EMI challenges in modern power electronic-based converters: recent advances and mitigation techniques
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The utilization of power electronic-based converters is gaining momentum across a wide spectrum of industries. However, modern power electronic converters operate at higher frequencies compared to conventional power electronic converters, which can lead to higher rates of change in voltage and current during phase switching, and thus potentially produce more severe conducted and radiated electromagnetic interference (EMI). Their electromagnetic compatibility (EMC) has become a critical research topic, and EMI in high-frequency power electronic-based converters is more complex than that in conventional converters. This review presents a comprehensive survey of recent advancements, EMI design, and analysis of modern power electronic-based converters, focusing on the sources and mechanisms of both conducted and radiated EMI, and mitigating techniques. This review also covers the impact of topology optimization, control strategy design, and packaging design on EMC performance. Addressing emerging EMI issues in modern power electronic device-based converters is essential for ensuring safe and reliable operations. Through strategic design optimization and the implementation of EMI mitigation strategies, modern converters can seamlessly be integrated into diverse applications, offering improved EMI performance as a hallmark of their versatility.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2023.1274258

Two-dimensional semiconductors based field-effect transistors: review of major milestones and challenges
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Two-dimensional (2-D) semiconductors are emerging as strong contenders for the future of Angstrom technology nodes. Their potential lies in enhanced device scaling and energy-efficient switching compared to traditional bulk semiconductors like Si, Ge, and III-V compounds. These materials offer significant advantages, particularly in ultra-thin devices with atomic scale thicknesses. Their unique structures enable the creation of one-dimensional nanoribbons and vertical and lateral heterostructures. This versatility in design, coupled with their distinctive properties, paves the way for efficient energy switching in electronic devices. Moreover, 2-D semiconductors offer opportunities for integrating metallic nanoribbons, carbon nanotubes (CNT), and graphene with their 2-D channel materials. This integration helps overcome lithography limitations for gate patterning, allowing the realization of ultra-short gate dimensions. Considering these factors, the potential of 2-D semiconductors in electronics is vast. This concise review focuses on the latest advancements and engineering strategies in 2-D logic devices.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2023.1277927

Measurement and analysis of the electromagnetic environment in 500 kV back-to-back converter stations
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Guid: https://www.frontiersin.org/articles/10.3389/felec.2023.1249007

Editorial: Re-electrification technology and application of the energy consumption terminal
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Guid: https://www.frontiersin.org/articles/10.3389/felec.2023.1178703

Hybrid neuroelectronics: towards a solution-centric way of thinking about complex problems in neurostimulation tools
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Responsive neuromodulation is increasingly being used to treat patients with neuropsychiatric diseases. Yet, inefficient bridges between traditional and new materials and technological innovations impede advancements in neurostimulation tools. Signaling in the brain is accomplished predominantly by ion flux rather than the movement of electrons. However, the status quo for the acquisition of neural signals is using materials, such as noble metals, that can only interact with electrons. As a result, ions accumulate at the biotic/abiotic interface, creating a double-layer capacitance that increases impedance and negatively impacts the efficiency of neural interrogation. Alternative materials, such as conducting polymers, allow ion penetration in the matrix, creating a volumetric capacitor (two orders of magnitude larger than an area-dependent capacitor) that lowers the impedance and increases the spatiotemporal resolution of the recording/stimulation. On the other hand, the increased development and integration capabilities of CMOS-based back-end electronics have enabled the creation of increasingly powerful and energy-efficient microchips. These include stimulation and recording systems-on-a-chip (SoCs) with up to tens of thousands of channels, fully integrated circuitry for stimulation, signal conditioning, digitation, wireless power and data telemetry, and on-chip signal processing. Here, we aim to compile information on the best component for each building block and try to strengthen the vision that bridges the gap among various materials and technologies in an effort to advance neurostimulation tools and promote a solution-centric way of considering their complex problems.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2023.1250655

Topology synthesis of integrated active power decoupling converters using asymmetrical H-bridge circuits
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Aiming to handle the inherent double-line frequency ripple power in single-phase power systems, a lot of active power decoupling (APD) topologies have been developed. In this paper, a general method is introduced to synthesize APD topologies. The main construction idea is to insert a rectifier/inverter into asymmetrical H-bridge circuits (AHCs) or replace the switch/diode in the AHCs with a rectifier/inverter. This approach not only reveals the formation process of existing APD topologies but also deduces new APD topologies. Finally, an experimental case study has been carried out to illustrate the feasibility and effectiveness of the proposed topology synthesis method.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2023.1250099

