Converter Modules Research Articles

Study on the energy harvesting and hydrodynamic stability characteristics of a novel floating bridge with wave energy conversion modules

Integrating floating bridges with wave energy converters can provide a viable option for developing economical wave energy resources, and solving problems of the high cost of wave energy devices and the unstable motion of floating bridges. This paper proposes a novel wave energy floating bridge with an integrated wave energy conversion module (WECM), and its energy capture and hydrodynamic stability problems are investigated. A nonlinear stiffness power take off (PTO) mechanism is used. A hybrid dynamics model for the system is established and the accuracy of numerical model is verified. The energy capture and motion stability of the linear PTO and nonlinear PTO wave energy floating bridge under regular and irregular wave conditions are compared. Results show that WECM can enhance the floating bridge with wave power generation capability and better motion stability in waves. The linear PTO mechanism can reduce the motion response of the floating bridge by choosing the appropriate PTO damping value under regular waves. The nonlinear PTO mechanism increases the double-peak width to broaden the energy capture frequency band. The nonlinear PTO is more suitable for low-frequency wave sea conditions, while the linear PTO is more suitable for high-frequency wave sea conditions. This article can provide favorable reference data for floating bridge design and practical application in the future.

A thin, wideband transmissive cross polarization converter.

This study presents a very thin wideband linear polarization converter in transmission mode with near-unity conversion efficiency. The suggested converter consists of a periodic array on a single-layer substrate, two metallic layers and six vias. Metallic vias connect the upper and lower layers of the construction. The radiated electromagnetic wave with linear polarization can be transformed into its orthogonal component in the transmission mode by the proposed converter. The suggested polarization converter operates well in the 9.53-13.35 GHz frequency band (36%). Additionally, The structure provides a larger than 90% Polarization Conversion Ratio (PCR) through the frequency range of 8.89-14.21 GHz. The conversion mechanism has been explained and confirmed through both surface current distribution, electric charge distribution and experimental tests. Over the whole frequency range, there is good agreement between the simulated and measured results.

Energy Efficiency Improvements in Wind Energy Systems via Sensorless Soft-Switching Control

This study implements a series resonant converter (SRC) and pulse density modulation (PDM) power control strategies to minimize switching losses and improve the efficiency of an off-grid, small-scale wind energy conversion system (WECS). Additionally, the maximum power point tracking (MPPT) method was employed to further reduce costs and increase system reliability. The "perturb and observe" (P&O) MPPT technique was utilized, enabling operation at the maximum power point (MPP) without the need for wind speed data or an aerodynamic model of the turbine. The speed and power data required for the P&O algorithm were derived from the three-phase generator variables using the double second-order generalized integrator frequency-locked loop (DSOGI-FLL) algorithm. The performance of a 1.5 kW WECS was analyzed through simulations conducted in Powersim (PSIM), and the results are presented. The analysis revealed that the designed system achieved an average MPPT efficiency of 97%. Furthermore, the efficiency of the resonant converter was measured to be 90% for the lowest wind speed and 93% for other wind speeds. These findings demonstrate that the proposed system offers a significant improvement in overall energy conversion efficiency, ensuring reliable and cost-effective operation of small-scale WECS, with an average system efficiency of approximately 90-93% across varying wind conditions.

New Properties of Phosphorus to Zinc Elements - Exploration of Energy Conversion Characteristics Based on Electromagnetic Signal Transmission in Semiconductor Devices

This study aims to explore novel properties of phosphorus (P) to zinc (Zn) elements. On the basis of previous work, we have explored the properties of elements ranging from H to Si. And the chemical elements belong layered, with P to Zn defined as the fourth layer to be researched using a contemporary industrial perspective. Since the late 19th century, there has been a progression in the application of electricity and magnetism to motor technology, leading to the evolution of computer systems capable of receiving, processing, and displaying external signals. These functionalities are recognized as attributes of the P element, serving as sensor modules for energy conversion. Subsequently, the establishment of a global production system through the utilization of the Internet and the Internet of Things has facilitated the growth of the biomedical industry within a vast industrial framework. This framework is characterized as the essence of the S element, functioning as an amplifier module for energy conversion. These 16 elements perform higher-level functions and can be seen as various processes for energy conversion in electromagnetic equipment, exemplified by biological signal transduction. They correspond to semiconductor chip fields such as from sensors and amplification circuits to displays and printing. This exploration is poised to enhance comprehension of the distinctive properties inherent in these elements.

