Vol. 174
Latest Volume
All Volumes
PIERC 174 [2026] PIERC 173 [2026] PIERC 172 [2026] PIERC 171 [2026] PIERC 170 [2026] PIERC 169 [2026] PIERC 168 [2026] PIERC 167 [2026] PIERC 166 [2026] PIERC 165 [2026] PIERC 164 [2026] PIERC 163 [2026] PIERC 162 [2025] PIERC 161 [2025] PIERC 160 [2025] PIERC 159 [2025] PIERC 158 [2025] PIERC 157 [2025] PIERC 156 [2025] PIERC 155 [2025] PIERC 154 [2025] PIERC 153 [2025] PIERC 152 [2025] PIERC 151 [2025] PIERC 150 [2024] PIERC 149 [2024] PIERC 148 [2024] PIERC 147 [2024] PIERC 146 [2024] PIERC 145 [2024] PIERC 144 [2024] PIERC 143 [2024] PIERC 142 [2024] PIERC 141 [2024] PIERC 140 [2024] PIERC 139 [2024] PIERC 138 [2023] PIERC 137 [2023] PIERC 136 [2023] PIERC 135 [2023] PIERC 134 [2023] PIERC 133 [2023] PIERC 132 [2023] PIERC 131 [2023] PIERC 130 [2023] PIERC 129 [2023] PIERC 128 [2023] PIERC 127 [2022] PIERC 126 [2022] PIERC 125 [2022] PIERC 124 [2022] PIERC 123 [2022] PIERC 122 [2022] PIERC 121 [2022] PIERC 120 [2022] PIERC 119 [2022] PIERC 118 [2022] PIERC 117 [2021] PIERC 116 [2021] PIERC 115 [2021] PIERC 114 [2021] PIERC 113 [2021] PIERC 112 [2021] PIERC 111 [2021] PIERC 110 [2021] PIERC 109 [2021] PIERC 108 [2021] PIERC 107 [2021] PIERC 106 [2020] PIERC 105 [2020] PIERC 104 [2020] PIERC 103 [2020] PIERC 102 [2020] PIERC 101 [2020] PIERC 100 [2020] PIERC 99 [2020] PIERC 98 [2020] PIERC 97 [2019] PIERC 96 [2019] PIERC 95 [2019] PIERC 94 [2019] PIERC 93 [2019] PIERC 92 [2019] PIERC 91 [2019] PIERC 90 [2019] PIERC 89 [2019] PIERC 88 [2018] PIERC 87 [2018] PIERC 86 [2018] PIERC 85 [2018] PIERC 84 [2018] PIERC 83 [2018] PIERC 82 [2018] PIERC 81 [2018] PIERC 80 [2018] PIERC 79 [2017] PIERC 78 [2017] PIERC 77 [2017] PIERC 76 [2017] PIERC 75 [2017] PIERC 74 [2017] PIERC 73 [2017] PIERC 72 [2017] PIERC 71 [2017] PIERC 70 [2016] PIERC 69 [2016] PIERC 68 [2016] PIERC 67 [2016] PIERC 66 [2016] PIERC 65 [2016] PIERC 64 [2016] PIERC 63 [2016] PIERC 62 [2016] PIERC 61 [2016] PIERC 60 [2015] PIERC 59 [2015] PIERC 58 [2015] PIERC 57 [2015] PIERC 56 [2015] PIERC 55 [2014] PIERC 54 [2014] PIERC 53 [2014] PIERC 52 [2014] PIERC 51 [2014] PIERC 50 [2014] PIERC 49 [2014] PIERC 48 [2014] PIERC 47 [2014] PIERC 46 [2014] PIERC 45 [2013] PIERC 44 [2013] PIERC 43 [2013] PIERC 42 [2013] PIERC 41 [2013] PIERC 40 [2013] PIERC 39 [2013] PIERC 38 [2013] PIERC 37 [2013] PIERC 36 [2013] PIERC 35 [2013] PIERC 34 [2013] PIERC 33 [2012] PIERC 32 [2012] PIERC 31 [2012] PIERC 30 [2012] PIERC 29 [2012] PIERC 28 [2012] PIERC 27 [2012] PIERC 26 [2012] PIERC 25 [2012] PIERC 24 [2011] PIERC 23 [2011] PIERC 22 [2011] PIERC 21 [2011] PIERC 20 [2011] PIERC 19 [2011] PIERC 18 [2011] PIERC 17 [2010] PIERC 16 [2010] PIERC 15 [2010] PIERC 14 [2010] PIERC 13 [2010] PIERC 12 [2010] PIERC 11 [2009] PIERC 10 [2009] PIERC 9 [2009] PIERC 8 [2009] PIERC 7 [2009] PIERC 6 [2009] PIERC 5 [2008] PIERC 4 [2008] PIERC 3 [2008] PIERC 2 [2008] PIERC 1 [2008]
2026-11-06 Latest Published
By Yujia Song Jiming Qi Jiasheng Wang Yuantai Niu Jinjun Bai Shenghang Huo
