In situ diagnostics and prognostics of solder fatigue in IGBT modules for electric vehicle drives

This paper proposes an in situ diagnostic and prognostic (D&P) technology to monitor the health condition of insulated gate bipolar transistors (IGBTs) used in EVs with a focus on the IGBTs' solder layer fatigue. IGBTs' thermal impedance and the junction temperature can be used as health indicators for through-life condition monitoring (CM) where the terminal characteristics are measured and the devices' internal temperature-sensitive parameters are employed as temperature sensors to estimate the junction temperature. An auxiliary power supply unit, which can be converted from the battery's 12-V dc supply, provides power to the in situ test circuits and CM data can be stored in the on-board data-logger for further offline analysis. The proposed method is experimentally validated on the developed test circuitry and also compared with finite-element thermoelectrical simulation. The test results from thermal cycling are also compared with acoustic microscope and thermal images. The developed circuitry is proved to be effective to detect solder fatigue while each IGBT in the converter can be examined sequentially during red-light stopping or services. The D&P circuitry can utilize existing on-board hardware and be embedded in the IGBT's gate drive unit.

Non-convex dynamic economic/environmental dispatch with plug-in electric vehicle loads

Electric vehicles are a key prospect for future transportation. A large penetration of electric vehicles has the potential to reduce the global fossil fuel consumption and hence the greenhouse gas emissions and air pollution. However, the additional stochastic loads imposed by plug-in electric vehicles will possibly introduce significant changes to existing load profiles. In his paper, electric vehicles loads are integrated into an 5-unit system using a non-convex dynamic dispatch model. The actual infrastructure characteristics including valve-point effects, load balance constrains and transmission loss have been included in the model. Multiple load profiles are comparatively studied and compared in terms of economic and environmental impacts in order o identify patterns to charge properly. The study as expected shows ha off-peak charging is the best scenario with respect to using less fuels and producing less emissions.

A self-learning teaching-learning based optimization for dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.

Analysis of electric vehicle charging using the traditional generation expansion planning analysis tool WASP-IV

Electric vehicles (EV) are proposed as a measure to reduce greenhouse gas emissions in transport and support increased wind power penetration across modern power systems. Optimal benefits can only be achieved, if EVs are deployed effectively, so that the exhaust emissions are not substituted by additional emissions in the electricity sector, which can be implemented using Smart Grid controls. This research presents the results of an EV roll-out in the all island grid (AIG) in Ireland using the long term generation expansion planning model called the Wien Automatic System Planning IV (WASP-IV) tool to measure carbon dioxide emissions and changes in total energy. The model incorporates all generators and operational requirements while meeting environmental emissions, fuel availability and generator operational and maintenance constraints to optimize economic dispatch and unit commitment power dispatch. In the study three distinct scenarios are investigated base case, peak and off-peak charging to simulate the impacts of EV’s in the AIG up to 2025.

Climatic signals in the life histories of insects:the distribution and abundance of heather psyllids (Strophingia spp.) in the UK

1. The population density and age structure of two species of heather psyllid Strophingia ericae and Strophingia cinereae, feeding on Calluna vulgaris and Erica cinerea, respectively, were sampled using standardized methods at locations throughout Britain. Locations were chosen to represent the full latitudinal and altitudinal range of the host plants.

2. The paper explains how spatial variation in thermal environment, insect life-history characteristics and physiology, and plant distribution, interact to provide the mechanisms that determine the range and abundance of Strophingia spp.

3. Strophingia ericae and S. cinereae, despite the similarity in the spatial distribution patterns of their host plants within Britain, display strongly contrasting geographical ranges and corresponding life-history strategies. Strophingia ericae is found on its host plant throughout Britain but S. cinereae is restricted to low elevation sites south of the Mersey-Humber line and occupies only part of the latitudinal and altitudinal range of its host plant. There is no evidence to suggest that S. ericae has reached its potential altitudinal or latitudinal limit in the UK, even though its host plant appears to reach its altitudinal limit.

4. There was little difference in the ability of the two Strophingia spp. to survive shortterm exposure to temperatures as low as - 15 degrees C and low winter temperatures probably do not limit distribution in S. cinereae.

5. Population density of S. ericae was not related to altitude but showed a weak correlation with latitude. The spread of larval instars present at a site, measured as an index of instar homogeneity, was significantly correlated with a range of temperature related variables, of which May mean temperature and length of growing season above 3 degrees C (calculated using the Lennon and Turner climatic model) were the most significant. Factor analysis did not improve the level of correlation significantly above those obtained for single climatic variables. The data confirmed that S. ericae has a I year life cycle at the lowest elevations and a 2 year life cycle at the higher elevations. However, there was no evidence, as previously suggested, for an abrupt change from a one to a 2 year life cycle in S. ericae with increasing altitudes or latitudes.

6. By contrast with S. ericae, S. cinereae had an obligatory 1 year life cycle, its population decreased with altitude and the index of instar homogeneity showed little correlation with single temperature variables. Moreover, it occupied only part of the range of its host plant and its spatial distribution in the UK could be predicted with 96% accuracy using selected variables in discriminant analysis.

7. The life histories of the congeneric heather psyllids reflect adaptations that allow them to exploit host plants with different distributions in climatic and thereby geographical space. Strophingia ericae has the flexible life history that enables it to exploit C. vulgaris throughout its European boreal temperate range. Strophingia cinereae has a less flexible life history and is adapted for living on an oceanic temperate host. While the geographic ranges of the two Strophingia spp. overlap within the UK, the psyllids appear to respond differently to variation in their thermal environment.