Digitizing Low-Frequency Analog Control Circuit Using Bilinear Function Algorithm

In the past, low-frequency analog control circuits were largely used in analog control systems. With the rapid development of modern digital electronic technology, the digitization of traditional low-frequency analog control circuits while retaining the same functions as the original analog control systems has become an important trend in the field of electronic design. For this reason, this study aimed to develop an analog signal digitization model for control signals at a low frequency below 10 Hz. In terms of signal receiving and transmission requirements, the proposed model is configured with analog-to-digital converter (ADC), digital-to-analog converter (DAC), and pulse width modulation (PWM) functions. In the development environment, the input and output signals are first normalized and processed with PWM, enabling the digital signal processor to deal with analog signal receiving, processing, and external transmission. To replace the existing compensator in analog circuits, a digital compensator is used in the digital signal processor. Based on the bilinear function in MATLAB software, the parameter values demanded for the digital compensator can thus be obtained, achieving the automatic calculation of bilinear transformation in the system. Multisim simulation is then used to simulate analog circuit systems for comparison with the digitized outcomes. The experimental results reveal that the performance of the designed digital control circuit matches the simulation outcomes in both Bode gain (dB) and phase responses when the signal frequency is below 10 Hz. The effectiveness of the digitized analog control circuit for low-frequency control signals is therefore confirmed.

A high accuracy CMOS peak detection and holder ASIC for neutron detectors

With the completion and operation of a series of high-performance neutron sources, such as the China Spallation Neutron Source (CSNS), various neutron scattering spectrometers have continuously increased their performance requirements. One important aspect is to reduce collisions between scattered neutrons and air molecules during neutron scattering experiments, thereby reducing background noise and obtaining highly accurate experimental measurement results. This paper presents an application-specific integrated circuit (ASIC) dedicated to position-sensitive Helium-3 tubes neutron detector, which introduces peak detection and holder (PDH) circuits on the basis of traditional front-end electronics. Through a specific design, the switches and holding capacitor of the PDH module are isolated, ensuring that the holding voltage is not affected by switch noise, and maximizing the measurement accuracy of the PDH module. The 8 channel ASIC, realized in 0.18 μm CMOS technology, has a 10 fC to 1 pC input signal range with a linearity error within 0.22% to 1%. The PDH module is supplied with a single voltage of 1.8 V with a total power consumption of 350 μW with a layout area of 361 μm × 68 μm. The ASIC further enhances system integration, allowing the analog-to-digital conversion module to employ low-speed ADCs, thereby reducing the overall power consumption of the readout system. This enables the entire detector to operate in a vacuum environment, providing a new electronic readout solution for future neutron scattering and imaging experiments.

LDWLE: self-supervised driven low-light object detection framework

Low-light object detection involves identifying and locating objects in images captured under poor lighting conditions. It plays a significant role in surveillance and security, night pedestrian recognition, and autonomous driving, showcasing broad application prospects. Most existing object detection algorithms and datasets are designed for normal lighting conditions, leading to a significant drop in detection performance when applied to low-light environments. To address this issue, we propose a Low-Light Detection with Low-Light Enhancement (LDWLE) framework. LDWLE is an encoder-decoder architecture where the encoder transforms the raw input data into a compact, abstract representation (encoding), and the decoder gradually generates the target output format from the representation produced by the encoder. Specifically, during training, low-light images are input into the encoder, which produces feature representations that are decoded by two separate decoders: an object detection decoder and a low-light image enhancement decoder. Both decoders share the same encoder and are trained jointly. Throughout the training process, the two decoders optimize each other, guiding the low-light image enhancement towards improvements that benefit object detection. If the input image is normally lit, it first passes through a low-light image conversion module to be transformed into a low-light image before being fed into the encoder. If the input image is already a low-light image, it is directly input into the encoder. During the testing phase, the model can be evaluated in the same way as a standard object detection algorithm. Compared to existing object detection algorithms, LDWLE can train a low-light robust object detection model using standard, normally lit object detection datasets. Additionally, LDWLE is a versatile training framework that can be implemented on most one-stage object detection algorithms. These algorithms typically consist of three components: the backbone, neck, and head. In this framework, the backbone functions as the encoder, while the neck and head form the object detection decoder. Extensive experiments on the COCO, VOC, and ExDark datasets have demonstrated the effectiveness of LDWLE in low-light object detection. In quantitative measurements, it achieves an AP of 25.5 and 38.4 on the synthetic datasets COCO-d and VOC-d, respectively, and achieves the best AP of 30.5 on the real-world dataset ExDark. In qualitative measurements, LDWLE can accurately detect most objects on both public real-world low-light datasets and self-collected ones, demonstrating strong adaptability to varying lighting conditions and multi-scale objects.

Joint Fault Diagnosis of IGBT and Current Sensor in LLC Resonant Converter Module Based on Reduced Order Interval Sliding Mode Observer.

