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Trap plays an important role in the charge transportation of three-layer oil-paper and the investigation of trap parameters at different degradation degree is of great significance for further research of the partial discharge (PD) mechanism. This article considers the turn-to-turn structure of on-board traction transformer. A defect model of three-layer oil-paper insulation was designed for PD test. The PD degradation samples are selected from the inception of PD to the breakdown of PD to study the characteristics of surface potential decay on degradation samples by using isothermal surface potential decay method. Given that, the trap distribution at different degradation stages was calculated and its influence on PD characteristics was investigated. The result shows that AC fluctuation voltages caused by inter-harmonic has a great influence on PD distribution, surface charge distribution and trap distribution. With the increase of degradation, the decay rate of surface potential increases and the decay rate of AC fluctuation voltages is larger than that pure AC. And also, the number of shallow trap with AC fluctuation voltages is larger than that with pure AC. The rate of free charge increases with the number of shallow trap increasing. More free electrons involves in the process of PD, accelerating the aging rate of three-layer oil paper samples. Therefore, it can be concluded that surface charge and trap distribution are helpful to clarify PD mechanism.

Oil-paper insulation will inevitably endure impulse voltage with a superimposed dc voltage (superimposed voltage) because of introduced lightning or switching, which can induce charge accumulation and trigger flashover during the operation of a converter transformer. Temperature rise is also a nonnegligible factor that can significantly influence the performances of oil-paper insulation. This paper aims to reveal the effects of ambient temperature and superimposed voltage on surface charge and flashover behaviors in an oil-paper insulation system. Surface potential decay (SPD) experiments were performed under superimposed voltage with various polarity and amplitude combinations and at the temperature ranging from 20 °C to 80 °C. The results show that the initial surface potential and decay rate increase as the amplitude of the impulse voltage increases at 20 °C. The initial surface potential declines, and the process of SPD is accelerated at higher temperatures because of the increased concentration of shallow traps. Subsequently, flashover tests were conducted under superimposed voltage. It is found that flashover occurs after applying superimposed voltages even with a rather low dc voltage. In addition, the dc voltage component is primarily responsible for flashover. Weibull results also indicate that it is prone to trigger flashover at higher temperatures, because thermal excitation helps more carriers to escape from deep traps and participate in the process of flashover. Accordingly, the insulation characteristics of oil-paper system can be significantly influenced by superimposed voltage and temperature, which should draw great concern among the power grid.

Voice-over IP (VoIP) technology is a kind of digital transmission technology based on IP network. It is one of the important methods to use voice service in VoIP as steganographic carrier to ensure secure transmission. However, the traditional steganographic code has some problems, such as low embedding efficiency and weak concealment, which cannot meet the requirements of VoIP streaming media information hiding for the security of secret information. Therefore, a steganographic algorithm combining F5 and simplified wet paper code (SWPC) algorithm is proposed. The main idea is to embed secret messages in each row of the carrier matrix using the F5 algorithm, and then the SWPC algorithm is used to embed the columns according to the wet and dry characteristics of the wet paper code without affecting the results before row embedding. We use the VoIP streams encoded by the ITU-T G.729a codec as a carrier to verify the proposed scheme. The experimental results demonstrate that the proposed scheme can achieve relatively better IP speech data steganographic transparency and that it can outperform F5-WPC and SWPC approaches.

Due to the high penetration of renewable energy resources in microgrids (MGs), the grid inertia becomes low which leads to the grid to be vulnerable to large disturbances. The energy storage devices can play an important role to enhance the inertia of MGs. However, due to the high investment cost of storages or their dp/dt limitation, the installed energy storages cannot cover the challenge of high df/dt. A prominent solution to solve the problem is to use the inertia response of the wind generators. However, relatively high second frequency nadir is the main drawback of using the inertia response of the wind generators which may impose an extensive disturbance to MGs. Accordingly, a coordinated operation strategy for MGs between wind generator and hybrid energy storage (HES) system is proposed in this paper. In addition, to improve the inertia response of the MG; providing high-quality communication infrastructures with low delay and increasing the Ultracapacitor capacity have been paid attention. In this paper, the costs of the installed Ultracapacitor and quality of communication services are defined as the operation cost. Guaranteeing enough frequency damping for the MG with low operation cost are two conflict objectives. Therefore, a multi-objective optimization method is used to set the controllers’ values and reduce the operation cost. The results confirmed that the effectiveness of the proposed strategy to control hybrid power storage in coordination with the wind generator and the frequency recovery process is improved. Also, employing the optimum values guaranteed the frequency damping effectively with low operation cost. The Integral Absolute Error (IAE) value and operation cost are reduced by 13.6% and 32%, respectively. Also, the simulation results show that the maximum MG frequency deviation and maximum df/dt is well compatible with different standards in the presence of load perturbations and different wind speeds.

Lifetime estimation of power semiconductor devices have been widely investigated to improve the reliability and reduce the cost of maintenance of power converters. However in most reported work, the aging effect is not considered in the lifetime evaluation process due to the omission or limitation of thermal cycle counting method. Additionally, the electrical/thermal simulation and lifetime estimation are usually implemented in different simulators/platforms, for the same reason. Thus, to tackle these problems, a concise but comprehensive MOSFET model that enables electro-thermal modeling, aging and lifetime estimation on LTspice® circuit simulator is proposed in this paper. The idea comes from the fact that, MOSFET on-state resistance Rds,on is not only temperature dependent, but also widely accepted as the device failure precursor. In other words, as it carries critical information about instantaneous temperature and aging progress. Hence, co-simulation can be achieved by constructing electrical, thermal, and aging and lifetime sub-modules exclusively first, and using Rds,on, to build linkages among them. Averaged modeling technique is adopted due to the ease of establishing links among these three sub-modules, and fast simulation speed as compared to a switched converter model. Behavioral models are employed to realize the thermal cycles counting, stress accumulation and degradation evaluation. This paper demonstrates that it is possible to use a single simulation software to monitor performances of devices and circuits, and their lifetime estimation simultaneously. High-stress thermal cycling and long-term random mission profiles are applied to verify the correctness of the model and to mimic a 10-year load respectively. An accelerated aging trend can be observed in the long-term mission profile simulation, which is in agreement with the theory. Facilitated by the employment of averaged circuits, the proposed method is a good simulation/analytical tool to implement a long-term mission profile that requires reliability assessment.