Progress In Electromagnetics Research C, Vol. 174, 110-119, 2026
Abstract
Uncertainty quantification (UQ) is an important means of characterizing how input-parameter fluctuations affect electromagnetic responses, and it provides a theoretical basis for performance prediction, reliability evaluation, and robust optimization in computational electromagnetics. For high-cost full-wave electromagnetic simulations, the least-squares support vector regression (LSSVR) surrogate model can improve the efficiency of computational electromagnetics UQ within a reasonable accuracy range because of its small-sample learning and nonlinear fitting capabilities. However, the sampling strategy directly affects the accuracy of the surrogate model. Conventional Latin hypercube sampling (LHS) allocates sampling resources equally among all dimensions, which may waste computational resources in LSSVR-based UQ. The paper proposes an LSSVR surrogate-model-based UQ method incorporating a hierarchical dimensionality reduction sparse grid strategy (LSSVR-DRSG-H) to prioritize the allocation of computational resources to highly sensitive input parameters. Validation results from a case study on human head electromagnetic exposure demonstrate that, compared with the conventional LSSVR, which achieves an MEAM of 0.8391 using 100 full-wave simulations, the proposed LSSVR-DRSG-H attains a higher MEAM of 0.8530 with only 85 full-wave simulations.
2026-11-06
PIER C
Vol. 174, 110-119, 2026
download: 3
Improved LSSVR Uncertainty Quantification Method Based on Hierarchical Dimension-Reduced Sparse Grid
Yujia Song, Jiming Qi, Jiasheng Wang, Yuantai Niu, Jinjun Bai and Shenghang Huo
Uncertainty quantification (UQ) is an important means of characterizing how input-parameter fluctuations affect electromagnetic responses, and it provides a theoretical basis for performance prediction, reliability evaluation, and robust optimization in computational electromagnetics. For high-cost full-wave electromagnetic simulations, the least-squares support vector regression (LSSVR) surrogate model can improve the efficiency of computational electromagnetics UQ within a reasonable accuracy range because of its small-sample learning and nonlinear fitting capabilities. However, the sampling strategy directly affects the accuracy of the surrogate model. Conventional Latin hypercube sampling (LHS) allocates sampling resources equally among all dimensions, which may waste computational resources in LSSVR-based UQ. The paper proposes an LSSVR surrogate-model-based UQ method incorporating a hierarchical dimensionality reduction sparse grid strategy (LSSVR-DRSG-H) to prioritize the allocation of computational resources to highly sensitive input parameters. Validation results from a case study on human head electromagnetic exposure demonstrate that, compared with the conventional LSSVR, which achieves an MEAM of 0.8391 using 100 full-wave simulations, the proposed LSSVR-DRSG-H attains a higher MEAM of 0.8530 with only 85 full-wave simulations.