Lifetime prediction and reliability analysis for aluminum electrolytic capacitors in EV charging module based on mission profiles
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The charging modules of Electric vehicles (EVs) always run in a complex and variable state. As the weakness in the reliable operation of charging modules, the accurate lifetime prediction of aluminum electrolytic capacitors (Al-caps) is important for the later maintenance and reliability design. The hotspot temperature calculation method and lifetime model limit the accuracy of aluminum electrolytic capacitors lifetime prediction methods, which cannot meet the increasing requirements for reliability. In order to solve the problems above, this paper has proposed a hotspot temperature calculation method based on the ripple current with frequency characteristics and the cooling conditions on the heat generation and thermal conductivity of the capacitors. Furthermore, the lifetime model under reference voltage has been constructed with 3D surface fitting toolbox, which describes the trends of capacitor lifetime with ambient temperature and hotspot temperature under the constant voltage condition. Considering the variation of voltage, the multiple lifetime model of capacitor is established with a voltage correction coefficient. With the proposed method, it can be realized about the real-time lifetime prediction of capacitors under multiple operating profiles such as ripple current, thermal dissipation conditions, ambient temperature and operating voltage. Finally, the effectiveness of the proposed method is verified with the annual profiles of a 30 kW EV charging module.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2023.1226006

Impact of inverter-based resources on transmission line relaying -part II: power swing protection
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The power swing characteristic of transmission lines (TLs) can be affected by the large-scale integration of inverter-based resources (IBRs), resulting in the maloperation of the legacy power swing blocking (PSB) and out-of-step tripping (OST) functions. This paper presents a brief review of power swing phenomena and the impact on power swing protection functions. In this regard, the impact of IBR integration of type-III, and type-IV wind turbine generation (WTG) on legacy power swing protection functions has been scrutinized. To do so, the performance of impedance-based PSB and OST functions during the IBR integration has been investigated via comprehensive simulation studies. The results show that under a system contingency and high IBR penetration, depending on the IBR technology, the system experiences frequency oscillations and swinging impedance trajectories which are different from those from synchronous generators, such that the reliable operation of the legacy PSB and OST functions can be jeopardized. Moreover, during power swing phenomena, the simulation results have found that the security of distance protection cannot be guaranteed and the fault ride-through requirements cannot be maintained when a high share of IBRs have been integrated.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2023.1144383

Ear canal pressure sensor for food intake detection
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Introduction: This paper presents a novel Ear Canal Pressure Sensor (ECPS) for objective detection of food intake, chew counting, and food image capture in both controlled and free-living conditions. The contribution of this study is threefold: 1) Development and validation of a novel wearable sensor that uses changes in ear canal pressure and the device’s acceleration as an indicator of food intake, 2) A method to identify chewing segments and count the number of chews in each eating episode, and 3) Facilitation of egocentric image capture only during eating by triggering camera from sensor detection thus reducing power consumption, privacy concerns, as well as storage and computational cost.

Methods: To validate the device, data were collected from 10 volunteers in a controlled environment and three volunteers in a free-living environment. During the controlled activities, each participant wore the device for approximately 1 h, and during the free living for approximately 12 h. The food intake of the participants was not restricted in any way in both part of the experiment. Subject-independent Support Vector Machine classifiers were trained to identify periods of food intake from the features of both the pressure sensor and accelerometer, and features only from the pressure sensor.

Results: Results from leave-one-out cross-validation showed an average 5 sec-epoch classification F-score of 87.6% using only pressure sensor features and 88.6% using features from both pressure sensor and accelerometer in the controlled environment. For the free-living environment, both classifiers accurately detected all eating episodes. The wearable sensor achieves 95.5% accuracy in counting the number of chews with respect to manual annotation from the videos of the eating episodes using a pressure sensor classifier in the controlled environment.

