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In order to achieve the purpose of extending the speed range and reducing power electronics devices for the permanent-magnet linear motor drive system, a half-centralized open-end winding (OEW) topology is studied for rail transit applications in this paper. In this topology, compared with the traditional OEW topology, the number of voltage-source-inverters (VSIs) can be reduced from four to three to drive two OEW movers and all these VSIs share a common dc bus voltage. In order to improve the steady-state performances, a four-vector phase model predictive voltage control (FV-PMPVC) is proposed in this paper. Due to the spatial distribution of phase voltage vector (PVV), an orthometric synthesis principle (OSP) is proposed to calculated the duration time for the vector synthesis, which reduces the computation burden and enhances the robustness. Comparing the existing control method, FV-PMPVC can get similar dynamic performances but better steady-state performances. Additionally, the half-centralized topology using FV-PMPVC can have same speed range while less VSIs are required. The effectiveness of FV-PMPVC is verified by experimental results. [ABSTRACT FROM AUTHOR]

Miniaturization and low cost contribute to the development and popularization of wireless power transfer (WPT). Reducing the number of power conversion stages can reduce the volume and cost of the WPT converter, and even make it possible to improve the efficiency. A single-stage WPT converter with constant current (CC) and constant voltage (CV) output and its asymmetric modulation method are proposed in this paper. A direct AC-AC converter is applied to the primary side of the WPT converter to directly convert line-frequency AC to high-frequency AC. The applied direct AC-AC converter that can replace the commonly used multi-stage primary converter reduces the number of circuit devices, thereby reducing the volume and cost of primary converter. The proposed WPT converter can realize zero voltage switching (ZVS) and power factor correction (PFC). In order to achieve CC and CV output, a switchable hybrid compensation topology is applied to the proposed WPT converter. A 720-W experimental prototype was manufactured to verify the rationality of the proposed WPT converter and the correctness of the theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper presents an isolated single-stage on-board electric vehicle charger without an intermediate DC-link. Based on an isolated current-source topology, the converter features soft-switching in semiconductors regardless of load variation for the full AC line voltage range. Moreover, it requires no external snubber or clamp circuits. The power factor correction and voltage regulation are provided by a relatively simple phase shift modulation, while the amount of circulating energy is kept at minimum. The charger is distinguished by its efficiency characteristic – the maximum is achieved in the constant power charging mode. The control method, component stresses, and design constraints of the topology are analyzed. The concept is verified using a 3 kW experimental SiC-based prototype, which reaches a peak efficiency of 96.4%. Moreover, the charger has demonstrated efficiencies above 95% with the THD of 4.1% when operating in constant power mode at the maximal power. [ABSTRACT FROM AUTHOR]

This paper presents a novel active power control scheme for SRMs that are used as S/G units at MEAs; the proposed method uses a vector-controlled SAF, facilitating the acceleration of the SRM during starter mode and the efficient power control of the SRG at various operational points during generator mode. Moreover, an energy storage unit is incorporated in the SAF, aiming at enhancing the SRM's starting torque production and taking full advantage of the SRG's energy generation capability, through the appropriate phases’ magnetization regulation that is imposed by the developed adaptive SAF vector control. In addition, the proposed scheme provides enhanced FRTC during both modes of operation. The mathematical analysis is verified through MATLAB/Simulink simulations, while the performance of the S/G concept under study is evaluated via real-time CHIL tests, with the use of the dSPACE 1202 (MicroLabBox) platform and the 16-bit dsPIC30F4011 microcontroller. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) and cell-free (CF) massive multiple-input multiple-output (MIMO) are two promising technologies for realizing beyond-fifth generation (5G) networks. In this paper, we study the uplink spectral efficiency (SE) of a practical spatially correlated RISs-aided CF massive MIMO system over Rician fading channels. Specifically, we derive the closed-form expression for characterizing the uplink SE of the system, which shows that increasing the number of RIS elements can improve the system performance. Moreover, the results unveil that the spatial correlation of RIS has a significant impact on the system while leading to the best performance gain at a half wavelength spacing. Finally, the accuracy of our analytical results are verified by Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