Made available in DSpace on 2022-04-29T08:29:33Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 Distribution network is an essential part of electric power system, which however has higher power losses than transmission system. Distribution losses directly affect the operational cost of the system. Therefore, power loss reduction in distribution network is very important for distribution system users and connected customers. One of the commonly used ways for reducing losses is distribution system reconfiguration (DSR). In this process, configuration of distribution network changes by opening and closing sectional and tie switches in order to achieve the lowest level of power losses, while the network has to maintain its radial configuration and nodal voltage limits, and supply all connected loads. The DSR aiming loss reduction is a complex mixed-integer optimization problem with a quadratic term of power losses in the objective function and a set of linear and non-linear constraints. Accordingly, distribution network researchers have dedicated their efforts to developing efficient models and methodologies in order to find optimal solutions for loss reduction via DSR. In this paper, an efficient mathematical model for loss minimization in distribution network reconfiguration considering the system voltage profile is presented. The model can be solved by commercially available solvers. In the paper, the proposed model is applied to several test systems and real distribution networks showing its high efficiency and effectiveness for distribution systems reconfiguration. Associated Laboratories Institute of Bioenergy Research (IPBEN) São Paulo State University Campus of Ilha Solteira Department of Electrical Power Engineering Tishreen University School of Electrical and Computer Engineering National Technical University of Athens Department of Electrical and Computer Engineering College of Engineering Sultan Qaboos University Associated Laboratories Institute of Bioenergy Research (IPBEN) São Paulo State University Campus of Ilha Solteira

In this paper, we propose a simple framework for closed-loop system identification: the stabilized output error method. Traditional closed-loop system identification methods rely on the linearity of the target system, and they require the identification of noise models or prior knowledge or identifiability of the feedback controllers to obtain unbiased estimates. But in many real-world applications, the noise dynamics and feedback controllers are complex and difficult to identify, and the nonlinearity may not be ignored. The proposed framework introduces a virtual controller that stabilizes the error between model prediction and the output of the target system. This enables us to apply the output error method, which gives unbiased estimates without depending on the noise model and is applicable to a wide range of models, including nonlinear systems, to closed-loop system identification problems. The paper describes the framework and gives the theoretical support and design guidelines for virtual controllers. Through numerical examples, we show the effectiveness of the proposed framework in various situations, which include identification of (a) linear gray box models, (b) systems in the presence of disturbances having realistic complexity, and (c) a nonlinear unstable system in a human-in-the-loop environment.

The present article outlines the core technologies needed to realize the Hyperloop transportation system (HTS). Currently, the HTS vacuum tube train concept is viewed as the fastest way to cross the earth’s surface. However, the concept has not yet been demonstrated for subsonic or near-sonic speeds in large-scale implementations. Among the challenging technical areas are the tube’s depressurization, the capsule’s air resistance, and choked flows occurring around the capsule. There is also a need for effective levitation and propulsion solutions compatible with the velocities being proposed. Moreover, several conflicting objectives have been identified in the HTS design. It is highlighted that the tubes should be wide enough to lower the capsule’s drag forces but that a large-sized tube comes at the expense of higher operational energy costs and infrastructure investments. Another struggle is aiming at a low-cost passive track design and, and at the same time, a lightweight vehicle. One technical path is to turn the whole guideway into an electric propulsor, arriving at a ’lightweight capsule solution’ (LCS). Alternatively, the vehicle could be transformed into a ’modified airplane’ that stores massive amounts of onboard energy, yielding an energy-autonomous ’low infrastructure solution’ (LIS). In a case study, it is shown that even LIS technology is compatible with short-haul flights (1500km) but that it requires an energy reservoir of about 30% of the capsule’s overall mass. Results and discussions presented in this paper are supported by analytical predictions with parameters or input data either supported by referred simulations or experiments. In general, the paper aims to open up the discussion, provide a sufficient understanding of the Hyperloop field’s multidisciplinary aspects, and establish a foundation for further investigations. In the end, new research tasks have been defined, which have the potential to go beyond the state of current knowledge. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

The increasing number of megawatt-scale photovoltaic (PV) power plants and other large inverter-based power stations that are being added to the power system are leading to changes in the way the power grid is operated. In response to these changes, new grid code requirements establish that inverter-based power stations should not only remain connected to the grid during faulty conditions but, also provide dynamic support. This feature is referred in the literature to as momentary cessation operation. The few published studies about momentary cessation operation for PV power plants have not shed much light on the impact of these systems on the overall power system stability problem. As an attempt to address this issue, this paper proposes a control scheme for PV inverters that improves the transient stability of a synchronous generator connected to the grid. It is shown through the paper that the proposed control scheme makes the PV inverter’s dc link capacitors absorb some of the kinetic energy stored in the synchronous machine during momentary cessation. Besides that, the proposed solution is also able to improve voltage stability through the injection of reactive power. Experimental and simulation results are presented in order to demonstrate the effectiveness of the proposed control scheme.

Due to the large overshoot and poor disturbance rejection impact the control accuracy of the permanent magnet synchronous motor (PMSM) in the proportional–integral–derivative (PID) control mode. In this paper, we propose an optimal double-loop pseudo-derivative feedback (PDF) control strategy. Firstly, to obtain high-precision feedback current and minimize the influence of sampling delay, a double-feedback PDF control structure is configured based on the $\Sigma $ – $\Delta $ sampling modulation and Sinc3 filter. Secondly, we adopt an instant-sampling and instant-update (ISIU) strategy based on a field-programmable gate array (FPGA), which can reduce the update delay of the pulse-width modulation (PWM), and design the hardware timing diagram, accordingly. Then, based on the influence of the closed-loop pole position on the dynamic performance of the system and the saturation characteristics of the power device, the PDF parameters tuning method of the current loop and speed loop is proposed. Finally, the system performance under different control strategies is compared and analyzed through simulations and experiments. The results show that the optimal double-loop PDF control strategy proposed in this paper can considerably expand the bandwidth of the current loop and has better disturbance rejection.

This paper presents a bio-inspired intelligent controller to enhance the performance of a nonlinear system. The controller is designed by capturing the emotional intelligence of mammalian brain mediated by the limbic system in which certain parts are responsible for generating emotions and these can be combined together as brain affective system inspired control architecture (BASIC). This controller has been used to cope with nonlinearities present in control applications. In this paper brain inspired control architecture is proposed while incorporating the sensory cortex explicitly in the architecture and the computational equations of various modules are suitably developed. The performance of the proposed controller is analyzed on a typical nonlinear system, namely, Permanent magnet synchronous motor for speed control, harmonics in stator phase currents and ripples produced in electromagnetic torque at different operating conditions. Its performance is compared with the existing control techniques in offline simulations as well as in real-time Hardware-in-loop environment. The results establish the computational efficiency, accuracy and robustness of the proposed controller.

In response to national and international carbon reduction goals, renewable energy resources like photovoltaics (PV) and wind, and energy storage technologies like fuel-cells are being extensively integrated in electric grids. All these energy resources require power electronic converters (PECs) to interconnect to the electric grid. These PECs have different response characteristics to dynamic stability issues compared to conventional synchronous generators. As a result, the demand for validated models to study and control these stability issues of PECs has increased drastically. This paper provides a review of the existing PEC model types and their applicable uses. The paper provides a description of the suitable model types based on the relevant dynamic stability issues. Challenges and benefits of using the appropriate PEC model type for studying each type of stability issue are also presented.