Discussion: The manual review of the images found that only 3.7% of captured images belonged to the detected eating episodes, suggesting that sensor-triggered camera capture may facilitate reducing the number of captured images and power consumption of the sensor.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2023.1173607

Straightforward data transfer in a blockwise dataflow for an analog RRAM-based CIM system
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Analog resistive random-access memory (RRAM)-based computation-in-memory (CIM) technology is promising for constructing artificial intelligence (AI) with high energy efficiency and excellent scalability. However, the large overhead of analog-to-digital converters (ADCs) is a key limitation. In this work, we propose a novel LINKAGE architecture that eliminates PE-level ADCs and leverages an analog data transfer module to implement inter-array data processing. A blockwise dataflow is further proposed to accelerate convolutional neural networks (CNNs) to speed up compute-intensive layers and solve the unbalanced pipeline problem. To obtain accurate and reliable benchmark results, key component modules, such as straightforward link (SFL) modules and Tile-level ADCs, are designed in standard 28 nm CMOS technology. The evaluation shows that LINKAGE outperforms the conventional ADC/DAC-based architecture with a 2.07×∼11.22× improvement in throughput, 2.45×∼7.00× in energy efficiency, and 22%–51% reduction in the area overhead while maintaining accuracy. Our LINKAGE architecture can achieve 22.9∼24.4 TOPS/W energy efficiency (4b-IN/4b-W) and 1.82 ∼4.53 TOPS throughput with the blockwise method. This work demonstrates a new method for significantly improving the energy efficiency of CIM chips, which can be applied to general CNNs/FCNNs.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2023.1129675

Design of a wireless charging system in DC microgrids with accurate output regulation and optimal efficiency
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This paper presents a general circuit and control design method for wireless power transfer (WPT) systems in DC microgrids to achieve optimal power transfer efficiency, while maintain accurate output voltage regulation. An auxiliary inductor is added at the transmitter resonator to form a current sink to ensure zero voltage switching (ZVS) of the primary-side full-bridge inverter with even extreme-light load conditions. Besides, an adaptive proportional-integral (PI) controller is adopted to track the output voltage references by regulating the phase shift angle of the phase shift control for the full-bridge inverter. The coefficients of the adaptive proportional-integral controller are determined by the inductor of the auxiliary inductor. Both simulation and experimental results have validated the effectiveness of the proposed circuit and control design in achieving optimal efficiency and output voltage regulation for wireless power transfer systems in DC microgrids with source and load variations.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2023.968549

Optimal dispatch of integrated energy systems considering integrated demand response and stepped carbon trading
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The integrated energy system is an effective way to achieve carbon neutrality. To further exploit the carbon reduction potentials of IESs, an optimal dispatch strategy that considers integrated demand response and stepped carbon trading is proposed. First, an integrated demand response (IDR) pricing approach is proposed based on the characteristics of different load types. Classify multi-energy loads into curtailable and substitutable loads, and incentivize both loads through a price elasticity matrix and low-price energy in the same period. Then, to better incentivize IESs to reduce carbon emissions, a stepped pricing mechanism was introduced in the carbon price. Finally, an optimal dispatch model is developed with an objective function that minimizes the sum of energy purchase cost, carbon trading cost, and operation and maintenance (O&M) cost. Considering the high-dimensional and non-linear characteristics of the model, an improved differential evolution (DE) algorithm is introduced in this paper. In addition, this paper also analyzes the effects of the stepped carbon trading parameters on the optimal dispatching results of the system in terms of carbon trading base price, carbon emission interval length, and carbon price growth rate. Compared to the case of adopting a single IDR model or a single stepped carbon trading, carbon emissions from the IESs decreased by 6.28% and 3.24%, respectively, while total operating costs decreased by 1.24% and 0.92%, The results show that the model proposed in this paper has good environmental and economic benefits, and the reasonable setting of stepped carbon trading parameters can effectively promote the low-carbon development of IESs.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2023.1110039

Research on optimal coil configuration scheme of insulator relay WPT system
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This paper presents the optimized structure of the multi-relay coils insulator of WPT system. With the rapid development of the smart grid, on-line monitoring devices in the transmission tower have been widely used. However, the power supply problem has become an important bottleneck in the development of transmission tower intelligent sensing technology. Hence, the multi-relay coils wireless power transfer technology has been proposed to supply for the tower monitoring equipment in this paper. Compared with traditional multi-relay coils, the effects of the number, arrangement position and turns of relay coils on the performance of WPT system are further explored. The simulation results show that the operation performance of WPT can be significantly improved by optimizing the coil arrangement position and turns. Moreover, there are multiple configuration schemes that the design indexes of the system could be achieved. The experiment results show that in the 110 kV high-voltage transmission with the insulator length of 1.015 m, the transmitting power and efficiency of the WPT system could be increased to 1.81 W and 60.11% respectively by parameters optimization, which ensures the continuous and stable work of the monitoring equipment.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2023.1034082