Due to the forecasted fast increasing cellular traffic and the already highly congested licensed spectrum, it is critical to exploit and utilize the unlicensed spectrum resources for the fifth-generation (5G) and beyond networks. A challenging problem is the coexistence of 5G and other networks with fair, reliable, and efficient sharing of the unlicensed spectrum. In this paper, we propose a blockchain-enhanced distributed spectrum sharing scheme for coexisting multiple operators and multiple WiFi APs. We design a novel lightweight and efficient consensus mechanism, named Proof of Strategy (PoG). In this consensus mechanism, the problem of spectrum sharing is used as a consensus puzzle, and the part of the unlicensed spectrum is used as the ‘fee’ of miners. With such a design, the computing overhead of the consensus process is expected to be reduced significantly. We develop a non-cooperative game to analyze the behavior of the miners and obtain a symmetric Bayesian Nash equilibrium under the uniform distribution of mining cost estimation. It can be found mathematically and experimentally that the strategy of the winner tends to maximize the system revenue by sharing the unlicensed spectrum resource. Furthermore, to reduce the impact of heavy interactions on system throughput, the operation of WiFi APs in the proposed scheme can be adaptively switched between ‘contention mode’ and ‘blockchain mode’ according to the network traffic load. The dynamic behavior is constructed as an evolutionary game, and the existence and uniqueness of equilibrium points are proved by theoretical analysis. Simulations demonstrated the fairness and effectiveness of the proposed blockchain-based scheme and the mode switching method for distributed spectrum sharing by heterogeneous wireless networks. [ABSTRACT FROM AUTHOR]

The use of the emerging hybrid analog-digital structure for future millimeter-wave communications has attracted much attention. Although this structure can reduce the power consumption considerably, the spatial covariance matrix (SCM), as the core of subspace-based direction of arrival (DOA) estimation algorithms, cannot be obtained directly. The beam sweeping algorithm (BSA) was proposed for SCM reconstruction from compressed measurements. However, the BSA is computationally intensive owing to the high-dimensional matrix-to-matrix multiplication and matrix inversion. To address this issue, a BSA algorithm with high accuracy and low computational-cost using the submatrix multiplication (BSASM) is proposed in this paper. By appropriately adjusting the weight, which consists of a switch and a phase shifter, connected to each antenna, the SCM can be accurately reconstructed with low-dimensional matrix-to-vector multiplication and 2-dimensional matrix inversion, thus reducing the computational-cost significantly. After SCM reconstruction, various DOA estimation algorithms can be exploited to obtain the DOA information. Simulation experiments are conducted to verify the performance of the proposed algorithm. The results indicate that using a substantially lower computational-cost, BSASM can reconstruct SCM more accurately than BSA. [ABSTRACT FROM AUTHOR]

In subway systems, increasing attention has been paid to improve energy efficiency due to remarkable energy consumption for rail transportation operation. The optimization of single-train driving control and multi-train operation synergy are two critical and closely related aspects for energy saving, but they are rarely solved in an integrative manner. The comprehensive study on these two aspects is a complex, large-scale, multi-variable and constrained task, which involves nested, coupled and mutual-input optimization processes. This paper proposes an energy-efficient integrated model, which includes optimizing single-train operation control in an inner model and multi-train operation synergy, committing to the utilization of regenerative braking energy (RBE) in an outer model. A parallelized particle swarm optimization based on Map-Reduce (PPSO-MR) algorithm is proposed to solve the integrated model to reduce the execution time. Two concepts of temporal-spatial record and time shift are introduced to derive the movement of a train at inter-stations for the operation adjustment of multiple trains on a subway line. Experimental results show that the proposed control model solved by the holistic optimization approach can achieve lower energy consumption with fast execution time. This study provides the novel model and algorithm to obtain energy-saving schedules serving the multi-train operation coordination. [ABSTRACT FROM AUTHOR]

Two-stage AC-DC converters are considered as a prominent solution for DC-type electric vehicle (EV) chargers. However, this kind of architecture suffers from high switching losses with large heatsink and DC-link capacitor volume. To relieve this issue, this paper presents a new hybrid modulation for DC-type EV chargers, where a two-phase clamped discontinuous pulse-width-modulation (DPWM) in the front-end circuit is cooperated with the variable frequency triangular-current-mode (TCM) zero voltage switching (ZVS) or its simplified implementation, i.e., boundary-ZVS (B-ZVS) strategy, in the back-end circuit. The former can stop the switching actions in the front-end stage during two-thirds of the grid period, while the AC currents are at their highest values, which can yield to the best switching loss reduction and deliver high power factor operation. Besides, TCM-ZVS or B-ZVS modulations can achieve ZVS turn-on action for all semiconductors during all operating range in the DC-DC stage to further reduce the power losses on the semiconductors. With such characteristics, the proposed strategies can reduce the switching losses of the system to the best extent, and thus allow an enhancement of the system power density by improving the power conversion efficiency. The proposed strategy is described, analyzed, validated, and benchmarked in a 5 kW SMD SiC MOSFET-based two-stage AC-DC converter. A 99% power efficiency can be achieved with the solution implementing the TCM-ZVS strategy at an output voltage of 400 V and rated power. [ABSTRACT FROM AUTHOR]