This paper considers the economy and reliability of the microgrid cluster system, and proposes a bi-level optimized operation strategy for the microgrid cluster, which aims to improve the economic benefits of the microgrid cluster and reduce the operating risk of microgrid. The upper layer takes the microgrid cluster as the research object, with the goal of minimizing the total operating cost of the system, and establishes the optimal model of the microgrid cluster. The lower layer takes the sub-microgrid as the research object, and establishes the microgrid optimization model with the goal of optimal operating cost and operating risk index. The method of combining mixed integer linear programming and IABC algorithm is used to solve the multi-objective bi-level optimization model, and to provide decision makers with two microgrid dispatching schemes with different focuses. Finally, an example is used to verify the effectiveness of the bi-level optimization strategy and improved algorithm proposed in this paper, as well as the practicability of the two dispatching schemes.

The widespread use of Unmanned Aerial Vehicles (UAV) has made the security and computing resource application efficiency of UAV a hot topic in the security field of the Internet of Things. In this paper, an optimized lightweight identity security authentication protocol, Optimized Identity Authentication Protocol (ODIAP) is proposed for Internet of Drones (IoD) networks. The protocol is targeted to the security risks faced by IoD networks, and proposes the security authentication mechanism consisting of 3 phases and 7 authentication processes, which enables the protocol has both forward and backward security, and can resist mainstream network attacks. Meanwhile, this paper fully considers the computational load and proposes the identity information generation and verification method based on the Chinese residual theorem, which reduces the computational load of resource-constrained nodes and shifts the complex computational process to server nodes with abundant computational resources. Moreover, after security protocol analysis and tool verification based on the automated security verification tool Proverif, the protocol in this paper has complete security. At the same time, the performance analysis and comparison with other mainstream protocols shows that this protocol effectively optimizes the use of computing resources without compromising security.

This paper focuses on the time-domain analysis of bandpass (BP) negative group delay (NGD) function. The innovative NGD investigation is based on the time-domain experimentation of an innovative topology of “lill”-shape passive microstrip circuit. The design principle of the proof of concept (POC) constituted by particular microstrip shapes is described. The NGD circuit is inspired from a recent fully distributed “li”-topology. Before the time-domain investigation, the BP NGD specifications of the circuit under study are academically defined. As practical application of the basic definition, a frequency domain validation of “lill”-circuit is presented in the first section of the paper. The POC circuit is specified by a -8 ns NGD value at 2.31 GHz NGD center frequency and a 27 MHz NGD bandwidth. The “lill”-circuit exhibits an attenuation loss of about -6.2 dB at the NGD center frequency. Then, the two-port black box model of “lill”-NGD-circuit represented by touchstone data of the measured S-parameters is exploited for the transient simulation. The measured group delay (GD) illustrates that the tested “lill”-circuit operates as a BP function regarding the NGD with NGD equal to -8.1 ns at the NGD center frequency. The time-domain demonstration of the BP NGD function was performed using a gaussian pulse modulating sine carrier. The innovative experimental setup with the possibility to plot simultaneously well synchronized input and output signals is explained. The BP NGD time-domain response is understood from commercial tool simulation using the touchstone S-parameters of the measured “lill”-circuit by using a Gaussian up-converted pulse having a 27 MHz frequency bandwidth. It was observed that the output signals are delayed when the sine carrier is out of NGD-band. However, the output signal envelope is in advanced of about -8 ns when the carrier is tuned to be approximately equal to the 2.31 GHz NGD center frequency. To confirm the time-domain typical behavior of BP NGD response, an input pulse signal having Gaussian waveform were considered during the test. However, the input signal spectrum must be determined in function of the NGD bandwidth. After tests, measured output signal envelopes presenting leading edge, trailing edge and peak in time-advance compared to the input ones are observed experimentally. The results of the present feasibility study open a potential microwave communication application of BP NGD function notably for systems operating with ISM and IEEE 802.11 standards.

This paper presents a polarization insensitive frequency selective surface (FSS) based on concentric ring slots with five closely spaced passbands. The proposed FSS unit cell contains five ring slots coupled with a supplementary innermost ring slot. The close band response within the first five transmission bands is achieved by the influence of the modified geometry obtained with the inclusion of the sixth ring slot. This added ring slot causes the appearance of a stopband, due to the conductive ring between the fifth and the sixth ring apertures, and a passband produced inherently by the sixth ring aperture. The effect of the additional stopband and passband in the FSS response has been investigated in the paper. Full-wave simulations reveal that a modified geometry with proper sizes effectively enables the close band response of the pentaband FSS. To validate the proposed approach, a 729-element penta-bandpass FSS prototype operating at millimeter-wave frequencies has been designed, fabricated, and tested. Experimental results in a free-space measurement setup indicate resonances at $f_{1} =26.7$ , $f_{2} =29.8$ , $f_{3} =33.6$ , $f_{4} =38.1$ , and $f_{5} =44.2$ GHz, with resonant frequency ratios of $f_{2} / f_{1} =1.12$ , $f_{3} / f_{2} =1.13$ , $f_{4} / f_{3} =1.13$ , and $f_{5} / f_{4} =1.16$ . This FSS demonstrates an extremely low ratio of the highest and the lowest resonant frequencies ( $f_{5} / f_{1} =1.66$ ) for a penta-band operation. This polarization insensitive FSS demonstrates good performance at oblique angular incidence for elevation angles up to 45°.

It is expected that peer to peer energy trading will constitute a significant share of research in upcoming generation power systems due to the rising demand of energy in smart microgrids. However, the on-demand use of energy is considered a big challenge to achieve the optimal cost for households. This paper proposes a blockchain-based predictive energy trading platform to provide real-time support, day-ahead controlling, and generation scheduling of distributed energy resources. The proposed blockchain-based platform consists of two modules; blockchain-based energy trading and smart contract enabled predictive analytics modules. The blockchain module allows peers with real-time energy consumption monitoring, easy energy trading control, reward model, and unchangeable energy trading transaction logs. The smart contract enabled predictive analytics module aims to build a prediction model based on historical energy consumption data to predict short-term energy consumption. This paper uses real energy consumption data acquired from the Jeju province energy department, the Republic of Korea. This study aims to achieve optimal power flow and energy crowdsourcing, supporting energy trading among the consumer and prosumer. Energy trading is based on day-ahead, real-time control, and scheduling of distributed energy resources to meet the smart grid’s load demand. Moreover, we use data mining techniques to perform time-series analysis to extract and analyze underlying patterns from the historical energy consumption data. The time-series analysis supports energy management to devise better future decisions to plan and manage energy resources effectively. To evaluate the proposed predictive model’s performance, we have used several statistical measures, such as mean square error and root mean square error on various machine learning models, namely recurrent neural networks and alike. Moreover, we also evaluate the blockchain platform’s effectiveness through hyperledger calliper in terms of latency, throughput, and resource utilization. Based on the experimental results, the proposed model is effectively used for energy crowdsourcing between the prosumer and consumer to attain service quality.

