Forecasting the grid power demand of charging stations from EV drivers’ attitude

In recent years there has been a significant increase in the production of electric vehicles (EVs), in the global strive to reduce polluting gases produced by conventional fossil-fuel driven vehicles. Therefore, many optimization algorithms have been proposed for EV mobility and the charging of battery packs in the stations connected to power grids. However, there are situations in which experimental results are not sufficient, and simulations are needed. In this work, we address the effects of the charge demands of an EV fleet on the grid by considering the attitude of EV drivers, and especially their range anxiety. This influences their decision of when to recharge the battery pack. To this end, an agent-based model has been developed for the simulation of a power grid considering different scenarios based mainly on the state of charge (SOC) of battery packs at the time of the charging requests of EVs at service stations. The results indicate that in general a high battery SOC at the beginning of charging increases the probability of reaching higher power peaks on the grid

Modeling of thermally induced skew variations in clock distribution network

Clock distribution network is sensitive to large thermal gradients on the die as the performance of both clock buffers and interconnects are affected by temperature. A robust clock network design relies on the accurate analysis of clock skew subject to temperature variations. In this work, we address the problem of thermally induced clock skew modeling in nanometer CMOS technologies. The complex thermal behavior of both buffers and interconnects are taken into account. In addition, our characterization of the temperature effect on buffers and interconnects provides valuable insight to designers about the potential impact of thermal variations on clock networks. The use of industrial standard data format in the interface allows our tool to be easily integrated into existing design flow

Automated Segmentation of Cells with IHC Membrane Staining

This study presents a fully automated membrane segmentation technique for immunohistochemical tissue images with membrane staining, which is a critical task in computerized immunohistochemistry (IHC). Membrane segmentation is particularly tricky in immunohistochemical tissue images because the cellular membranes are visible only in the stained tracts of the cell, while the unstained tracts are not visible. Our automated method provides accurate segmentation of the cellular membranes in the stained tracts and reconstructs the approximate location of the unstained tracts using nuclear membranes as a spatial reference. Accurate cell-by-cell membrane segmentation allows per cell morphological analysis and quantification of the target membrane proteins that is fundamental in several medical applications such as cancer characterization and classification, personalized therapy design, and for any other applications requiring cell morphology characterization. Experimental results on real datasets from different anatomical locations demonstrate the wide applicability and high accuracy of our approach in the context of IHC analysi

A Li-ion battery charge protocol with optimal aging-quality of service trade-off

The reduction of usable capacity of rechargeable batteries can be mitigated during the charge process by acting on some stress factors, namely, the average state-of-charge (SOC) and the charge current. Larger values of these quantities cause an increased degradation of battery capacity, so it would be desirable to keep both as low as possible, which is obviously in contrast with the objective of a fast charge. However, by exploiting the fact that in most battery-powered systems the time during which it is plugged for charging largely exceeds the time required to charge, it is possible to devise appropriate charge protocols that achieve a good balance between fast charge and aging. In this paper we propose a charge protocol that, using an accurate estimate of the charging time of a battery and the statistical properties of the charge/discharge patterns, yields an optimal trade-off between aging and quality of service. The latter is measured in terms of the distance of the actual SOC from 100% at the end of the charge phase. Results show that the present method improves significantly over other similar protocols proposed in the literature

A Li-ion battery charge protocol with optimal aging-quality of service trade-off

The reduction of usable capacity of rechargeable batteries can be mitigated during the charge process by acting on some stress factors, namely, the average state-of-charge (SOC) and the charge current. Larger values of these quantities cause an increased degradation of battery capacity, so it would be desirable to keep both as low as possible, which is obviously in contrast with the objective of a fast charge. However, by exploiting the fact that in most battery-powered systems the time during which it is plugged for charging largely exceeds the time required to charge, it is possible to devise appropriate charge protocols that achieve a good balance between fast charge and aging. In this paper we propose a charge protocol that, using an accurate estimate of the charging time of a battery and the statistical properties of the charge/discharge patterns, yields an optimal trade-off between aging and quality of service. The latter is measured in terms of the distance of the actual SOC from 100% at the end of the charge phase. Results show that the present method improves significantly over other similar protocols proposed in the literature

Empirical derivation of upper and lower bounds of NBTI aging for embedded cores

In deeply scaled CMOS technologies, device aging causes transistor performance parameters to degrade over time. While reliable models to accurately assess these degradations are available for devices and circuits, the extension to these models for estimating the aging of microprocessor cores is not trivial and there is no well accepted model in the literature. This work proposes a methodology for deriving an NBTI-induced aging model for embedded cores. Since aging can only be determined on a netlist, we use an empirical approach based on characterizing the model using a set of open synthesizable embedded cores, which allows us to establish a link between the aging at the transistor level and the aging from the core perspective in terms of maximum frequency degradation. Using this approach, we were able to (1) prove the independence of the aging on the workloads which run by the cores, and (2) calculate upper and lower bounds for the “aging factor” that can be used for a generic embedded processor. Results show that our method yields very good accuracy in predicting the frequency degradation of cores due to NBTI aging effect, and can be used with confidence when the netlist of the cores is not available