In this paper, a switched multibeam multi-sector array antenna is proposed to provide 3-D coverage for vehicle to infrastructure (V2I) under 5G-IoT application framework. The multi-sector design is optimized using a quality-conscious communication area synthesis process to achieve $\mathbf {360}^\circ$ coverage in azimuth. Each sector of the design has two microstrip array antenna (MAA) to obtain coverage in the upper and lower halves of the elevation region. The proposed antenna is designed to enhance frequency-dependent beam squint phenomena exploited to achieve multibeam coverage in the elevation region. The simulation results of the proposed antenna having $\mathbf {3\times 2}$ size of MAA indicates the achieved desired radiation characteristics, and a prototype of the same operating in WLAN band ($\mathbf {5.15-5.825}$ GHz) is fabricated for verification. The experimental results show the maximum realized gain is $\mathbf {7.85}$ dBi and the beam tilt of $\mathbf {10.8}^\circ$ to $\mathbf {46.8}^\circ$ in elevation is achieved at central frequencies $\mathbf {5.15}$ GHz and $\mathbf {5.825}$ GHz, respectively. The coverage obtained is $\mathbf {360}^\circ$ in azimuth and $\mathbf {93.6}^\circ$ in elevation. The signal to interference ratio is measured around the antenna, which shows interference suppression of more than $\mathbf {10}$ dB achieved between the MAAs of alternate sectors. Moreover, the port isolation is better than $\mathbf {26}$ dB. Hence, sixteen simultaneous beams utilizing frequency re-use can be operated in the 3-D space around the access point to communicate with multiple drones/vehicles and IoT nodes to realize a smart vehicular application. [ABSTRACT FROM AUTHOR]

Improving the efficiency of traffic signal control is an effective way to alleviate traffic congestion at signalized intersections. To achieve effective management of the system-wide traffic flows, current research tends to focus on applying reinforcement learning (RL) techniques for collaborative traffic signal control in a traffic road network. However, the existing collaboration-based methods often ignore the impact of transmission delay for exchanging traffic flow information on the system. Most of the studies assume that the signal controllers can collect all instantaneous vehicular features without delay. To fill the gap, we propose an RL-based cooperative traffic signal control scheme considering the data transmission delay issue in a traffic road network. In this paper, we (1) design our new RL agents to cooperatively control the traffic signals by improving the reward and state representation based on the state-of-the-art max-pressure control theory; (2) propose a traffic state prediction method to address the data transmission delay issue by decreasing the discrepancy between the real-time and delayed traffic conditions; (3) evaluated the performance of our proposed work on both synthetic and real-world scenarios with a different range of data transmission delays. The results demonstrate that our method surpassed the performance of the previous max-pressure-based traffic signal control methods and addressed the data transmission delay issue. [ABSTRACT FROM AUTHOR]

This paper investigates the outage and throughput performance of full-duplex (FD) cooperative relaying (CR) based non-orthogonal multiple access system (NOMA) with energy harvesting (EH) i.e., FD-CR-EH-NOMA system. We consider a network scenario, where the base station (BS) serves two downlink users, with the near user configured as a FD relay to deliver messages to the far user. We derive analytical expressions for the outage probabilities experienced by the users and the system outage probability of FD-CR-EH-NOMA network under time switching relaying (TSR) protocol in the presence/absence of direct link from BS to the far user. Assuming imperfect successive interference cancellation (i-SIC), we derive analytical expressions for (i) optimal power allocation (OPA) factor at the BS and (ii) optimal time switching (OTS) factor at the relay that independently minimizes the system outage probability. Further, we use the alternating optimization technique to determine the jointly optimal power allocation and time switching factors that minimize the system outage probability. Furthermore, we determine the OTS factor that maximizes the asymptotic throughput of the system in the delay-limited transmission mode. With the help of numerical and simulation investigations, we show that the system outage and throughput of the considered network improve significantly under the proposed schemes. [ABSTRACT FROM AUTHOR]