Due to the lack of inertial support of the physical rotor of reliable power, the problem of weak inertia of the system is prominent when large-scale grid connection. Aiming at the weak inertia problem of new energy power systems, this paper takes the photovoltaic power generation system with generalized droop control as the research object. Firstly, the paper introduces the structure of the photovoltaic power generation system and the mathematical principle of generalized droop control At the same time, the electrical torque model of the system is established in order to reveal the inertia characteristics of the grid-tied inverter under the generalized droop control, moreover, the influencing factors of the system’s inertia characteristics and the influence rules of parameters are analyzed and studied. Finally, simulation analysis verifies the correctness of the analysis. The research results show that the photovoltaic inverter system under the generalized droop control has obvious inertia characteristics, the change of inertia size is affected by the dominant zero pole of the controller, and the equivalent inertia coefficient has frequency domain characteristics.

Compared with silicon (Si) IGBTs, silicon carbide (SiC) MOSFETs have much faster switching speeds and high switching frequency operation capability, enabling compact and high-efficiency motor drive systems. However, the increased switching speed and frequency also cause increased-level of common-mode (CM) voltage with higher slew rates (dv/dt). The CM voltage leads to machine leakage currents as well as bearing currents such as electric discharge machining (EDM) type current and capacitive-type (dv/dt) current. These bearing currents can cause degradation or failure of motor bearings. In order to investigate the impact of SiC motor drives on the motor bearing currents, in this paper, the mechanism and modelling of bearing currents are analyzed first. Then, a direct measurement method is used to assess the bearing currents in the induction motor driven by the SiC converter. In the experiment, the number of EDM current events is counted and the amplitude of the capacitive-type of current is also examined under various switching speeds and frequencies of SiC devices. Furthermore, the bearing currents are also extensively tested under various bearing temperatures, motor speeds and dc-link voltages. The correlations between the bearing currents and various factors have been revealed in this paper.

In this paper, a new high efficiency soft-switching non-isolated three-port converter (TPC) is proposed. In the conventional TPC, three switches are required to process power in different directions between inputs and output. Providing soft-switching condition for all switches using a low number of auxiliary components is a challenging task. In this paper, the conventional TPC topology is modified by changing its structure and adding a simple auxiliary circuit such that all switches operate under soft-switching condition in all operating modes. To reduce the volume of the converter, the magnetic components are integrated using a coupled inductor in the auxiliary soft-switching cell. In this paper, various converter operating modes are presented, and design considerations are discussed. Finally, a prototype 200 W, 100 V converter is implemented in the laboratory, and the theoretical analysis is validated by the experimental results.

In this paper, an extensive reliability analysis of wind energy conversion systems (WECS) is presented. Elaborate the analysis is presented starting from the subassembly level to the subsystem level, then the system or the overall WECS. The fault tree method with a Weibull probability distribution function is introduced as a complete model for estimating the wind turbine subassemblies’ reliability. The model was tested using a massive dataset of failure rates of various wind turbine subassemblies derived from relevant literature, comprising various operating concepts and the different climate conditions. In addition, ranking for various subassemblies of wind energy conversion systems concerning their impact on the overall system reliability is also presented in this paper to identify the weak items and subsystems. This identification guides the designers and planners in setting the appropriate maintenance strategies to increase the overall reliability of the considered systems and achieve a desired level of reliability. The results indicate that the model has practical applications for managing wind turbines, and the implementation demonstrates the proposed approach’s effectiveness and efficiency, which may significantly enhance the WECS reliability.

Circuit breaker (CB) and fault current limiter (FCL) are two major fault protection devices used in mesh-type DC microgrids. This paper proposes the parameters selection method to obtain a reliable and economic configuration scheme of CBs and FCLs applied in mesh-type DC microgrid. The breaking time of CB, the nominal breaking current of CB and the inductance of FCL are selected as three optimization parameters in an evaluation model. Since the reliability of fault protection scheme depends on whether the nominal breaking current of the CB is greater than the line current at the breaking moment of CB, it is necessary to accurately calculate the post-fault line current. Based on this, an accurate transient DC microgrid model is presented in this paper. And then, an improved non-dominated sorting genetic algorithm II (NSGA-II) is used to configure the parameters of CBs and FCLs quickly. Besides, a case study on six-terminal DC microgrid test system shows that the proposed method can obtain accurate post-fault line current and can achieve the parameters selection of CBs and FCLs.

In this paper, a finite control set model predictive direct power control (FCS-MPDPC) method based on satisfactory optimization, for single-phase three-level PWM rectifier, is proposed to achieve global optimization that takes into account all its objectives and constraints. Satisfaction optimization aims to obtain the satisfactory solution after coordination of multiple goals, instead of the optimal solution of a single goal. By replacing “optimal” with “satisfaction”, more control degrees of freedom are acquired, so that low-priority auxiliary control objectives can participate in the optimization process. Meanwhile, in order to enhance the description accuracy of FCS-MPDPC method for the future trend of PWM rectifier, the prediction time domain is extended from the traditional single-step to multi-step, and the average switching frequency model is established to realize the low switching frequency control. The satisfactory optimized FCS-MPDPC method proposed in this paper is compared, through simulation and experimental results, with the standard FCS-MPDPC method, which verifies the effectiveness and superiority of the proposed algorithm.

Recent development on 3D flash memories largely promotes the wide application of Solid-State Drives (SSDs) by providing larger capacity from vertically-stacked layers. However, there exist speed variations across different layers because of manufacturing process variations or physical designs, which induces new challenges to fully explore the advantages of existing SSDs, e.g. the parallel structure. This paper investigates the effect of speed variation on the parallel performance of SSDs. To balance chips’ workloads, traditional method selects chips in a round-robin way. As chip queue time can be estimated by some main factors, the chip also can be chosen in a greedy way. However, because of the layer speed variation, queue time estimation model should be modified. This paper first establishes a new queue time estimation model with the awareness of the flash layer information. Then the model is used to estimate the chip queue time and to direct write requests into the chip with the least queue time. The key idea is to largely reduce queue time of each write, thus reducing the average SSD response time. Finally, this new request redirection method is evaluated on SSDsim with real world workloads. Experimental results show that our model can estimate the queue time more accurately and our new request redirection method can improve 8.3% of write queue time on average under the situation of 4 times speed variation among 16 layers.

