Optimal Charging Management of Microgrid-Integrated Electric Vehicles

The relevance of electric vehicles (EVs) is increasing along with the relative issues. The definition of smart policies for scheduling the EVs charging process represents one of the most important problems. A discrete-event approach is proposed for the optimal scheduling of EVs in microgrids. This choice is due to the necessity of limiting the number of the decision variables, which rapidly grows when a small-time discretization step is chosen. The considered optimization problem regards the charging of a series of vehicles in a microgrid characterized by renewable energy source, a storage element, the connection to the main grid, and a charging station. The objective function to be minimized results from the weighted sum of the cost for purchasing energy from the external grid, the weighted tardiness of the services provided, and a cost related to the occupancy of the socket. The approach is tested on a real case study.

Matrix Converter

The matrix converter (MC) has recently attracted significant attention among researchers because of its applications in wind energy conversion, military power supplies, induction motor drives, etc. Recently, different MC topologies have been proposed and developed which have their own advantages and disadvantages. Matrix converter can be classified as a direct and indirect structure. This chapter aims to give a general description of the basic features of a three phase to three phase matrix converters in terms of performance and of technological issues. Matrix converter is a direct AC-AC converter topology that is able to directly convert energy from an AC source to an AC load without the need of a bulky and limited lifetime energy storage element. AC-AC topologies receive extensive research attention for being an alternative to replace traditional AC-DC-AC converters in the variable voltage and variable frequency AC drive applications.

Electrical Efficiency of SECE-based Interfaces for Piezoelectric Vibration Energy Harvesting

Piezoelectric energy harvesting (PEH) interfaces have been widely investigated during the last decades in order to maximize the harvested power. Among the energy extraction circuits proposed in the literature, some of the most effective ones consist of extracting the electric charges from the piezoelectric elements in a synchronous way with the vibrations and within a very short portion of the vibration period (SECE, SECPE, FTSECE, etc.). For these strategies, most previous studies take the electrical efficiency (i.e., the electrical losses between the energy extracted from the piezoelectric element and the energy which is finally transferred in a storage element) into account in an ad-hoc and case-by-case manner. In this brief, we propose a unified analysis that applies to model the electrical efficiency of these SECE-based strategies taking into account losses introduced by the electrical interface. We identify the main loss mechanisms by demonstrating that the electrical efficiency mainly varies with two parameters: the quality factor of the electrical interface and the voltage inversion ratio of the considered strategy. Measurements on the FTSECE strategy show that our model predicts the stored power with a good accuracy and allows a better optimization of the harvesting interface (up to 5.4 times more stored power at off-resonance frequencies, and 30% larger harvesting bandwidth).

Muti-level voltage synthetic voltage direct power flow controller

Aiming at the defects of DC energy storage elements, complex structure and large volume of unified power flow controller (UPFC), the paper combines flying capacitor multilevel technology and voltage vector synthesis technology with unified direct power flow controller. A three-level direct power flow controller (3L-DPFC) and a new control strategy are proposed. By obtaining the power parameters of the receiving end and substituting them into the derived calculation formula, the compensation voltage can be deduced to adjust the phase and amplitude, and the change relationship between the compensation voltage and the power parameters of the receiving end can be calculated through multiple groups of data, so as to adjust the active power flow and reactive power flow in the power grid. Compared with the unified direct power flow controller, it has the advantages of no DC energy storage element, small volume, simple structure, and the voltage stress of each switch is reduced by half, which reduces the failure rate and economic cost of the controller. In the paper, the topology and control strategy of three-level synthetic DPFC are described in detail, and its buck AC conversion theoretical analysis is verified by simulation.

Performance analysis of unpowered lower limb exoskeleton during sit down and stand up

ABSTRACT Conventional unpowered lower limb exoskeleton paid little attention to the metabolic cost of body during sit down (SD)/stand up (SU). The SD motion model and the motion characteristics of lower extremity are analyzed; then, a novel unpowered lower limb exoskeleton is proposed, and the contribution degree of muscles and stiffness of joints are used for determining the location and stiffness of energy storage element. The metabolic cost of relevant muscles in joints of the left leg is obtained based on Opensim software. The results show that metabolic cost of the gracilis, rectus femoris (RF), and long head of the biceps femoris decreased about 13%, 9%, and 68%, respectively. The total metabolic cost of body decreased about 14% during SD. However, the metabolic cost of the gracilis, RF, and long/short head of the biceps femoris increased about 22%, 33%, 208%, and 46%, respectively. And the metabolic cost of sartorius reduces about 39%, the total metabolic cost of body increased about 25.6% during SU, under the exoskeleton conditions. The results of this study can provide a theoretical basis for the optimal design of unpowered lower limb exoskeleton.

