An online optimum voltage estimation and real‐time MPP tracking for a PV system

In this paper, a photovoltaic system topology incorporating a new maximum power point tracking (MPPT) controller method is presented. This method uses an autotuning estimator and a PI controller to make the system work in the maximum power point. The controller is formulated based on the bijectivity in the photovoltaic generator characteristic; therefore, if the optimal voltage is reached, this means that the maximum of power is obtained. The proposed MPPT algorithm is implemented on a dSpace DS1104 controller board. In order to demonstrate the efficiency of the proposed algorithm in real time, an experimental setup using a boost converter connected to a resistive load is successfully implemented and studied. The obtained experimental results prove the validity of the proposed MPPT algorithm.     

How drivers decide whether to get a fuel cell vehicle: An ethnographic decision model

This article develops and tests an ethnographic decision model (EDM) of hydrogen fuel cell vehicle (FCV) adoption using interviews with California residents that either actually adopted an FCV or “seriously considered” doing so before deciding against it. We developed an initial model from 25 semi-structured interviews in which respondents self-described their decision-making processes. We iteratively tested and refined the model in a second round of 53 structured interviews. The final model consists of a first stage that assesses FCV adoption feasibility and a second stage that compares FCVs to other vehicle types. The model ultimately correctly predicts 86.8% of cases in the sample. In the first stage, respondents preferred to satisfy their need for a primary refueling station near home but a substantial number were willing to rely on a station near or on the way to work or other destination. Most drivers required a convenient backup station and a means of managing long-distance trips. Vehicle size options eliminated a few respondents. None rejected FCV adoption due to insufficient driving range. In the second stage, nearly all drivers engaged in some kind of cost comparison, though the factors considered varied greatly. Most opted for what they viewed as the less costly option, although a few FCV adopters and non-adopters were willing to pay more for their more preferred option. EDM is a promising qualitative research method for generating insights into how people navigate the decision whether or not to get an alternative-fuel vehicle.     

An optimization algorithm inspired by the States of Matter that improves the balance between exploration and exploitation

The ability of an Evolutionary Algorithm (EA) to find a global optimal solution depends on its capacity to find a good rate between exploitation of found-so-far elements and exploration of the search space. Inspired by natural phenomena, researchers have developed many successful evolutionary algorithms which, at original versions, define operators that mimic the way nature solves complex problems, with no actual consideration of the exploration-exploitation balance. In this paper, a novel nature-inspired algorithm called the States of Matter Search (SMS) is introduced. The SMS algorithm is based on the simulation of the states of matter phenomenon. In SMS, individuals emulate molecules which interact to each other by using evolutionary operations which are based on the physical principles of the thermal-energy motion mechanism. The algorithm is devised by considering each state of matter at one different exploration–exploitation ratio. The evolutionary process is divided into three phases which emulate the three states of matter: gas, liquid and solid. In each state, molecules (individuals) exhibit different movement capacities. Beginning from the gas state (pure exploration), the algorithm modifies the intensities of exploration and exploitation until the solid state (pure exploitation) is reached. As a result, the approach can substantially improve the balance between exploration–exploitation, yet preserving the good search capabilities of an evolutionary approach. To illustrate the proficiency and robustness of the proposed algorithm, it is compared to other well-known evolutionary methods including novel variants that incorporate diversity preservation schemes. The comparison examines several standard benchmark functions which are commonly considered within the EA field. Experimental results show that the proposed method achieves a good performance in comparison to its counterparts as a consequence of its better exploration–exploitation balance.     

Stability,performance and sensitivity analysis of I.I.D. jump linear systems

This paper presents a symmetric Kronecker product analysis of independent and identically distributed jump linear systems to develop new, lower dimensional equations for the stability and performance analysis of this type of systems than what is currently available. In addition, new closed form expressions characterising multi-parameter relative sensitivity functions for performance metrics are introduced. The analysis technique is illustrated with a distributed fault-tolerant flight control example where the communication links are allowed to fail randomly.     

Identification of Toxin Inhibitors Using a Magnetic Nanosensor‐Based Assay

A magnetic nanosensor‐based method is described to screen a library of drugs for potential binding to toxins. Screening is performed by measuring changes in the magnetic relaxation signal of the nanosensors (bMR nanosensors) in aqueous suspension upon addition of the toxin. The Anthrax lethal factor (ALF) is selected as a model toxin to test the ability of our bMR nanosensor‐based screening method to identify potential inhibitors of the toxin. Out of 30 molecules screened, sulindac, naproxen and fusaric acid are found to bind LF, with dissociation constants in the low micromolar range. Further biological analysis of the free molecules in solution indicate that sulindac and its metabolic products inhibited LF cytotoxicity to macrophages with IC₅₀ values in the micromolar range. Meanwhile, fusaric acid is found to be less effective at inhibiting LF cytotoxicity, while naproxen does not inhibit LF toxicity. Most importantly, when the sulindac and fusaric acid‐bMR nanosensors themselves are tested as LF inhibitors, as opposed to the corresponding free molecules, they are stronger inhibitors of LF with IC₅₀ values in the nanomolar range. Taken together, these studies show that a bMR nanosensors‐based assay can be used to screen known drugs and other small molecules for inhibitor of toxins. The method can be easily modified to screen for inhibitors of other molecular interactions and not only the selected free molecule can be study as potential inhibitors but also the bMR nanosensors themselves achieving greater inhibitory potential.     

A Multisensor Architecture Providing Location-based Services for Smartphones

This paper introduces a multisensor architecture to fuse data acquired from different sensors available in commodity smartphones in order to build accurate location-based services, and pursuing a good balance between accuracy and performance. Using scale invariant features from the images captured using the smartphone camera, we perform a matching process against previously obtained images to determine the current location of the device. Several refinements are introduced to improve the performance and the scalability of our proposal. Location fingerprinting, based on IEEE 802.11, will be used to determine a cluster of physical points, or zone, where the device seems to be according to the received signal strength. In this way, we will reduce the number of images to analyze to those contained in the tentative zone. Additionally, accelerometers will also be considered in order to improve the system performance, by means of a motion estimator. This set of techniques enables a wide range of location-based applications.