The importance of accurate battery models for power assessment in smart energy systems

The smart energy system is characterized by a broader combination of various energy sources and energy storage devices with smart control management and increased attention to optimization for increasing energy efficiency. The fundamental dimension in the smart energy system design is the power assessment of the possible design architecture. This demand imposes a need for accurately tracking the system’s power flow, simulating and validating the system’s behavior, and applying additional optimization and exploration during the design time. Thus, it is evident that simulation is a critical step in the design flow of a smart energy system. One essential element to enable such accurate simulation is the precise model of the power generation and consumption. While sophisticated models for energy sources exist, the power flow in the system does not perfectly match the power drawn from the energy storage devices because the battery, as the primary energy storage device in the smart energy system, has non-ideal discharge characteristics. We propose adopting an elaborate battery model for the smart energy system’s accurate power assessment in this work. We show the importance of battery model accuracy when conducting a power assessment using two different case studies

Modeling Cyber-Physical Production Systems with SystemC-AMS

The heterogeneous nature of SystemC-AMS makes it a perfect candidate solution to support Cyber-Physical Production Systems (CPPSs), i.e., systems that are characterized by a tight interaction of the cyber part with the surrounding physical world and with manufacturing production processes. Nonetheless, the support for the modeling of physical and mechanical dynamics typical of production machinery goes far beyond the initial application scenario of SystemC-AMS, thus limiting its effectiveness and adoption in the production and manufacturing context. This paper starts with an analysis of the current adoption of SystemC-AMS to highlight the open points that still limit its effectiveness, with the goal of pinpointing current issues and to propose solutions that could improve its effectiveness, and make SystemC-AMS an essential resource also in the new Industry 4.0 scenario

Semi-Automatic Generation of Device Drivers for Rapid Embedded Platform Development

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IP-XACT for Smart Systems Design: Extensions for the Integration of Functional and Extra-Functional Models

Smart systems are miniaturized devices integrating computation, communication, sensing and actuation. As such, their design can not focus solely on functional behavior, but it must rather take into account different extra-functional concerns, such as power consumption or reliability. Any smart system can thus be modeled through a number of views, each focusing on a specific concern. Such views may exchange information, and they must thus be simulated simultaneously to reproduce mutual influence of the corresponding concerns. This paper shows how the IP-XACT standard, with some necessary extensions, can effectively support this simultaneous simulation. The extended IP-XACT descriptions allow to model extra-functional properties with a homogeneous format, defined by analysing requirements and characteristic of three main concerns, i.e., power, temperature and reliability. The IP-XACT descriptions are then used to automatically generate a skeleton of the simulation infrastructure in SystemC. The skeleton can be easily populated with models available in the literature, thus reaching simultaneous simulation of multiple concerns

SystemC-AMS thermal modeling for the co-simulation of functional and extra-functional properties

Temperature is a critical property of smart systems, due to its impact on reliability and to its inter-dependence with power consumption. Unfortunately, the current design flows evaluate thermal evolution ex-post, on offline power traces. This does not allow to consider temperature as a dimension in the design loop, and it misses all the complex inter-dependencies with design choices and power evolution. In this paper, by adopting the functional language SystemC-AMS, we propose a method to enable thermal/power/functional co-simulation. The system thermal model is built by using state-of-the-art circuit equivalent models, by exploiting the support for electrical linear networks intrinsic of SystemC-AMS. The experimental results will show that the choice of SystemC-AMS is a winning strategy for building a simultaneous simulation of multiple functional and extra-functional properties of a system. The generated code exposes an accuracy comparable to that of the reference thermal simulator HotSpot. Additionally, the initial overhead due to the general purpose nature of SystemC-AMS is compensated by surprisingly high performance of transient simulation, with speedups as high as two orders of magnitude