Improved LSSVR Uncertainty Quantification Method Based on Hierarchical Dimension-Reduced Sparse Grid
2026-11-06
PIER C
Vol. 174, 99-109, 2026
download: 7
SHAP-Based Explainable Machine Learning for Terahertz Material Classification and Sensor Design Guidance
Lifeng Zhu, Jing Shen, Lei Zhang, Yongbin Sun, Xiaofeng Zhang, Luoyi Li, Xianliang Li, Chong Tian, Zhangchong Ye, Jie Cai, Qingqing Ge and Jiangyang Zhan
The black-box nature of machine learning (ML) models limits their adoption in industrial terahertz (THz) inspection systems where decision transparency is mandatory. We present a SHAP-based explainability framework for THz classification of five insulating materials using a 636-dimensional feature set (625 spectral channels plus 11 morphological descriptors) benchmarked across 11 classifiers. LightGBM achieved the highest performance (Macro F1 = 86.84%, Accuracy = 87.18%) and was selected for in-depth SHAP analysis and four validation experiments. SHAP-guided feature selection showed that 50 features (7.9% of the space) already match the full baseline and are the smallest tested subset that does so. Cross-model analysis showed Gradient_Std to be the single highest-ranked SHAP feature for LightGBM, XGBoost, and Random Forest alike, confirming its discriminative role to be a property of the data rather than of a single learner. Four SHAP-identified spectral windows (113 channels, 18.1%) combined with morphological features retained 95.7% of full-spectrum performance (F1 = 83.07%). A noise robustness sweep from 60 dB to 5 dB SNR, assessed against an explicit reliability criterion (Macro F1≥95% of each subset's own noise-free value), places the minimum usable SNR at 30 dB for the full feature set, shows that the morphological descriptors degrade first (falling below their criterion at 50 dB when used alone), and supports a 40 dB design margin. Engineered morphological descriptors contributed 39.8× more per feature than raw spectral channels. These results provide actionable guidance for compact narrowband sensor design and edge deployment in industrial insulation inspection.
SHAP-Based Explainable Machine Learning for Terahertz Material Classification and Sensor Design Guidance
2026-11-05
PIER C
Vol. 174, 91-98, 2026
download: 18
Prediction of Dynamic Electromagnetic Interference for Navigation Receiver of UAV
Ceyi Ma, Wei Shang, Ke Li and Meng Li
To effectively improve the dynamic prediction efficiency of external interference coupling at the airborne antenna end of the quadrotor unmanned aerial vehicle (UAV), and realize the dynamic analysis of electromagnetic interference (EMI) of the quadrotor UAV, we proposed a novel two-dimensional dynamic electromagnetic interference (2D-DEMI) prediction method based on bi-cubic interpolation. By using bicubic interpolation to restore the interference-coupling voltage at the antenna end, the number of samples can be reduced effectively, and prediction can be accelerated. Then, the coupling-voltage database at the antenna end is established by predicting the results. Finally, we evaluated the effectiveness and accuracy of the proposed method through experiments. The results show that the CPU time can be reduced by more than 80% using bi-cubic interpolation algorithm. According to the measured results, the prediction root mean squared error (RMSE) of dynamic electromagnetic interference is just 1.6. The results indicate that the proposed method can rapidly predict the dynamic electromagnetic interference of the quadrotor UAV.
Prediction of Dynamic Electromagnetic Interference for Navigation Receiver of UAV
2026-11-03
PIER C
Vol. 174, 82-90, 2026
download: 19
Design and Implementation of a Compact UWB Filtenna Using a Feed-Line-Integrated Resonator for Mitigating WLAN Interference at 5.8 GHz
Esraa M. Majeed and Ahmed M. A. Sabaawi
This paper presents the design and optimization of a wideband filtering antenna (filtenna) for UWB applications. The design combines a wideband antenna and a feed-line-mounted band-stop filter (BSF) to suppress Wi-Fi (5-6 GHz) interference while keeping the design compact and simple. This antenna is built on a 32 × 32 mm2 FR4 substrate with a partial ground plane and is embedded with a circular ring resonator in the feed line to obtain the desired rejection characteristics. The antenna was designed and simulated using CST Studio Suite. The outcome revealed that the designed filtenna has a wide operating range of 2.78-11.79 GHz with a targeted rejection band around 5-6 GHz. deep resonances are observed at 3.35 GHz and 7.40 GHz, with reflection coefficient of -23.85 dB and -55.14 dB, respectively indicating good impedance matching outside the rejected band. The filtenna was fabricated and experimentally characterized in terms of S11, showing the intended band-rejection behavior with some differences between the simulated and measured response. A parametric study of the ring dimensions shows how the position and bandwidth of the rejection band can be tuned while the UWB response outside the notch is preserved. The filtenna was fabricated, and its measured S11 confirms the band-rejection behavior, with some differences from the simulated response. The results show that a compact feed-line ring resonator is a simple way to introduce WLAN rejection into a UWB antenna, making the design a candidate for sub-6 GHz and IoT applications.