This paper addresses the problem of decoding non-binary low density parity check codes(LDPC) over finite field $GF(q)$ using symbol flipping approach. To achieve low complexity reliable communication, three new algorithms for improving the bit error rate performance of the non-binary LDPC decoder are presented. The first type is the symbol flipping decoding algorithm using a flipping function based on the channel reliability to identify the least reliable symbol position. In this algorithm, if the predicted symbol value satisfies the check sum, then the value is declared as correct otherwise the value is adjusted and sent back to the QAM detector. Algorithms 2 in this paper is an improvement to iterative joint detection-decoding algorithm by using the method of iterative hard decision based majority logic to select the new candidate symbol value. The feedback value to the QAM detector is adjusted by using Euclidean distance between the current symbol and the newly selected symbol value. Algorithm 3 is a low complexity version of Algorithm 2 which is derived by applying a majority voting scheme. In the majority voting scheme, symbols are short listed first by voting and all the computation are carried out only for the short listed least reliable symbols which significantly lowers the processing complexity. Numerical results and complexity analysis show that the proposed methods have good bit error rate versus complexity trade-off for various applications when compared with some existing algorithms.

This paper discusses contemporary problems concerning ship microgrids. It focuses on the role of power electronics and power quality issues, both conventional, such as voltage and frequency variations, and new issues, such as waveform distortions ensuing from the wide proliferation of power electronics in ship microgrids. The paper also contains a discussion on the provisions of the Unified Requirements of International Association of Classification Societies and other leading power quality standards in the industry, with an emphasis on Total Harmonic Distortion (THD) definition. An overview of power converters for high power applications in ships and their impact on ship networks is also given. Next, original results of various power quality phenomena recorded in ship microgrids are presented and commented on, followed by a review and recommendations for maritime microgrid modeling and signal processing methods for power quality assessment in the discussed systems. Finally, preliminary proposals for power quality control are presented.

Wireless charging is a convenient method of charging Electric Vehicles (EVs). Its application has been widely studied for electric cars but so far there have been limited experiments for electric bicycles (e-bikes). This paper addresses the design process and implementation details related to a wireless charger for a specific e-bike. Some issues such as the position of the secondary coil or the control algorithm prove to be crucial to the performance of the wireless transfer. Concerning the placement of the secondary coil, the paper proposes and validates a theoretical model to quantify the effects of the surrounding interfering materials. A CC-CV (Constant Current - Constant Voltage) control algorithm has been implemented to validate the theoretical results in these two charging phases. The control, the coils and the compensation networks have been designed to be simple and robust. The theoretical model, the charger and its control have proven to be effective in a real 84-W e-bike.

A new application of network reliability is proposed to help analyze a business process performance in usual business activities. This research is to construct an easy, formal and mathematical tool to probe the health of daily-run business activities. A business activity consists of a series of value-added tasks, which are carried out by their related attenders, to meet business objectives. Traditional management behaviors include practices and skills to sustain the plan, sanction, management, and analysis of business activities. However, the assessment of activity performance remains a weak gap in analytic requirements. The approach proposed in this paper is one of the expected tools to fill the gaps in traditional management practices. The paper is to provide managers several new visions of modeling and analysis, which are not easily derived by traditional management practices. A distributor process with several scenarios to explain the approach are explored, and discussed.

As a result of the increase in penetration of inverter-based generation such as wind and solar, the dynamics of the grid are being modified. These modifications may threaten the stability of the power system since the dynamics of these devices are completely different from those of rotating generators. Protection schemes need to evolve with the changes in the grid to successfully deliver their objectives of maintaining safe and reliable grid operations. This paper explores the theory of traveling waves and how they can be used to enable fast protection mechanisms. It surveys a list of signal processing methods to extract information on power system signals following a disturbance. The paper also presents a literature review of traveling wave-based protection methods at the transmission and distribution levels of the grid and for AC and DC configurations. The paper then discusses simulations tools to help design and implement protection schemes. A discussion of the anticipated evolution of protection mechanisms with the challenges facing the grid is also presented.

The emergence of fast-switching wide-bandgap (GaN, SiC) power electronics devices has enabled motor drive systems to achieve high efficiency, power density, control bandwidth and high-level of integration. However, the fast-switching speed and high switching frequency result in an increased level of motor overvoltage at both motor terminals and stator neutral. This overvoltage increases the stress across the motor winding insulation and bearings. This paper investigates three types of motor overvoltages, i.e., differential mode (DM) (phase-to-phase) motor terminal overvoltage, common mode (CM) (phase-to-ground) motor terminal overvoltage and CM stator neutral overvoltage (motor neutral to ground). Both the high switching speed (high dv/dt) effect and the high switching frequency effect on the motor overvoltage are investigated in this paper, where the high switching frequency effect has not been fully addressed in existing literature. Significant overvoltage is observed when the switching frequency or its multiples coincide with the cable or motor anti-resonant frequency. The anti-resonant behavior in the cable and motor impedance has been used to identify the overvoltage oscillation frequency and to explain the overvoltage observations for the three types of motor overvoltages. The analysis has been tested using a 7.5kW motor setup with and without a four-core cable, driven by a SiC or a GaN three-phase inverter with a switching frequency up to 250kHz and switching speed up to 40kV/ $\mu \text{s}$ . In addition, the motor bearing current, which is a main cause of bearing degradation, has also been tested and the increase of bearing current is observed due to the high frequency effect.

Commonly used variants of the proportional-integral, PI, and the integral-proportional, IP, compensator gains selections, merged with the $\mathfrak {D}$ -decomposition technique are presented in this paper. The motivation to this work is the willingness to check whether such a combination can lead to unified and perhaps simplified approach in this matter. Therefore, the $\mathfrak {D}$ -decomposition technique has been effectively combined with the frequency- and the time-domain driven requirements regarding the control dynamics. Criteria such as the gain- and phase-margins, $(GM, PM)$ , the sensitivity, $M_{\text {S}}$ , the pole placements by means of the $(\sigma, \omega _{\text {d}})$ and the $(\xi, \omega _{\text {n}})$ , and the overshoot with the rise time $(\delta, t_{\text {r}})$ are considered. It has been shown that the control design effort can be reduced by the means of the $\mathfrak {D}$ -decomposition to intuitive judgments in the proportional and integral gains coordinates $(K_{\text {P}}, K_{\text {I}})$ with parametric curves. As such it can be thought of as a promising scenario in a case considered. The analyses are presented and discussed in details. They are conducted basing on example of output voltage closed loop control of the Dual Active Bridge, DAB, converter. The circuit operates under the phase shift control scheme. The control-to-output transfer function identification and the control circuit delays are included in the analyses. The case analysis have shown that the time domain requirements are less effectively met with the PI regulator when compared to its IP configuration. This is due to the commonly used simplifications during conversion between the $(\xi, \omega _{\text {n}})$ and the $(\delta, t_{\text {r}})$ in presence of uncompensated zero of the closed loop transfer function. The paper contains complete and intelligible approach to dedicated mathematical investigations verified experimentally.