A Compact PV Panel Model for Cyber-Physical Systems in Smart Cities

One of the ambitious goals of the ‘‘Smart city’’ paradigm is to design zero-energy buildings. Buildings can be considered as connected cyber-physical systems that require the construction of sound methodologies inherited from the Electronic Design Automation (EDA) research. In particular, aiming at autonomous buildings, the effective design of renewable energy sources is a key aspect for which such methodologies have to be developed. In this work, we propose a modeling strategy for the early estimation of the performance of photovoltaic (PV) arrays. Although a plethora of PV panel models there exists, most of these models suffer from accuracy/complexity tradeoffs. On one hand, building fast models forces to ignore either the correlation between temperature and irradiance, or the topology of panels, thus yielding inaccurate estimations. On the other, more accurate models are time consuming and require costly measurements or circuit analysis, that cannot be extracted from the sole datasheet. This paper proposes a compact semi-empirical model, suitable for real time simulation and built solely from information derived from the PV panel datasheet. The model is built by empirically fitting an expression of the panel operating point as a function of both irradiance and temperature, and of the adopted PV system topology. The accuracy and effectiveness of the proposed model have been validated w.r.t. the production traces of the PV systems of a real world industrial building

HDTLib: an efficient implementation of SystemC data types for fast simulation at different abstraction levels

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Multi-Domain Fault Models Covering the Analog Side of a Smart or Cyber-Physical System

Over the last decade, the industrial world has been involved in a massive revolution guided by the adoption of digital technologies. In this context, complex systems like cyber-physical systems play a fundamental role since they were designed and realized by composing heterogeneous components. The combined simulation of the behavioral models of these components allows to reproduce the nominal behavior of the real system. Similarly, a smart system is a device that integrates heterogeneous components but in a miniaturized form factor. The development of smart or cyber-physical systems, in combination with faulty behaviors modeled for the different physical domains composing the system, enables to support advanced functional safety assessment at the system level. A methodology to create and inject multi-domain fault models in the analog side of these systems has been proposed by exploiting the physical analogy between the electrical and mechanical domains to infer a new mechanical fault taxonomy. Thus, standard electrical fault models are injected into the electrical part, while the derived mechanical fault models are injected directly into the mechanical part. The entire flow has been applied to two case studies: a direct current motor connected with a gear train, and a three-axis accelerometer

Design of District-level Photovoltaic Installations for Optimal Power Production and Economic Benefit

PhotoVoltaic (PV) installations are a widespreadsource of renewable energy, and are quite common urbanbuildings’ roofs. To soften both the initial investment and therecurrent maintenance costs, the current market trends delegatethe construction of PV installations toEnergy Aggregators, i.e.,grouping of consumers and producers that act as a single entityto satisfy local energy demand and to sell the surplus energy tothe grid. In this perspective, PV installations can be designedwith a larger perspective, i.e.,at district level, to maximize powerproduction not of a single building but rather of a number ofblocks of a city. This implies new challenges, including efficientdata management (the covered area can be squared kilometerswide) and optimal PV installation (the number of PV modulescan be in the order of hundreds or even thousands). Thispaper proposes a framework to combine detailed geographic andirradiance information to determine anoptimal PV installationover a district, by maximizing both power production and economicconvenience. Our simulation results run on a real-world districtprove that the framework allows an advanced evaluation of costsand benefit, that can be used by Energy Aggregators to design anew PV installation, and demonstrate an improvement on powergeneration up to 20% w.r.t. standard installations

A Cross-level Verification Methodology for Digital IPs Augmented with Embedded Timing Monitors

Smart systems are characterized by the integration in a single device of multi-domain subsystems of different technological domains, namely, analog, digital, discrete and power devices, MEMS, and power sources. Such challenges, emerging from the heterogeneous nature of the whole system, combined with the traditional challenges of digital design, directly impact on performance and on propagation delay of digital components. This article proposes a design approach to enhance the RTL model of a given digital component for the integration in smart systems with the automatic insertion of delay sensors, which can detect and correct timing failures. The article then proposes a methodology to verify such added features at system level. The augmented model is abstracted to SystemC TLM, which is automatically injected with mutants (i.e., code mutations) to emulate delays and timing failures. The resulting TLM model is finally simulated to identify timing failures and to verify the correctness of the inserted delay monitors. Experimental results demonstrate the applicability of the proposed design and verification methodology, thanks to an efficient sensor-aware abstraction methodology, by applying the flow to three complex case studies