LLC resonant converters have emerged as essential components in DC charging station modules, thanks to their outstanding performance attributes such as high power density, efficiency, and compact size. The stability of these converters is crucial for vehicle endurance and passenger experience, making reliability a top priority. However, malfunctions in the switching transistor or current sensor can hinder the converter's ability to maintain a resonant state and stable output voltage, leading to a notable reduction in system efficiency and output capability. This article proposes a fault diagnosis strategy for LLC resonant converters utilizing a reduced-order interval sliding mode observer. Initially, an augmented generalized system for the LLC resonant converter is developed to convert current sensor faults into generalized state vectors. Next, the application of matrix transformations plays a critical role in decoupling open-circuit faults from the inverter system's state and current sensor faults. To achieve accurate estimation of phase currents and detection of current sensor faults, a reduced-order interval sliding mode observer has been designed. Building upon the estimation results generated by this observer, a diagnostic algorithm featuring adaptive thresholds has been introduced. This innovative algorithm effectively differentiates between current sensor faults and open switch faults, enhancing fault detection accuracy. Furthermore, it is capable of localizing faulty power switches and estimating various types of current sensor faults, thereby providing valuable insights for maintenance and repair. The robustness and effectiveness of the proposed fault diagnosis algorithm have been validated through experimental results and comparisons with existing methods, confirming its practical applicability in real-world inverter systems.

Energy Enhancement for Grid Connection by Boost Inverter in Tripolar Operation with Novelty Quadcoupling Control

In this paper a single-phase differential boost inverter is presented that has two functions, first is boost up and second is active power quadcoupling without adding active power electronics components for smart grid system. There are three operating principals: First is pulse energy modulation which operates converter in continuous conduction mode (CCM), Second is quadcoupler which is designed by adding four boost converters and third is Tripolar technique which used to add two inductors and one capacitor for each boost converter. The proposed model consist of four boost converters in parallel with interleaving switching technique to get lower duty cycle. The energy is delivered to the quadcoupler through tripolar technique. When two grids are connected through DC to AC conversion the boost inverter can increase voltages on required demand. A Simulink model is designed that shows and proves properties of proposed system with high energy, high efficiency and power control with lower voltage stress.

Structural Design and Kinematic Modeling of Highly Biomimetic Flapping-Wing Aircraft with Perching Functionality.

Birds use their claws to perch on branches, which helps them to recover energy and observe their surroundings; however, most biomimetic flapping-wing aircraft can only fly, not perch. This study was conducted on the basis of bionic principles to replicate birds' claw and wing movements in order to design a highly biomimetic flapping-wing aircraft capable of perching. First, a posture conversion module with a multi-motor hemispherical gear structure allows the aircraft to flap, twist, swing, and transition between its folded and unfolded states. The perching module, based on helical motion, converts the motor's rotational movement into axial movement to extend and retract the claws, enabling the aircraft to perch. The head and tail motion module has a dual motor that enables the aircraft's head and tail to move as flexibly as a bird's. Kinematic models of the main functional modules are established and verified for accuracy. Functional experiments on the prototype show that it can perform all perching actions, demonstrating multi-modal motion capabilities and providing a foundation upon which to develop dynamics models and control methods for highly biomimetic flapping-wing aircraft with perching functionality.

A bidirectional DC/DC converter for renewable energy source-fed EV charging stations with enhanced DC link voltage and ripple frequency management

The amount of electricity that the grid must supply has increased as the number of electric vehicles (EVs) has increased. The best way to minimize power pollution between the automobile and the grid is to use an EV charging station to establish a bidirectional connection with an energy storage unit (ESU). This paper proposes a bidirectional DC/DC converter for battery available at the renewable energy sources (RES) fed charging station. This bidirectional DC-DC converter has important advantages such as dc link voltage stress reduction and the ripple frequency of inductor current is two times of the converter's switching frequency. The proposed converter consists of two identical Zero Voltage Transition (ZVT) cells and each cell includes a capacitor, two resonant inductors and a supplementary switch which is combined with the traditional three level topology that enables both buck and boost operating modes. The simulation-based analysis has been done using MATLAB/Simulink. The simulation results have been verified with the help of experimental setup is presented for the converter module for validating the charging station.