The power-gas integrated energy system lays a foundation for improving energy efficiency, promoting the large-scale utilization of renewable energy, and building a low-carbon sustainable energy system. However, the complex interaction between the power system and the natural gas system has brought about prominent, more diverse, and complex dynamic stability problems. Interference in one system will propagate to another system through coupling devices, which may cause serious disasters such as cascading failures. In order to analyze the transient process of the natural gas system caused by the adjustment of the coupling devices, this paper established a model for the coupling devices and the dynamic process of the natural gas system in the power-gas integrated energy system. By comparing the existing numerical calculation methods, the method of characteristic was selected to solve the hyperbolic partial differential equations, and the mathematical models of different nodes in the natural gas system were established. The accuracy and practicability of the algorithm are verified by 3 cases, and the accuracy of the algorithm is verified by case 1 and case 2 including the power-to-gas(P2G)and gas turbine. Case 3 verified the practicability of the algorithm by analyzing the fluctuation of the natural gas system caused by the adjustment of power-gas coupling links, and the adjustment is caused by the change of new energy generation. The results of this paper can analyze the interaction of coupling equipment and natural gas system, and lay the foundation for the realization of dynamic simulation of the whole integrated energy system.

In this paper, a quaternion-based adaptive dynamic surface control method is proposed for attitude tracking control for small-scale unmanned helicopters with external disturbance and uncertain dynamics. The quaternion formalism is introduced and a quaternion-based multi-input-multi-output nonlinear model is derived from the attitude dynamics of a small-scale helicopter. The low-complexity controllers are designed by the dynamic surface control method as it eliminates the problem of the explosion of items. The singularity problem is avoided by substituting Euler kinematic equations in the nonlinear model with quaternion expressions and integrating the quaternion expressions into the design process of the dynamic surface control. For improving the robustness of the control system, the radial basis function networks are applied to approximate the uncertain dynamics. The external disturbance is also compensated in the controllers’ design. This paper proves that the proposed method can guarantee the uniformly ultimate boundness of this attitude system. Simulation results are presented finally and show the effectiveness of this control approach.

This paper introduces a new method of estimating the variation interval and the expected value of optimal economic operation cost for the energy hub (EH) model considering load and renewable energy uncertainties in the residential district. Firstly, renewable energy and load uncertainties are defined as uncertain sets of historical data. Due to dispatch factors, the traditional EH model is non-linear and difficult to calculate and analyze. In this paper, a multi-step modeling method is developed for the breakdown of a complex EH model (CEH) into several simple EH (SEH) models and variable substitutions in each SEH, to eliminate the non-linearity of CEH. The upper and lower bound of the operating costs are then obtained based on the duality theorem and the expected value is calculated by expected value model. Finally, the case study in Beijing residential district is carried out to confirm the efficiency of the proposed method.

By the virtue of its highly nonlinear magnetic characteristics, the Switched Reluctance Machine (SRM) poses a formidable challenge for digital current regulators operating at a fixed switching frequency. Very fast tracking performance demanded by highly dynamic reference current profiles often surpass the conventional limits on closed-loop bandwidth posed by finite sampling frequency. The non-linear nature of matched disturbance to be compensated by the controller appearing in the form of induced emf grows in significance as a function of operating speed while the varying nature of inductance profile stipulates a need for gain adaptation by the control law in order to maintain consistency in closed-loop dynamic response. In the view of these unique SRM characteristics, the paper presents a detailed theoretical analysis of the widely implemented current control techniques from literature and provides illustrations in the context of their implementation in a digital controller. The analysis presented in this paper can also serve as a foundation for more advanced versions of these control techniques as well as their combinations.

In the era of paper-based contract, a lot of time, human labor and expenses are required to handle the process of contract drafting, contract signing, contract execution, and payment settlement. The emerging of electronic contract enhances the tedious signing process of paper-based contract and improves the efficiency of contract management. However, due to the centralized system architecture and the database-based storage schema, the stored contract data is at high risk of information leaking, data tampering and hacker attacks. In this study, we introduce Blockchain technology to the contract management, and develop a process-oriented contract management system (BEcontractor) for a Hangzhou-located power grid enterprise X, aiming to solve a series of security issues existing in the traditional electronic contract system. By deploying BEcontractor, procurement activities could be resumed online among X and its nation-widely commodity suppliers during COVID-19 epidemic. Up to September 2020, 6336 electronic contracts have been signed, with an accumulated amount of $\yen ~6.5$ billion. It is showed that the cost for accomplishing the contract signing process was significantly reduced, and the payment period was shortened from three months to around one month.

Impedance measurement is a practical method to obtain the impedance characteristic of the power electronic equipment (PEE), which is important for the small-signal stability analysis. In the impedance measurement, the measurement results may be influenced by the external noise. Therefore, it is essential to study how to avoid the measurement errors caused by the noise. To address this issue, this paper analyzes the method of suppressing the noise interference by enhancing signal-to-noise ratio (SNR) and concludes that there is limitation on improving the measurement accuracy by merely enhancing SNR due to the practical limitation on the perturbation amplitudes. And then this paper proposes an improved impedance measurement method, by which the measurement errors caused by the noise can be decreased effectively. By investigating the influence mechanism of the noise on the impedance measurement results, the measurement error can be divided into average component and fluctuant component. The average component can be eliminated by averaging two groups of measurement results with the phase difference of $\pi $ rad while the influence of the fluctuant component can be minimized by employing complex-linear fitting algorithm. Finally, experiments are conducted to verify the effectiveness of proposed impedance measurement method.

Pitting corrosion of rotating machinery is one of the most common faults in industrial engineering. The convolutional neural network (CNN) is increasingly applied to the fault diagnosis. However, the conventional CNN method will reduce the feature dimension of the collected signal and cause the loss of information during the pooling process. In this paper, a new method based on dilated CNN combined with spatial dropout (DCSD) is proposed to diagnose the early faults of rotating machinery. By filling the convolution kernel, the DCSD method can increase the receptive field of the CNN without increasing the number of parameters while retaining more features of the raw vibration signal of the rotating machine. To avoid the dropout method eliminates the adjacent elements with a strong correlation, the Spatial Dropout method is adopted to reduce the overfitting problem of deep networks. The early pitting gears experiment was designed to verify the DCSD method in this paper. The raw vibration signal data of 6 different healthy states were collected to verify the effectiveness of the method. The experimental results show that the DCSD method proposed can effectively distinguish the different early gears pitting, and the diagnostic accuracy is better than other popular deep learning methods.