Design of Inductive Power Transfer (IPT) controller to tune EV charging level in a wide range is of great importance. The IPT power level controller is proposed to regulate the power transfer rate by modulating the active state and zero state counts of the converter. During active states, energy injection is applied to the IPT compensation tank which increases the IPT resonant current; during the zero state; no injection occurs, and the resonant current of IPT tank is in free oscillation. The FPGA-based IPT power controller is designed to be applied on single stage AC-AC matrix converter which allows direct connection to the main grid without any need of DC conversion; the controller is also operational in dual-stage AC-DC-AC topologies. The proposed IPT power controller is self-tuned without any need to wireless communication channel and offers more simplicity, higher speed, ease of implementation and lower cost. The efficiency up to 90.73% is achieved for the proposed IPT controller thanks to soft-switching (ZCS and ZVS). Finally, ModelSim-Quartus simulation results as well as experimental validation results are provided. [ABSTRACT FROM AUTHOR]

Railway point machines (RPMs) is one of the most vital devices closely related to the efficiency and safety of train operation. Considering the advantages of contactlessness and easy-to-collect of sound signals, a novel sound-based fault diagnosis method for RPMs is proposed. First, fractional calculus is introduced to wavelet packet decomposition energy entropy (WPDE). Fractional WPDE (FWPDE) is then proposed, which is verified to be a more effective tool for fault feature representation. Second, coarse-grain process is firstly introduced to FWPDE. Novel feature named multi-scale FWPDE is developed, which can significantly improve fault diagnosis accuracy. Third, to select optimal feature set and optimize the hyperparameters of support vector machine (SVM) at the same time, a synchronous optimization strategy based on binary particle swarm optimization (BPSO) is presented, which can further improve the diagnosis accuracy. The superiority and effectiveness of the proposed method are verified by comparing to some existing fault diagnosis methods. The diagnosis accuracies of reverse-normal and normal-reverse switching processes reach 99.33% and 99.67%, respectively. Especially, the proposed method is suitable for diagnosis of similar faults, which can also provide reference for similar research fields. [ABSTRACT FROM AUTHOR]

Considering the advantages of contactless fault diagnosis, a novel sound based fault diagnosis method for railway point machines (RPMs) is proposed. Firstly, a denoising method based on empirical mode decomposition (EMD) is proposed. The useful intrinsic mode functions (IMFs) are selected using kurtosis and energy criteria to reconstruct the denoised signal. Then, multi-scale fractional permutation entropy (MFPE) is proposed inspired by fractional calculus, which is more powerful than the classical multi-scale permutation entropy (MPE). And a two-scale algorithm is developed to avoid neglecting the information contained at the end of the signals in the coarse-graining process. Finally, the feasibility and superiority of the proposed method (D-FMPE-T) based on denoising method and two-scale algorithm are verified using support vector machine optimized by particle swarm optimization (PSO-SVM) through comparing with some commonly used feature extraction and classification methods. Besides, CWRU is also utilized for verification of the superiority of the proposed method. Experiment results show that the proposed method performs best. The identification accuracies on normal-reverse and reverse-normal switching processes, and CWRU data sets reach 99.3%, 99%, and 99.17% respectively, demonstrating the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This article presents the feasibility of a flyback charger for electric vehicles (EV) based on silicon-carbide (SiC) devices. The flyback topology is simplest, but its device voltage stresses are strongly affected by the transformer leakage inductance. To reduce the device voltage stresses by recovering the energy stored in the transformer leakage inductance, an active-clamp circuit and active snubber circuit are adopted in both sides of the transformer. Also, the active-clamp circuit helps to reduce the switching losses by making zero-voltage-switching (ZVS) condition. By deriving the loss equations of switching devices and transformer as a function of the switching frequency and magnetic flux swing, design optimization considering loss and volume is attempted. The snubber capacity and diode voltage stress are quantitatively suggested through the analysis of the power absorbed by the active snubber. Based on the analysis, a 3.3 kW/100 kHz prototype is designed and experimented to show the feasibility. Test results demonstrate 96.7% peak efficiency and 96.4% full load efficiency at 330V output voltage. [ABSTRACT FROM AUTHOR]