A Self‐Powered and Self‐Absorbing Wireless Sensor Node for Smart Grid

The health monitoring of electricity transmission systems has been increasingly attracting the scientific community's attention, especially those power transmission towers built in remote and deserted areas. The smart grid provides a realistic solution to the health monitoring problem, but there is a problem that the energy supplies are still constrained by batteries. This article proposes a novel vibration energy harvester to address the power supply challenges of auxiliary equipment mounted on electricity towers or transmission lines. The proposed harvester not only harvests vibration energy when working but also attenuates the vibration amplitude of the transmission line. The structure of the device comprises three modules: a module for capturing vibration, a module for motion conversion, and a power management module. The analytical response under sinusoidal and random excitation is investigated, and the performance of energy harvesting and the effect on vibration is tested. The prototype achieves a maximum power of 183.96 mW when tested using the servo hydraulic mechanical testing and sensing system, and the wireless data transmission experiment proves the power generation ability of the prototype. The experimental results show that the acceleration of the transmission line decreases when the prototype is working.

Low capacitor stress reconfigurable quadratic boost converter with fault tolerant capability for rooftop solar PV application.

Recently, many high-gain topologies have been derived. However, there is a need for a high-gain converter with fault-tolerant features. In this paper, a fault-tolerant reconfigurable quadratic boost converter is proposed for DC microgrid application. In this novel topology, 2-level redundancy is achieved by addressing the fault in the switch and capacitors. The operation of the converter in normal operating conditions and reconfiguration mode is discussed. The derived topology can achieve the same voltage gain even in the reconfiguration mode. The proposed topology exhibits better performance in the reconfiguration state. The voltage stress across the input and output capacitor is reduced in that state. The reliability analysis of capacitors in both states is carried out and compared with the aid of the reliability handbook. Finally, the topology operation in a normal and reconfiguration state is validated by building a 1-kW hardware setup. The results show that the quadratic boost converter in a reconfiguration state operates without altering the voltage gain of the converter and with reduced voltage stress across the capacitors.

A Novel Mathematical Approach for Inductor-Current Expressions Definition in Multilevel Dual-Active-Bridge Converters

The study of multilevel dual-active-bridge (DAB) converters has garnered significant attention in recent years thanks to their advantages with respect to the conventional two-level (2L) DAB; namely, its greater performance and its capability to operate at higher voltage. The analysis of the converter high-frequency inductor current (iL) is crucial, for instance, to compute its root mean square (RMS) value, required to estimate the conduction losses in the converter. The mathematical expression of iL is piecewise and multiple variations, i.e., modes, exist depending on the modulation parameter values. This increases the complexity of converter performance analytical study. Thus, a more practical and generalizable expression of iL current is desirable. This paper proposes novel compact analytic expressions for the instantaneous and RMS inductor current in the 2L-NL DAB converter, leveraging binary functions to define the piecewise intervals and to identify the mode as a function of the modulation parameter values. The proposed method paves the way for more simple and computationally efficient DAB performance optimization software tools that allow exploring any given converter structures and modulation strategies.

Design of a Supercapacitor Module and Control Algorithm for Practical Verification of a Hybrid Energy Storage System

This paper presents an approach to designing a supercapacitor (SC) module according to defined power profiles and providing a control algorithm for sharing the energy from the SC module and accumulator in a hybrid energy storage system (HESS). This paper also presents a view of a printed circuit board (PCB) of the SC module and an interconnection board between the bidirectional converter, accumulator, and SC module. The practical part of the paper presents the measurement of the voltages and currents on the SC module, accumulator, and output of the DC/DC converter to visualize the energy flow between them.

Detecting Hidden Voice Recorders via ADC Electromagnetic Radiation

Unauthorized covert voice recording presents a significant threat to privacy-sensitive scenarios, such as confidential meetings and private conversations. Due to their miniaturization and disguise characteristics, hidden voice recorders are difficult to notice. In this paper, we present DeHiREC , the first proof-of-concept system capable of detecting offline hidden voice recorders from their electromagnetic radiations (EMR). We first characterize the unique patterns of the emanated EMR signals and then locate the EMR source, i.e., the analog-to-digital converter (ADC) module embedded in the mixed signal system-on-chips (MSoCs). Since these unintentional EMR signals can be extremely noisy and weak, accurately detecting them can be challenging. To address this challenge, we design an EMR Catalyzing method to actively stimulate the EMR signals and then employ an adaptive-folding algorithm to improve the signal-to-noise ratio (SNR) of the sensed EMRs. We evaluate the performance of DeHiREC on 18 commercial voice recorders under various impacts, including interference from other devices. Experimental results reveal that DeHiREC is effective in detecting all 18 voice recorders and achieves an overall success rate of 94.72% and a recall rate of 92.03% at a distance of 0.2 m.

A Wide Color Gamut and Noniridescent Zinc-Anode Asymmetric Electrochromic Device for Self-Sustaining Color-Adaptive Bio-Camouflage System.