Aero-turbines usually work in various non-stationary and harsh operating environments. Its blades easily appear early crack faults in long-time operation, and it is difficult to dig out discriminant features of early crack. To solve these problems, in the paper, a novel intelligent approach for early crack diagnosis of turbine blades using three-dimensional blade tip clearance is presented. In order to improve feature learning ability to obtain better generalization ability, the paper firstly develops a novel deep learning method based on deep belief networks (DBNs). Considering the fact that the feature degradation easily occurs in deeper layers because of the change of the distribution in each layer's outputs with the increase of the layers, it is hard to decide which layer to learn features is useful for fault diagnosis. Accordingly, in the pre-training process, the global back-reconstruction (GBR) mechanism is introduced into DBNs to optimize the feature learning ability. The GBR mechanism can be realized between the input layer and hidden layers by “shortcut connection”, and the layer to learn more discriminant features can be determined automatically without prior knowledge. Moreover, due to three-dimensional blade tip clearance (3-DBTC) acquired from three different directions of turbine blades contains much more useful crack failure multiscale information, it is suitable to be used as an input from which to extract multiscale discriminant features. Eventually, in the supervised training, the softmax regression model is employed to classify the health conditions of turbine blades using these sensitive features learned from 3-DBTC. The experimental results show that the proposed method can effectively identify the crack of turbine blades with fairly high diagnostic accuracies and significantly outperform other methods considered in the paper.

The fast development of electric vehicles (EVs) provides significant opportunities to further utilize clean energies in the automotive. On-board chargers (OBCs) are widely used in EVs because of their simple installation and low cost. Limited space in the vehicle and short charging time require an OBC to be power-dense and highly efficient. Moreover, the possibility for EVs to deliver power back to the grid has increased the interest in bidirectional power flow solutions in the automotive market. This paper presents a comprehensive overview and investigation on the state-of-the-art solutions of bidirectional OBCs. It reviews the current status, including architectures and configurations, smart operation modes, industry standards, major components, and commercially available products. A detailed overview of the promising topologies for bidirectional OBCs, including two-stage and single-stage structures, is provided. Future trends and challenges for topologies, wide bandgap technologies, thermal management, system integration, and wireless charging systems are also discussed in this paper.

Phase-locked loop (PLL) systems play a crucial role in grid synchronization. Since variations on the grid voltage parameters are in general uncertain, the dynamics of PLLs are by nature nonlinear. This fact imposes a relevant challenge to guarantee their stability. Unfortunately, as argued in this paper, there is a remarkable lack of global stability tests even for the most common approaches, such as the synchronous reference frame (SRF). In this case, there is only available a small-signal—linearized—model-based approach to stability. The main issue of resorting to local conclusions is that synchronization is forced to operate under conservative conditions, where large-signal variations are forbidden. Needless to say, this has a detrimental impact on applications, since performance is limited by small disturbance assumptions. Motivated by this problem, in the present work, we provide global asymptotic stability tests for two fundamental PLL algorithms. Namely, the conventional SRF-PLL and the enhanced SRF-EPLL. To do so, we use a Lyapunov approach acting directly on nonlinear trajectories. Consequently, the provided stability proofs do not rely on any linearization technique, frequency-domain conversion, or small-signal model representation. The main contribution in this paper is a set of stability conditions that are valid in a global sense. Moreover, it is shown that these results have direct practical implications in the form of new robust PLL gain tuning guidelines.

Solar energy technology has gained significant attention in recent years. It has strongly emerged as an alternative to the conventional mode of electricity generation for developing countries like India for their rising energy needs. Solar energy based electricity generation not only addresses environmental concerns but also increases the energy security and reduces the carbon footprints generated by the coal-based power plant. To boost the share of Renewable energy in the energy mix, the renewable energy policy introduced by the government has acted as a catalyst for large scale deployment of solar energy system to push it as the major energy alternative for India. The normal intensity of solar radiation in India is 220 MW per km square with around 300 sunny days in a year, whereas the coal-based plant generates a huge amount of carbon footprints. Therefore, solar based power generation has the potential of not only reducing the emissions and but also it can cater the rising energy demand. Thus solar photovoltaic plants has become a major alternative energy option in India with the ability to give an improved power supply, reduced global warming and enhance the security of energy supply. In this paper, efforts have been made to look into the overall perspective of solar energy and coal based generation by studying and analyzing the present status, technologies use, accessibility, policies interventions, major contributions, future potentials and trends of solar energy and fossil fuels in the Indian power sector. A feasibility analysis of solar technology implementation with the replacement of coal based plant pant is carried out for Singrauli, India. Results of the proposed study shows that the coal-based power plant generates a huge amount of carbon footprints and it can be reduced by replacing the coal based power plants with solar energy based power generation system. Consequently solar energy based power generation system is a key alternative for developing countries like India having metrological parameters similar to the case study done in this paper with the capacity to provide an improved supply, decreased global warming in addition to improving the energy security.

Integrating Distributed Energy Resources (DERs) and Micro-Grid (MG) into a system evolved the traditional power system. In spite of their significant advantages, MGs may result in volatility and uncertainty in the power systems. For reliable operation of the grid, energy trading among MGs should be optimized to maintain a fair trading price, maximize participants’ profit, and satisfy network constraints. In this paper, the optimal power trading among multiple reconfigurable MGs is formulated as a Mixed-Integer Nonlinear Programming (MINLP) considering all energy resources and their dynamic prices. In spite of the other methods in the literature, the proposed method minimizes the total cost (increase sales and decrease purchases) and transmission loss considering all energy resources in the MGs. In order to flatten the load profile, a time-based load profile is considered for the demand response program. The performance of the proposed model is evaluated on an IEEE 6-bus network as well as a modified IEEE 33-bus test system. The results verify that the proposed method, (i) determines the best configuration among MGs with a switching reduction of about 30%, (ii) optimizes the power generation of energy resources with 12% reduction in energy production, and (iii) optimizes the power trading costs with a 10% reduction in costs compared with the basic model without DR and trade that is introduced as $Scen.1$ in this paper.