Design and Implementation of a Compact UWB Filtenna Using a Feed-Line-Integrated Resonator for Mitigating WLAN Interference at 5.8 GHz
2026-11-03
PIER C
Vol. 174, 71-81, 2026
download: 4
Photovoltaic Output Power Prediction Based on Thermoelectric Coupling Digital Twin Model of Inverter
Juanjuan Zhang and Xiaoyan Jiang
Accurate photovoltaic (PV) power forecasting requires both meteorological information and a representation of inverter operating states. This study develops a physics-informed DT-LSTM framework in which a reduced-order thermoelectric digital twin converts measured PV power, ambient temperature, wind speed, and irradiance into estimated loss power, thermal load, equivalent temperature, and temperature rise. Field power and weather records from January to June 2024 are aligned causally and divided chronologically into training (January 1-April 15), validation (April 16-30), main testing (May), and external testing (June) periods. At a 5 min resolution over the extended 07:00-22:00 window, DT-LSTM achieves MAE/RMSE values of 65.90/132.12 kW in the main test and 67.07/124.52 kW in the external test, compared with 72.57/137.77 kW and 73.10/130.12 kW for LSTM. The estimated thermal states are model-derived variables rather than measured device temperatures; accordingly, the results demonstrate forecasting utility and physical consistency, not direct temperature-field validation. The study provides a physics-informed virtual-sensing forecasting framework and identifies controlled multi-seed ablation and measured thermal validation as future work.
Photovoltaic Output Power Prediction Based on Thermoelectric Coupling Digital Twin Model of Inverter
2026-11-01
PIER C
Vol. 174, 62-70, 2026
download: 17
FSS-Enabled Modified Bow-Tie Antenna Design for High-Gain, Low-SAR Applications
Kesavalu Naidu Keerthi Naidu and Selvaraj Imaculate Rosaline
This work presents a modified, wide-band, bow-tie antenna integrated with a Frequency Selective Surface (FSS) designed to enhance gain and significantly reduce the Specific Absorption Rate (SAR). The proposed antenna, with a compact profile of 0.47λg × 0.77λg, operates at a center frequency of 2.4 GHz and exhibits a high radiation efficiency. By employing a flared polygonal radiating element, the antenna achieves wide-band performance across an operational spectrum of 1.97 GHz to 3.09 GHz, yielding a fractional bandwidth of 46.7%. An FSS array, functioning as a spatial filter, was designed and positioned 39 mm from the antenna, thereby forming an integrated system. Through numerical simulations, this system shows the gain improvement of the antenna from 2.51 dBi to 6.5 dBi and simultaneously reduces the SAR from 3.9 W/kg to 1.6 W/kg per 10 g of tissue, falling well below the permitted safety limit. The antenna and FSS array prototypes were fabricated and tested for scattering parameters, gain improvement, and radiation pattern. The measured results were in close alignment with the simulations, demonstrating the efficiency of the antenna for safe and high-performance off-body biomedical applications.