Inspired by camouflage-colored organisms, the development of bio-camouflage systems using electrochromic (EC) technology has gained significant interest. However, existing EC systems struggle with achieving a wide color gamut, noniridescent colors, and self-sustainability. Herein, a self-sustainable color-adaptive bio-camouflage system integrating EC and nanogenerator (NG) technologies, enabling environmental color adaptation, and thermal regulation without an external power source is proposed. The system is based on a zinc-anode EC device (ZECD) with an asymmetric structure, incorporating flexible tungsten oxide and vanadium oxide electrodes. During the EC process, tungsten oxide shifts between blue and transparent, allowing near-infrared thermal modulation, while the vanadium oxide transitions from yellow to transparent. This design enables reversible near-infrared modulation and noniridescent color conversion among black, blue, green, yellow, and transparent. For the self-sustainability of the system, an electromagnetic and triboelectric hybrid NG that collects biomechanical energy is developed. In a typical driven cycle, the integrated system transitions colors and achieves significant near-infrared spectral modulation, demonstrating environmental adaptability and thermal regulation. Experiments on human skin and simulated chameleon color changes further confirm the system's effectiveness. This work highlights the potential of integrating EC and NG technologies to advance color-adaptive camouflage systems, opening new an avenue for bio-camouflage design.

Skin-core-fiber-based fabric integrated with pressure sensing and deep learning for posture recognition

The aggravation of subhealth caused by contemporary lifestyles boosts the innovation of sensing systems that can acquire and analyze physiological signals in a real-time, high-efficiency, and even smart way. However, reliable and universal fabrication for these smart sensing units in a bulk or film form remains challenging and thus restricts their widespread applications. Herein, we developed a smart fabric system for accurate real-time sitting posture recognition based on the combination of wet-spun skin-core aerogel fibers, a signal conversion module, and deep learning model. The sensing fibers show a high sensitivity of 23.59 kPa−1, fast response/recovery time of 45/40 ms, and excellent stability over 10,000 cycles, suggesting good pressure-sensing ability. After being assembled them with a signal conversion module, the resultant fabric sensing system could capture physiological signals from human motions and sitting posture in a precise and real-time fashion. Such systems function well even integrated into different parts of clothing and provide long-term wearing comfort. When introducing a deep learning model, 98 % sensing accuracy is demonstrated. This fabric sensing system not only provides reliable solutions to subhealth status monitoring and unhealthy lifestyle correction, but also inspires the mass production of next-generation smart textiles.

Multi-Terminal DC Transformer for Renewable Energy Cluster Grid Connection

An AC (alternative current) power integration of distributed energies faces multi-fold challenges such as synchronization and weak grid-induced instability. In this study, a multi-terminal DC transformer is proposed for renewable energy clusters grid connection. The DC transformer provides multiple DC input ports for renewable energy collection, while the load port is connected to the medium-voltage DC grid via a modular multilevel converter (MMC). The multi-port topology enables flexible power transfer between multiple input sources to the load without additional components. The carrier layer modulation strategy is implemented to balance the MMC module voltage; bidirectional power transmission between multiple input sources is achieved through the phase shift modulation (PSM) method. First, we provided a detailed introduction of the proposed topology and working principle. A simulation model was built using the SIMULINK, and the simulation results verified the effectiveness of the proposed converter modulation strategy and phase shift modulation method. A corresponding hardware experimental platform was designed and built, and the modulation and voltage equalization functions of modular multilevel rectifiers were presented as well as the measured results of power transmission modulation of the converter under single-input and multi-input conditions. The results indicate that the proposed transformer can achieve multiple DC inputs and has multi-channel power transmission capabilities, making it suitable for renewable energy clusters grid connection.

Indigenous Development of MIC-Based C-Band Dual Chain Down Converter Unit for GEOSAT- Spacecraft Checkout System

As part of miniaturization, the development work for the C-band dual-chain down converter, which is extensively used in TM (Telemetry) data acquisition system in GEOSAT spacecraft checkout system has been taken up in MIC (Microwave Integrated Circuit) approach using microstrip line structure. A prototype unit is realized using standard surface mount devices (SMD) and few indigenously developed MIC components namely, the directional couplers, the power dividers etc. The MIC-based down converter module, which forms the heart of the unit is housed in an Aluminium milled box having the dimension of 150 x 150 x 25 mm3. Except internal Local Oscillator (LO), RF Switches and Power supply, all other circuitry are mounted withinthis milled box which is housed in 1U chassis. It meets all the requirements of a conventional down converter. The paper describes the salient features of the unit, its detailed design approach and realization plan and finally the test and evaluation results of the prototype unit developed indigenously.