CoFHE: Software and hardware Co-design for FHE-based machine learning as a service
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Introduction: Privacy concerns arise whenever sensitive data is outsourced to untrusted Machine Learning as a Service (MLaaS) platforms. Fully Homomorphic Encryption (FHE) emerges one of the most promising solutions to implementing privacy-preserving MLaaS. But prior FHE-based MLaaS faces challenges from both software and hardware perspectives. First, FHE can be implemented by various schemes including BGV, BFV, and CKKS, which are good at different FHE operations, e.g., additions, multiplications, and rotations. Different neural network architectures require different numbers of FHE operations, thereby preferring different FHE schemes. However, state-of-the-art MLaaS just naïvely chooses one FHE scheme to build FHE-based neural networks without considering other FHE schemes. Second, state-of-the-art MLaaS uses power-hungry hardware accelerators to process FHE-based inferences. Typically, prior high-performance FHE accelerators consume >160 Watt, due to their huge capacity (e.g., 512 MB) on-chip SRAM scratchpad memories.

Methods: In this paper, we propose a software and hardware co-designed FHE-based MLaaS framework, CoFHE. From the software perspective, we propose an FHE compiler to select the best FHE scheme for a network architecture. We also build a low-power and high-density NAND-SPIN and SRAM hybrid scratchpad memory system for FHE hardware accelerators.

Results: On average, under the same security and accuracy constraints, on average, CoFHE accelerates various FHE-based inferences by 18%, and reduces the energy consumption of various FHE-based inferences by 26%.

Discussion: CoFHE greatly improves the latency and energy efficiency of FHE-based MLaaS.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2022.1091369

Analytic circuit model for thermal drying behavior of electronic inks
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Understanding the sintering process of conductive inks is a fundamental step in the development of sensors. The intrinsic properties (such as thermal conductivity, resistivity, thermal coefficient, among others) of the printed devices do not correspond to those of the bulk materials. In the field of biosensors porosity plays a predominant role, since it defines the difference between the geometric area of the working electrode and its electrochemical surface area. The analysis reported so far in the literature on the sintering of inks are based on their DC characterization. In this work, the shape and distribution of the nanoparticles that make up the silver ink have been studied employing a transmission electron microscopy. Images of the printed traces have been obtained through a scanning electron microscope at different sintering times, allowing to observe how the material decreases its porosity over time. These structural changes were supported through electrical measurements of the change in the trace impedance as a function of drying time. The resistivity and thermal coefficient of the printed tracks were analyzed and compared with the values of bulk silver. Finally, this work proposes an analytical circuit model of the drying behavior of the ink based on AC characterization at different frequencies. The characterization considers an initial time when the spheric nanoparticles are still surrounded by the capping agent until the conductive trace is obtained. This model can estimate the characteristics that the printed devices would have, whether they are used as biosensors (porous material) or as interconnections (compact material) in printed electronics.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2022.1060197

Breakdown-limited endurance in HZO FeFETs: Mechanism and improvement under bipolar stress
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Breakdown is one of main failure mechanisms that limit write endurance of ferroelectric devices using hafnium oxide-based ferroelectric materials. In this study, we investigate the gate current and breakdown characteristics of Hf_0.5Zr_0.5O₂/Si ferroelectric field-effect transistors (FeFETs) by using carrier separation measurements to analyze electron and hole leakage currents during time-dependent dielectric breakdown (TDDB) tests. Rapidly increasing substrate hole currents and stress-induced leakage current (SILC)-like electron currents can be observed before the breakdown of the ferroelectric gate insulator of FeFETs. This apparent degradation under voltage stress is recovered and the time-to-breakdown is significantly improved by interrupting the TDDB test with gate voltage pulses with the opposite polarity, suggesting that defect redistribution, rather than defect generation, is responsible for the trigger of hard breakdown.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2022.1091343