Sustainability Analysis of a ZnO-NaCl-Based Capacitor Using Accelerated Life Testing and an Intelligent Modeling Approach

From small toys to satellites, capacitors play a vital role as an energy storage element, filtering or controlling other critical tasks. This research paper focuses on estimating the remaining useful life of a nanocomposite-based fabricated capacitor using various experimental and artificial intelligence techniques. Accelerated life testing is used to explore the sustainability and remaining useful life of the fabricated capacitor. The acceleration factors affecting the health of capacitors are investigated, and experiments are designed using Taguchi’s approach. The remaining useful lifetime of the fabricated capacitor is calculated using a statistical technique, i.e., regression analysis using Minitab 18.1 software. An expert model is designed using artificial neural networks (ANN), which warns the user of any upcoming faults and failures. The average remaining useful life of the fabricated capacitor, using accelerated life testing, regression, and artificial neural network, is reported as 13,724.3 h, 14,515.9 h, and 14,247.1 h, respectively. A comparison analysis is conducted, and performance metrics are analyzed to opt for the most efficient technique for the prediction of the remaining useful life of the fabricated capacitor, which confirms 93.83% accuracy using the statistical method and 95.82% accuracy using artificial neural networks. The root mean square error (RMSE) of regression and artificial neural networks is found to be 0.102 and 0.167, respectively, which validates the consistency of the reliability methods.

Multi Distance Face Recognition of Eye Localization with Modified Gaussian Derivative Filter

Face recognition at a distance (FRAD) is one of the most difficult types of face recognition applications, particularly at a distance. Due to the poor resolution of facial image, it is difficult to identify faces from a distance. Recently, while recording individuals, the camera view is broad and just a small portion of a person's face is visible in the image. To ensure that the facial image has a low resolution, which deteriorates both face detection and identification engines, the facial image is constantly at low resolution. As an immediate solution, employing a high-definition camera is considered as a simple and practical approach to improve the reliability of algorithm and perform well on low-resolution facial images. While facial detection will be somewhat decreased, a picture with higher quality will result in a slower face detection rate. The proposed work aims to recognize faces with good accuracy even at a distance. The eye localization works for the face and eye location in the face of a human being with varied sizes at multiple distances. This process is used to detect the face quickly with a comparatively high accuracy. The Gaussian derivative filter is used to reduce the feature size in the storage element, which improves the speed of the recognition ratio. Besides, the proposed work includes benchmark datasets to evaluate the recognition process. As a result, the proposed system has achieved a 93.24% average accuracy of face recognition.

Design and analysis of motion and energy regulating vibration harvester

In this paper a novel design of energy harvester has been proposed, which converts harmonic or random vibrations energy into useful electric power. The energy harvester comprises of mechanical motion rectifier, motion regulator, strain energy storage element and a rotary electric generator. The mechanical motion rectifier comprises of a spatial mechanism with unidirectional bearings and spherical joint that converts the linear oscillating force into unidirectional torque pulses. Further, motion regulating mechanism directs the energy flow to the strain energy storage element and drives the electric generator. The arrangement ensures that flow of vibration energy is regulated such that it is stored in the spring up to a threshold limit and thereafter dissipated to the electric generator. Rigid body simulations in Adams and Matlab have been used in design and analysis of the energy harvester with investigations for the effect of significant design parameters. Experimentation on a prototype has been performed to validate the numerical model which delivered 4.13 W of peak power and average power of 0.12–0.52 W within frequency range of 1–15 Hz. Simulation results on a real size device with higher torsion spring stiffness indicates that the harvester can operate with 69.8% efficiency and deliver 0.32–2.45 W of average power for frequency of 0.5–4 Hz.

Driving cycle based battery rating selection and range analysis in EV applications

<p>The energy consumption of electric vehicles (EVs)depends on traffic environment, terrain, resistive forces acting on vehicle, vehicle characteristics and driving habits of driver. The battery pack in EV is the main energy storage element and the energy capacity determines the range of vehicle. This paper discusses the behavior of battery when EV is subjected to different driving environments such as urban and highway. The battery rating is selected based on requirement of driving cycle. The MATLAB/Simulink model of battery energy storage system (BESS) consisting of battery, bidirectional DC/DCconverter and electric propulsion system is built. The simulation is carried out and the performance of BESS is tested for standard driving cycles which emulate actual driving situations. It has been shown that, the amount of the energy recovered by battery during deceleration depends on the amount of regenerative energy available in the driving cycle. If the battery recovers more energy during deceleration, the effective energy consumed by it reduces and the range of the vehicle increases.</p>