Guang-Zhong Cao

Bio: Guang-Zhong Cao is an academic researcher from Shenzhen University. The author has contributed to research in topics: Switched reluctance motor & Control system. The author has an hindex of 18, co-authored 109 publications receiving 1137 citations. Previous affiliations of Guang-Zhong Cao include Southwest Jiaotong University.

An Active-Rectifier-Based Maximum Efficiency Tracking Method Using an Additional Measurement Coil for Wireless Power Transfer

Abstract: The efficiency of wireless power transfer (WPT) systems is highly dependent on the load, which may change in a wide range in field applications. Besides, the detuning of WPT systems caused by the component tolerance and aging of inductors and capacitors can also decrease the system efficiency. In order to track the maximum system efficiency under varied loads and detuning conditions in real time, an active single-phase rectifier (ASPR) with an auxiliary measurement coil (AMC) and its corresponding control method are proposed in this paper. Both the equivalent load impedance and the output voltage can be regulated by the ASPR and the inverter, separately. First, the fundamental harmonic analysis model is established to analyze the influence of the load and the detuning on the system efficiency. Second, the soft-switching conditions and the equivalent input impedance of ASPR with different phase shifts and pulse widths are investigated in detail. Then, the analysis of the AMC and the maximum efficiency control strategy are provided in detail. Finally, an 800-W prototype is set up to validate the performance of the proposed method. The experimental results show that with 10% tolerance of the resonant capacitor in the receiver side, the system efficiency with the proposed approach reaches 91.7% at rated 800-W load and 91.1% at 300-W light load, which has an improvement by 2% and 10% separately compared with the traditional diode rectifier.

Inductive Power Transfer for Massive Electric Bicycles Charging Based on Hybrid Topology Switching With a Single Inverter

Abstract: It is more convenient and safer to employ inductive power transfer (IPT) systems to charge the battery pack of electric bicycles (EBs) than conventional plug-in systems. An IPT charging method suitable for charging massive EBs is proposed to achieve constant current (CC) and constant voltage (CV) output without feedback control strategies or communication link between transmitter side and receiver side. Two ac switches (ACSs) and an auxiliary capacitor utilized at receiver side are employed to be operated once to change the charging modes from CC mode to CV mode. The characteristics of the load-independent current output in the CC mode and load-independent voltage output in the CV mode are achieved by properly selecting the passive parameters of inductances and capacitors, so that no sophisticated control strategies are required to regulate the output as per the charging profile. The feasibility of proposed method has been verified with an experimental prototype in form of efficiency, stability of output current and voltage in CC/CV mode. The simple and economical approach is suitable for the massive EBs charging system with only one inverter, especially in China.

Hybrid and Reconfigurable IPT Systems With High-Misalignment Tolerance for Constant-Current and Constant-Voltage Battery Charging

Abstract: Inductive power transfer (IPT) for battery charging applications has significant advantages over the traditional plug-in system. Since misalignment between the primary and secondary windings is inevitable, it is of significance to improve the misalignment tolerance of IPT systems with constant-current (CC) and constant-voltage (CV) outputs for battery charging. In this paper, the load-independent output characteristic of the hybrid topology and the function switching between CC and CV of the reconfigurable topology are analyzed. Besides, a hybrid and reconfigurable IPT system with 3-D misalignment tolerance for CC and CV outputs is proposed, simplifying or even canceling control schemes. Moreover, a novel parametric design method is given for the IPT system, which can suppress the fluctuation of the output voltage/current within a certain range of misalignment. In order to validate the performance of the proposed topology, a 1-kW prototype is built, and the corresponding experiments are carried out. In the CC/CV mode, the system can operate with the longitudinal misalignment to 50% when the load varies from 36 to 480 Ω, and the fluctuation of the output current/voltage is within 5%. Similarly, the misalignment in Y - and Z -axis is 12.5% and 33.3%, respectively.

Hybrid Topology With Configurable Charge Current and Charge Voltage Output-Based WPT Charger for Massive Electric Bicycles

Abstract: Wireless power transfer chargers for electric bicycles (EBs) have many advantages over transitional plug-in systems. However, to meet the charge requirements, the traditional charger needs a dedicated inverter to achieve constant current (CC) output or constant voltage (CV) output. A hybrid topology-based EB charging strategy is proposed using a single high-frequency inverter (HFI) to charge massive EBs, and one charging stand can be shared to charge EBs with various specifications of batteries. Configurable CC and CV outputs can be realized by turning on/off two ac switches without adopting sophisticated control schemes or wireless communication links. Besides, zero phase angle switching of HFI can be realized, and then the system efficiency is increased. Finally, the proposed method is verified by experiments with various charging conditions. The results show that the fluctuation margins of charging currents and charging voltages in the whole charging process are both less than 2.5% and the maximum efficiency reaches 91.90%. With the merit of the proposed approach, the reduction of construction cost and the control complexity is achieved. Thus, it might be one of the most promising solutions for charging massive EBs in some regions like China.