Electric vehicle capacity forecasting model with application to load levelling

There are many uncertainties in forecasting the charging and discharging capacity required by electric vehicles (EVs) often as a consequence of stochastic usage and intermittent travel. In terms of large-scale EV integration in future power networks this paper develops a capacity forecasting model which considers eight particular uncertainties in three categories. Using the model, a typical application of EVs to load levelling is presented and exemplified using a UK 2020 case study. The results presented in this paper demonstrate that the proposed model is accurate for charge and discharge prediction and a feasible basis for steady-state analysis required for large-scale EV integration.

Residential electrical vehicle charging strategies: the good, the bad and the ugly

In recent years, a wide variety of centralised and decentralised algorithms have been proposed for residential charging of electric vehicles (EVs). In this paper, we present a mathematical framework which casts the EV charging scenarios addressed by these algorithms as optimisation problems having either temporal or instantaneous optimisation objectives with respect to the different actors in the power system. Using this framework and a realistic distribution network simulation testbed, we provide a comparative evaluation of a range of different residential EV charging strategies, highlighting in each case positive and negative characteristics.

Interpreting signals from astrophysical transient experiments

Time domain astronomy has come of age with astronomers now able to monitor the sky at high cadence both across the electromagnetic spectrum and using neutrinos and gravitational waves. The advent of new observing facilities permits new science, but the ever increasing throughput of facilities demands efficient communication of coincident detections and better subsequent coordination among the scientific community so as to turn detections into scientific discoveries. To discuss the revolution occurring in our ability to monitor the Universe and the challenges it brings, on 2012 April 25-26 a group of scientists from observational and theoretical teams studying transients met with representatives of the major international transient observing facilities at the Kavli Royal Society International Centre, UK. This immediately followed the Royal Society Discussion meeting "New windows on transients across the Universe" held in London. Here we present a summary of the Kavli meeting at which the participants discussed the science goals common to the transient astronomy community and analysed how to better meet the challenges ahead as ever more powerful observational facilities come on stream.

RMA with quantile normalization mixes biological signals between different sample groups in microarray data analysis

Quantile normalization (QN) is a technique for microarray data processing and is the default normalization method in the Robust Multi-array Average (RMA) procedure, which was primarily designed for analysing gene expression data from Affymetrix arrays. Given the abundance of Affymetrix microarrays and the popularity of the RMA method, it is crucially important that the normalization procedure is applied appropriately. In this study we carried out simulation experiments and also analysed real microarray data to investigate the suitability of RMA when it is applied to dataset with different groups of biological samples. From our experiments, we showed that RMA with QN does not preserve the biological signal included in each group, but rather it would mix the signals between the groups. We also showed that the Median Polish method in the summarization step of RMA has similar mixing effect. RMA is one of the most widely used methods in microarray data processing and has been applied to a vast volume of data in biomedical research. The problematic behaviour of this method suggests that previous studies employing RMA could have been misadvised or adversely affected. Therefore we think it is crucially important that the research community recognizes the issue and starts to address it. The two core elements of the RMA method, quantile normalization and Median Polish, both have the undesirable effects of mixing biological signals between different sample groups, which can be detrimental to drawing valid biological conclusions and to any subsequent analyses. Based on the evidence presented here and that in the literature, we recommend exercising caution when using RMA as a method of processing microarray gene expression data, particularly in situations where there are likely to be unknown subgroups of samples.

LYRIC/AEG-1 is targeted to different subcellular compartments by ubiquitinylation and intrinsic nuclear localization signals

PURPOSE: LYRIC/AEG-1 has been reported to influence breast cancer survival and metastases, and its altered expression has been found in a number of cancers. The cellular function of LYRIC/AEG-1 has previously been related to its subcellular distribution in cell lines. LYRIC/AEG-1 contains three uncharacterized nuclear localization signals (NLS), which may regulate its distribution and, ultimately, function in cells.

EXPERIMENTAL DESIGN: Immunohistochemistry of a human prostate tissue microarray composed of 179 prostate cancer and 24 benign samples was used to assess LYRIC/AEG-1 distribution. Green fluorescent protein-NLS fusion proteins and deletion constructs were used to show the ability of LYRIC/AEG-1 NLS to target green fluorescent protein from the cytoplasm to the nucleus. Immunoprecipitation and Western blotting were used to show posttranslational modification of LYRIC/AEG-1 NLS regions.

RESULTS: Using a prostate tissue microarray, significant changes in the distribution of LYRIC/AEG-1 were observed in prostate cancer as an increased cytoplasmic distribution in tumors compared with benign tissue. These differences were most marked in high grade and aggressive prostate cancers and were associated with decreased survival. The COOH-terminal extended NLS-3 (amino acids 546-582) is the predominant regulator of nuclear localization, whereas extended NLS-1 (amino acids 78-130) regulates its nucleolar localization. Within the extended NLS-2 region (amino acids 415-486), LYRIC/AEG-1 can be modified by ubiquitin almost exclusively within the cytoplasm.

CONCLUSIONS: Changes in LYRIC/AEG-1 subcellular distribution can predict Gleason grade and survival. Two lysine-rich regions (NLS-1 and NLS-3) can target LYRIC/AEG-1 to subcellular compartments whereas NLS-2 is modified by ubiquitin in the cytoplasm.