XMA2: A crossbar-aware multi-task adaption framework via 2-tier masks
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Recently, ReRAM crossbar-based deep neural network (DNN) accelerator has been widely investigated. However, most prior works focus on single-task inference due to the high energy consumption of weight reprogramming and ReRAM cells’ low endurance issue. Adapting the ReRAM crossbar-based DNN accelerator for multiple tasks has not been fully explored. In this study, we propose XMA², a novel crossbar-aware learning method with a 2-tier masking technique to efficiently adapt a DNN backbone model deployed in the ReRAM crossbar for new task learning. During the XMA²-based multi-task adaption (MTA), the tier-1 ReRAM crossbar-based processing-element- (PE-) wise mask is first learned to identify the most critical PEs to be reprogrammed for essential new features of the new task. Subsequently, the tier-2 crossbar column-wise mask is applied within the rest of the weight-frozen PEs to learn a hardware-friendly and column-wise scaling factor for new task learning without modifying the weight values. With such crossbar-aware design innovations, we could implement the required masking operation in an existing crossbar-based convolution engine with minimal hardware/memory overhead to adapt to a new task. The extensive experimental results show that compared with other state-of-the-art multiple-task adaption methods, XMA² achieves the highest accuracy on all popular multi-task learning datasets.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2022.1032485

A review and analysis of current-mode biosensing front-end ICs for nanopore-based DNA sequencing
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Bio-sensors connect the biological world with electronic devices, widely used in biomedical applications. The combination of microelectronic and medical technologies makes biomedical diagnosis more rapid, accurate, and efficient. In this article, the current-mode biosensing front-end integrated circuits (ICs) for nanopore-based DNA sequencing are reviewed and analyzed, aiming to present their operation theories, advantages, limitations, and performances including gain, bandwidth, noise, and power consumption. Because biological information and external interference are contained in extremely weak sensing current, usually at the pA or nA level, it is challenging to accurately detect and restore the desired signals. Based on the requirements of DNA sequencing, this paper shows three circuit topologies of biosensing front-end, namely, discrete-time, continuous-time, and current-to-frequency conversion types. This paper also makes an introduction to the current-mode sensor array for DNA sequencing. To better review and evaluate the research of the state-of-the-art, the most relevant published works are summarized and compared. The review and analysis would help the researchers be familiar with the requirements, constraints, and methods for current-mode biosensing front-end IC designs for nanopore-based DNA sequencing.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2022.1071132

Kinetic energy harvesting based sensing and IoT systems: A review
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The rapid advance of the Internet of Things (IoT) has attracted growing interest in academia and industry toward pervasive sensing and everlasting IoT. As the IoT nodes exponentially increase, replacing and recharging their batteries proves an incredible waste of labor and resources. Kinetic energy harvesting (KEH), converting the wasted ambient kinetic energy into usable electrical energy, is an emerging research field where various working mechanisms and designs have been developed for improved performance. Leveraging the KEH technologies, many motion-powered sensors, where changes in the external environment are directly converted into corresponding self-generated electrical signals, are developed and prove promising for multiple self-sensing applications. Furthermore, some recent studies focus on utilizing the generated energy to power a whole IoT sensing system. These systems comprehensively consider the mechanical, electrical, and cyber parts, which lead a further step to truly self-sustaining and maintenance-free IoT systems. Here, this review starts with a brief introduction of KEH from the ambient environment and human motion. Furthermore, the cutting-edge KEH-based sensors are reviewed in detail. Subsequently, divided into two aspects, KEH-based battery-free sensing systems toward IoT are highlighted. Moreover, there are remarks in every chapter for summarizing. The concept of self-powered sensing is clarified, and advanced studies of KEH-based sensing in different fields are introduced. It is expected that this review can provide valuable references for future pervasive sensing and ubiquitous IoT.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2022.1017511

Influence analysis of metal foreign objects on the wireless power transmission system
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The wireless power transmission (WPT) system through magnetic field coupling for energy transmission may have foreign objects in the transmission channel in the practical application process, which brings hidden dangers to the WPT system. In this article, a WPT system without and with foreign objects is constructed. The influence of foreign objects on self-inductance and mutual-inductance of coupling coils is studied from the aspects of foreign object height, radius, transmission distance, and coil turns. Then, by constructing the circuit topology of the series structure, the influence of foreign objects on the transmission efficiency and the phase difference between voltage and current of the system is studied, and finally the influence law of metal foreign objects on the performance of the WPT system is summarized.

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Guid: https://www.frontiersin.org/articles/10.3389/felec.2022.1033016