Wireless Power Transfer—An Overview

Abstract: Due to limitations of low power density, high cost, heavy weight, etc., the development and application of battery-powered devices are facing with unprecedented technical challenges. As a novel pattern of energization, the wireless power transfer (WPT) offers a band new way to the energy acquisition for electric-driven devices, thus alleviating the over-dependence on the battery. This paper presents an overview of WPT techniques with emphasis on working mechanisms, technical challenges, metamaterials, and classical applications. Focusing on WPT systems, this paper elaborates on current major research topics and discusses about future development trends. This novel energy transmission mechanism shows significant meanings on the pervasive application of renewable energies in our daily life.

Classification of Skin Disease Using Deep Learning Neural Networks with MobileNet V2 and LSTM

Abstract: Deep learning models are efficient in learning the features that assist in understanding complex patterns precisely. This study proposed a computerized process of classifying skin disease through deep learning based MobileNet V2 and Long Short Term Memory (LSTM). The MobileNet V2 model proved to be efficient with a better accuracy that can work on lightweight computational devices. The proposed model is efficient in maintaining stateful information for precise predictions. A grey-level co-occurrence matrix is used for assessing the progress of diseased growth. The performance has been compared against other state-of-the-art models such as Fine-Tuned Neural Networks (FTNN), Convolutional Neural Network (CNN), Very Deep Convolutional Networks for Large-Scale Image Recognition developed by Visual Geometry Group (VGG), and convolutional neural network architecture that expanded with few changes. The HAM10000 dataset is used and the proposed method has outperformed other methods with more than 85% accuracy. Its robustness in recognizing the affected region much faster with almost 2× lesser computations than the conventional MobileNet model results in minimal computational efforts. Furthermore, a mobile application is designed for instant and proper action. It helps the patient and dermatologists identify the type of disease from the affected region's image at the initial stage of the skin disease. These findings suggest that the proposed system can help general practitioners efficiently and effectively diagnose skin conditions, thereby reducing further complications and morbidity.

Constant Current/Voltage Charging Operation for Series–Series and Series–Parallel Compensated Wireless Power Transfer Systems Employing Primary-Side Controller

Abstract: This paper proposes a new control technique, which only employs the primary-side controller and load identification approach to adjust charging voltage/current for series–series (SS) and series–parallel (SP) compensated wireless power transfer (WPT) systems. The advantages are that dual-side wireless communication for real-time charging current/voltage adjustment is avoided as well as it is suitable for different charging modes, e.g., constant voltage (CV) and constant current (CC) charging defined by the battery charging profile. The load identification approach, which utilizes reflected impedance theory and quadrature transformation algorithm for calculating the active power, is proposed to estimate the equivalent load resistance of battery. Then, the CV/CC charging for both SS and SP compensation are achieved by the PI-controlled phase-shift H-bridge inverter. The simulation and experimental results validate the feasibility of proposed control method. During the CC charging, 3.01 and 3.03 A for SS and SP compensation with the error of 1.2% and 1.4% are achieved. During the CV charging, 25.8 and 25.7 V for SS and SP compensation with the error of 1.1% and 1.3% are realized. The proposed method improves the performance of both SS- and SP-compensated WPT systems to be more suitable for the applications that require compact and lightweight receiver.

Opportunities and challenges for near-field wireless power transfer: A review

Abstract: Traditional power supply cords have become less important because they prevent large-scale utilization and mobility. In addition, the use of batteries as a substitute for power cords is not an optimal solution because batteries have a short lifetime, thereby increasing the cost, weight, and ecological footprint of the hardware implementation. Their recharging or replacement is impractical and incurs operational costs. Recent progress has allowed electromagnetic wave energy to be transferred from power sources (i.e., transmitters) to destinations (i.e., receivers) wirelessly, the so-called wireless power transfer (WPT) technique. New developments in WPT technique motivate new avenues of research in different applications. Recently, WPT has been used in mobile phones, electric vehicles, medical implants, wireless sensor network, unmanned aerial vehicles, and so on. This review highlights up-to-date studies that are specific to near-field WPT, which include the classification, comparison, and potential applications of these techniques in the real world. In addition, limitations and challenges of these techniques are highlighted at the end of the article.

Getting to Know Low-light Images with The Exclusively Dark Dataset

Abstract: Low-light is an inescapable element of our daily surroundings that greatly affects the efficiency of our vision. Research works on low-light has seen a steady growth, particularly in the field of image enhancement, but there is still a lack of a go-to database as benchmark. Besides, research fields that may assist us in low-light environments, such as object detection, has glossed over this aspect even though breakthroughs-after-breakthroughs had been achieved in recent years, most noticeably from the lack of low-light data (less than 2% of the total images) in successful public benchmark dataset such as PASCAL VOC, ImageNet, and Microsoft COCO. Thus, we propose the Exclusively Dark dataset to elevate this data drought, consisting exclusively of ten different types of low-light images (i.e. low, ambient, object, single, weak, strong, screen, window, shadow and twilight) captured in visible light only with image and object level annotations. Moreover, we share insightful findings in regards to the effects of low-light on the object detection task by analyzing visualizations of both hand-crafted and learned features. Most importantly, we found that the effects of low-light reaches far deeper into the features than can be solved by simple "illumination invariance'". It is our hope that this analysis and the Exclusively Dark dataset can encourage the growth in low-light domain researches on different fields. The Exclusively Dark dataset with its annotation is available at this https URL