The boom of electric vehicles (EVs) has urged new designs and applications of power conversion technologies. Power converters, as one of the most critical components in EV battery systems, have seen significant developments in recent years. However, thus far forward design approaches for power converter topologies have been widely adopted, which are based on engineers’ empirical knowledge and instinct. This has been deemed having low design efficiency with high randomness and limited applicability, due to the absence of a systematic guideline. This approach, though widely adopted, can no longer meet the increasingly stringent and diverse needs of today’s research and industry, with the emerging trend of renewable energy sources. Aware of these drawbacks, in this study, we propose a novel reverse design approach through establishing general polynomial relations between the topology and voltage gain of high-step-up converters, which are found to be functions of basic boost converters’ voltage gains. With this newly formed polynomial relation, a generalized approach to devising power converters for various industrial needs can be derived, which is baptized the General Polynomial Reverse Design (GPRD) approach. Three polynomial converters are derived as examples to validate the proposed method, whereby their functionality and performances are verified and tested by prototype experiments, which substantiate the proposed design theory. [ABSTRACT FROM AUTHOR]

Adaptive traffic light signal control (ATSC) is a promising paradigm for alleviating traffic congestion in intelligent transportation systems. Most of the existing methods require heavy traffic data exchange among neighboring intersections to achieve collaborative ATSC, which may not be supported by bandwidth-limited communication links in practice. In this article, we develop a communication-efficient decentralized ATSC framework for traffic networks with multiple intersections, where each intersection only exchanges traffic statistics with its neighboring intersections. In particular, the proposed framework consists of a generative adversarial network (GAN) based algorithm for traffic data recovery, and a multi-agent deep reinforcement learning (DRL) based decentralized ATSC algorithm for traffic efficiency enhancement. By adopting the value decomposition technique that establishes a nonlinear mapping from the local state-action values to the global reward, each intersection can independently determine its traffic light signal based on its local traffic data while achieving collaboration among neighboring intersections. Our proposed decentralized ATSC framework is scalable to large-scale traffic networks, and is also robust to traffic flow variations via interacting with the environment. Simulations show that our proposed algorithm can significantly reduce the vehicle travel time while maintaining high and stable traffic throughput. [ABSTRACT FROM AUTHOR]

In this study, we investigate the problem of inter-vehicle communication topology (IVCT) assignment and control for vehicular platoons in LTE-V2V networks based on the cooperative awareness message dissemination mechanism. A sampled-data feedback controller is proposed for platoons to eliminate the effect of stochastic packet dropouts and external disturbance, where the controller gain depends on the IVCT. To guarantee the stability requirement of a platoon with the minimized cost function, a unified control framework is established to jointly determine the optimal IVCT from all the available ones and the associated feedback controller gain. This co-design procedure is based on the optimal control and dynamic programming technique, where both fixed and periodic switching IVCTs are available. A useful algorithm is proposed to implement the established co-design framework. Furthermore, we present numerical examples to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

With Mobile Edge Computing (MEC), computational intensive applications can be offloaded to the nearby edge servers to support latency-sensitive applications on mobile devices. Different from the cloud, edge servers usually have limited resources, and then selecting which edge server to run the offloaded computation becomes an important issue. Although server selection has received considerable attention, not much work has been done to consider the limited coverage of the edge server and the frequent user movement, which introduce many dynamic changing factors affecting the workload of the edge server and making it hard to achieve long-term optimum in the edge server selection. To deal with these challenges, we model the problem of continuous server selection as a Markov Decision Process (MDP). The difficulty of this problem is that achieving long-term optimum requires future knowledge, such as user mobility, server workload, etc, which is not known a priori. We do not have such knowledge and thus cannot find the optimal policy through traditional methods. To address this problem, we propose a Deep Reinforcement Learning (DRL) based algorithm to learn the selection policy based on the observed performance of past server selections. Specifically, a Long Short-Term Memory (LSTM) based neural network is exploited to encode the historical information which helps infer future knowledge of the dynamically changing factors. Then the DRL model selects the optimal server automatically based on the extracted system states. Extensive trace-driven evaluations demonstrate that the proposed DRL-based algorithm has the lowest overall cost compared to existing solutions. [ABSTRACT FROM AUTHOR]