The growth in sustainable generation technology such as fuel cell, wind energy conversion system, photovoltaic system, increase in fuel cost, energy necessity and the reduction in the fossil fuel reserve, for better power quality and reliability, is obliging the power sector to use the renewable based energy sources. In India, wind energy is gradually becoming an important and significant energy resource. Keeping in opinion the aforementioned wind energy prediction is becoming an essential study for harnessing the wind energy prospective. This paper proposes an effective technique based on intelligent approach for predicting wind power in different areas. This technique is based on using an intelligent model concerning the predicted gap to its similar one and two year old data. There are many intelligent and conventional models existed in literature for the wind power prediction like support vector machines (SVM), back propagation (BP) prediction etc. In this paper an effective fuzzy logic and model predictive control based models have been developed and offered for the wind power prediction for microgrid application by using air density and wind speed as the input parameters for fuzzy system. The outcomes are compared with the computed data and existing models and it can be observed that the different errors are found within the permissible limits. The outcomes obtained from fuzzy based technique are very close to calculated values if compared with model predictive based technique. Hence, the proposed models can be employed for the prediction of wind speed and wind power generation in the selected stations. The existing models results are compared with Kolkata city outcomes. The Error RMSE with Support vector machine, Back propagation, Model of forecast error correction +SVM and Model of forecast errors correction +BP, Neural Network method, model predictive based system, and proposed fuzzy logic based system are 30.48%, 32.83%, 26.81%, 28.58%, 1.1431%, 1.38% and 1.12% respectively. Therefore, the proposed techniques provide the best results and even these are observed within the suitable limits. Additionally, the achieved outcomes can be used for Microgrid/SmartGrid applications.

This paper discusses the problem of fault estimation for two-dimensional (2-D) Fornasini-Marchesini (FM) dynamical systems. The objective of this paper is to design a fault estimation filter to reconstruct the characteristics of faults in low-frequency domain and satisfy different performance levels. Utilizing the generalized Kalman-Yakubovich-Popov (GKYP) lemma, this problem is transformed into a multi-objective optimization problem, which is non-convex in essence. On this basis, an optimization algorithm is proposed to solve the non-convex optimization problem. Sufficient conditions are derived for the proposed fault estimation filter. Finally, simulation results show the effectiveness of the theoretical results.

In this paper, a fault-tolerant control (FTC) method for robotic manipulators is proposed to deal with the lumped uncertainties and faults in case of lacking tachometer sensors in the system. First, the third-order sliding mode (TOSM) observer is performed to approximate system velocities and the lumped uncertainties and faults. This observer provides estimation information with high precision, low chattering phenomenon, and finite-time convergence. Then, an FTC method is proposed based on a non-singular fast terminal switching function and the TOSM observer. This combination provides robust features in dealing with the lumped uncertainties and faults, increases the control performance, reduces chattering phenomenon, and guarantees fast finite-time convergence. Especially, this paper considers both two periods of time, in which before and after the convergence process takes place. The stability and the finite-time convergence of the proposed controller-observer technique is demonstrated using the Lyapunov theory. Finally, to verify the effectiveness of the proposed controller-observer technique, computer simulation on a serial two-link robotic manipulator is performed.

This paper has proposed a novel bearing fault detection method about adaptive Sparse-spike Deconvolution based on Curvelet Transform (CTSSD), where the novel technique about adaptive Sparse-spike Deconvolution names after ASSD. Its purpose is to recover the pulse sequence from a vibration signal including complex noise, and to evaluate the periodic pulse position and pulse amplitude. Firstly, in order to make the results sparse and improves the stability of the result, the L1 norm regularization method is proposed in this paper, which is used to constrain the signal pulse sequence sparsely. Secondly, considering that regularization parameters are not adaptive, the Quantum behavior Particle Swarm Optimization (QPSO) algorithm is proposed to determine the optimal regularization parameters, adaptively. Finally, considering that the periodic features of ASSD extraction are not continuous, the Curvelet transform is further introduced. The fault signal is transformed into the Curvelet domain, and the Curvelet coefficient is used to characterize the fault signal pulse sequence. This method proposed in this paper is applied to the simulation signal and the vibration signal of rolling bearing fault, and is compared with the ASSD and the minimum entropy deconvolution (MED) to verify the reliability and effectiveness.

The advantages of IoT are incontrovertible; however, significant risks and uncertainties over the protection of best practices and their related costs prevent many companies from adopting the technology. Also, users are aware of the consequences of breaches of IoT protection. Recent research indicates that 90% of consumers lack confidence in the safety of IoT devices. IoT defense has been described as one of the weakest areas. In this respect, significant efforts have been made, often through traditional cryptographic methods, to overcome security and privacy issues in IoT systems. The list of security issues (confidentiality, integrity, authentication, and availability) must be addressed to secure IoT devices from attack. IoT nodes’ specific features do not adequately protect the whole security spectrum of IoT networks through existing solutions. This paper aims to provide security to the IoT devices using nature-inspired Gravitational Search-guided artificial neural key. In this paper, artificial neural synchronization is used to create a neural key exchange protocol between two IoT devices over a public channel for cryptographic purposes. This proposed technique has many benefits, such as 1) it provides an optimized design of the neural network that facilitates the development and establishment of a neural key between the two approved IoT devices. 2) It offers the sharing of the private neural key over the public channel via artificial neural synchronization 3)Three hidden layers of the neural network contribute to the deep internal design. So, it’s going to be hard for the intruder to infer the internal layout. 4) The increase in the weight spectrum of the neural network raises the complexity of an effective attack exponentially, but the effort to create a neural key decreases over polynomial time. Various parametric experiments have been conducted out on the proposed methodology. The simulations of the procedure demonstrate efficacy in terms of the findings cited in the paper.

The BaSIC(DMM) topology has been experimentally demonstrated to improve the short-circuit time for a 1.2 kV SiC power MOSFET product from $4.8~\mu \text{s}$ to $7.9~\mu \text{s}$ with a 17% increase in on-state resistance by utilizing a commercially available 100 V rated Gate-Source-Shorted (GSS) Si Depletion-Mode power MOSFET (DMM). The optimization of the Si GSS-DMM is discussed in this paper to achieve even superior performance, namely larger short-circuit time with less increase in on-resistance. It is theoretically demonstrated for the first time that a highly desirable short-circuit time of $10~\mu \text{s}$ , similar to Si IGBTs, can be achieved for two SiC power MOSFET products with less than 3% increase in on-resistance. This was accomplished by reducing the breakdown voltage rating of the Si GSS-DMM from 100 V to 30 V, altering the cell design parameters, and utilizing the trench-gate design. The theoretical analysis provided in this paper provides valuable design guidelines for manufacturers of Si GSS-DMM devices to achieve optimum performance for use in the BaSIC(DMM) topology.

This paper reviews motor techniques for reducing the cost of electric vehicles (EVs) and improving their range. In recent years, environmental issues, energy crises and the greenhouse effect have urged the popularization of clean energy EVs. In order to achieve this goal, it is necessary to overcome technical difficulties in vehicle cost and range. As a key component of an EV, the motor occupies a large proportion of the overall vehicle cost, and its efficiency directly affects the mileage. In this context, this article discusses the merits and challenges of three mainstream EV motors: permanent magnet synchronous motor (PMSM), induction motor (IM), and switched reluctance motor (SRM) in terms of vehicle cost and range. Then this paper compares the advanced techniques of these motors in terms of topology, material applications and control strategies. Finally, the development trends and opportunities of the three motors in EVs are predicted.