has been analyzed. By measurement of PhyNode's load, both developed models are evaluated showing error less than 0.5% on estimation of the models' output. Furthermore, internal structure of power management device designed for ultra-low power applications is analyzed. Converter and maximum power point tracking as two main parts of this system are modeled separately. Despite suggestion of a partial model based on physical principles of converter, lack of design information leads to a black-box modeling approach. Therefore, two machine learning based models are developed for these parts. Combined model of them is tested on an evaluation data-set, showing a performance with a RMSE of 1.2%. Finally, a holistic model including all modules builds the overall structure of PhyNode's ESU. This model is tested with real data from different hardware combinations of PhyNode in action for long time periods showing a MAPE less than 1%. Due to the high accuracy of developed model, it is used for simulation of PhyNode in a real world scenarios. In addition, potentials of holistic model are shown by simulating energy balancing after different changes in either hardware or operational process of PhyNode

    Towards a foundation for holistic power system validation and testing

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    Renewable energy sources and further electrificationof energy consumption are key enablers for decreasing green-house gas emissions, but also introduce increased complexitywithin the electric power system. The increased availability ofautomation, information and communication technology, andintelligent solutions for system operation have transformed thepower system into a smart grid. In order to support thedevelopment process of smart grid solutions on the system level,testing has to be done in a holistic manner, covering the multi-domain aspect of such complex systems. This paper introducesthe concept of holistic power system testing and discuss first stepstowards a corresponding methodology that is being developed inthe European ERIGrid research infrastructure project.Comment: 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA

    ERIGrid Holistic Test Description for Validating Cyber-Physical Energy Systems

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    Smart energy solutions aim to modify and optimise the operation of existing energy infrastructure. Such cyber-physical technology must be mature before deployment to the actual infrastructure, and competitive solutions will have to be compliant to standards still under development. Achieving this technology readiness and harmonisation requires reproducible experiments and appropriately realistic testing environments. Such testbeds for multi-domain cyber-physical experiments are complex in and of themselves. This work addresses a method for the scoping and design of experiments where both testbed and solution each require detailed expertise. This empirical work first revisited present test description approaches, developed a newdescription method for cyber-physical energy systems testing, and matured it by means of user involvement. The new Holistic Test Description (HTD) method facilitates the conception, deconstruction and reproduction of complex experimental designs in the domains of cyber-physical energy systems. This work develops the background and motivation, offers a guideline and examples to the proposed approach, and summarises experience from three years of its application.This work received funding in the European Community’s Horizon 2020 Program (H2020/2014–2020) under project “ERIGrid” (Grant Agreement No. 654113)
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