The urban rail transit system has the characteristics of wide voltage fluctuation, intermittent and strong impact load, limited heat dissipation capacity. The high-speed flywheel energy storage system (FESS) is used to provide network voltage stability and regenerative braking energy recovery due to its high power density, unlimited number of charge-discharge cycles, fast response and environmental friendliness. When considering the design of high-speed FESS converter with 3.6 kHz fundamental frequency and 330 kW rated power used in 1500 VDC urban rail transit system, the two-stage topological converter reduces the efficiency and increase the cost and size, meanwhile, the series-connected converters and the multilevel converter increase the difficulties of control and insulation, so the two-level and I-type three-level converters of high-speed FESS are designed and evaluated. Several comparisons are made by detailed experimental data from the perspective of the traction load characteristics of the 1500 VDC urban rail transit system and the technical and economical requirements of the high-speed FESS. It is found that the three-level converter has significant advantages in matching the traction load characteristics for its higher duty cycle capability, as well as improving the technical and economical performances such as efficiency, du/dt value, THD, voltage stability, and reducing the cost by 40% when compared to the two-level converter. While in the future MW class high-speed FESS development, the maximum output power capacity of the three-level FESS is relatively lower than that of the two-level FESS. The theoretical analyses were verified by experiments. [ABSTRACT FROM AUTHOR]

The emerging 5G New Radio (NR) cellular systems that may operate in millimeter-wave (mmWave) frequency bands are expected to offer larger bandwidths. They are to be deployed in densely crowded environments, where the traffic load has a high degree of variability, which may introduce capacity bottlenecks. One of the options to alleviate the latter is to concurrently utilize the radio resources available in unlicensed mmWave bands, e.g., at 60 GHz. In this work, we address the coexistence of mmWave-based NR Unlicensed (NR-U) and WiGig technologies and account for the mmWave-specific directionality, propagation, and blockage effects. By further incorporating the features of duty cycling and random access operation, we construct a mathematical framework, which is capable of characterizing the achievable data rates of the NR-U users that operate over both licensed and unlicensed mmWave spectrum simultaneously. Our numerical results demonstrate that the rate attained by such devices is primarily regulated by the initial contention window size that, in its turn, heavily depends on the system and environmental parameters. We report the optimal contention window values for a wide range of blocker and user densities as well as antenna array configurations. [ABSTRACT FROM AUTHOR]

The safety of vulnerable road users is paramount, particularly as we move towards the widespread adoption of autonomous and self-driving vehicles. In this study, we investigate the use of a six-element distributed antenna system (DAS), operating at 5.8 GHz and mounted on the exterior (i.e., roof and wing mirrors) of an automobile, to enhance signal reliability for pedestrian-to-vehicle (P2V) communications. Due to its low complexity and ease of implementation, we consider the use of a switch-and-examine combining with post-examining selection (SECps) scheme to combine the signal received by the DAS. During our experiments, a pedestrian wearing a wireless device on their chest either stood stationary or walked by the side of a road. It was found that the overall signal reliability depends on not only the number, but also different groupings of the antennas which are selected. The goodness-of-fit results have shown that the temporal behavior of the diversity gain was adequately described by the Gaussian distribution. Building upon this, we also provide some useful insights into the antenna selection through the comparison of three different antenna selection mechanisms, namely per-sample random antenna selection, one-shot antenna selection and per-sample optimal antenna selection. [ABSTRACT FROM AUTHOR]

Conventional current-fed resonant converter suffers from high turn-off loss over wide range of fuel-cell voltage. To alleviate this problem, we propose high voltage gain current-fed resonant converter that achieves almost ZVS turn-off over a wide range of voltage gain. By employing a bidirectional switch across center nodes of the voltage doubler and corresponding modulation, the presented converter achieved almost ZVS at the turn-off instant; this trait significantly increases the power conversion efficiency even under high frequency operation. The inherent boost function of the current doubler, an additional boosting operation using a bidirectional switch, and double boosting of the voltage doubler enable the presented converter to achieve high voltage gain without having to use a transformer that has a high turns-ratio. Moreover, 180 $^\circ$ phase interleaving reduces the input current ripple to zero. The steady-state operation is analyzed comprehensively, and design considerations of the proposed converter are given. Finally, a prototype with input of 48-72 V, output of 380 V, and rated power of 1 kW is developed to validate the effectiveness and feasibility of the proposed converter. [ABSTRACT FROM AUTHOR]