FSS-Enabled Modified Bow-Tie Antenna Design for High-Gain, Low-SAR Applications
2026-11-01
PIER C
Vol. 174, 49-61, 2026
download: 5
Online Adaptive Vibration Compensation Control for an Inverter-Driven Six-Pole Active Magnetic Bearing Based on a Fuzzy-Optimized RDC-HWCLMS Algorithm
Zhihao Ma, Yichen Liu and Huangqiu Zhu
To address the inherent trade-off between convergence speed and steady-state error in conventional least mean square (LMS) algorithms for inverter-driven six-pole active magnetic bearings (AMBs), this paper proposes an online adaptive vibration compensation control strategy. In this strategy, a fuzzy-optimized Rayleigh-distribution-curve hybrid-weighted coefficient LMS (RDC-HWCLMS) algorithm is integrated with the influence coefficient method (ICM). First, the rotor unbalance dynamic model is derived, and the LMS-based synchronous vibration extraction principle is analyzed. Second, a Rayleigh-based variable-step-size law is constructed to improve transient convergence, and a hybrid-weighted coefficient update is introduced to suppress steady-state weight fluctuations under noisy displacement measurements. Furthermore, a fuzzy inference system (FIS) is introduced to enhance self-adaptability by dynamically tuning the step-size scaling parameter according to real-time error states. The extracted synchronous vibration components are then used by the ICM to generate compensation current references, which are injected into the AMB control system through the three-phase inverter. Finally, comparative simulated and experimental results on a 4-DOF inverter-driven six-pole AMB platform verify that the proposed online adaptive compensation control method achieves faster convergence, lower residual vibration, and stronger dynamic tracking adaptability than conventional LMS algorithms.
Online Adaptive Vibration Compensation Control for an Inverter-Driven Six-Pole Active Magnetic Bearing Based on a Fuzzy-Optimized RDC-HWCLMS Algorithm
2026-10-30
PIER C
Vol. 174, 42-48, 2026
download: 7
Study on the Effect of Magnetic Field on the Performance of a 5 kW Hall Thruster under High Discharge Voltage
Le Yang, Na Hui, Guoheng Zhang, Ling Guo and Peiyu Wang
This paper studies the changes in plasma discharge characteristics and thruster performance using a two-dimensional PIC-MCC model and performance testing experiments when adjusting the magnetic field configuration in the discharge channel through an additional excitation coil at a propellant flow rate of 5 mg/s and a discharge voltage range of 300-1000 V. The research results indicate that optimizing the magnetic field configuration in the discharge channel can improve the performance of the thruster under high discharge voltage, especially in the discharge voltage range of 600--1000\,V. The simulation results of plasma characteristics show that by adjusting the magnetic field configuration, the ion ionization efficiency can be improved; the wall loss of ions can be reduced; and the acceleration and focusing of ions can be improved. The simulation and experiments results of the thruster performance show that adjusting the magnetic field configuration can improve the efficiency of the thruster, avoid the decrease in thruster efficiency when the discharge voltage increases, and ensure high efficiency while achieving high specific impulse.
Study on the Effect of Magnetic Field on the Performance of a 5 kW Hall Thruster under High Discharge Voltage
2026-10-30
PIER C
Vol. 174, 34-41, 2026
download: 42
A Recursive Semi-Circular Fractal Patch Antenna with Alternating Conductive-Void Arc Topology for UWB Applications
Irsal Djeroud, Habib Khouni, Muhammad Inam Abbasi and Maizatul Alice Meor Said
This study proposes a printed ultra-wideband (UWB) antenna based on a recursive semi-circular fractal topology. The radiating element is generated via the hierarchical decomposition of a primary semi-circular structure into self-similar conductive and void arc segments. This alternating conductive-void arrangement lengthens the effective current path and excites several closely spaced resonant modes that merge into a single continuous band. The antenna is printed on a Rogers RT/duroid 5880 substrate with a thickness of 0.508 mm, characterized by a relative permittivity of εeff = 2.2 and a loss tangent of tanδ = 0.0009, and excited by a 50-Ω microstrip feed line over a notched partial ground plane. Occupying 28 × 30 × 0.508 mm3, corresponding to 0.287λ0 × 0.307λ0 × 0.0052λ0. The design achieves a simulated impedance bandwidth from 3.07 to 13.92 GHz (128% fractional bandwidth), and the measured impedance bandwidth extends from 3.03 to 14.05 GHz (129% fractional bandwidth). The simulated peak realized gain is 5.2 dBi, and the measured peak gain reaches 4.97 dBi. Simulated radiation efficiency above 93.8% across the entire operating band was obtained, and it reaches approximately 98.2% around 8 GHz. The measured radiation patterns show good agreement with simulated results at the investigated frequencies. The experimental validation of the proposed antenna with its thin, low-loss profile supports its potential use in diverse UWB wireless applications and sensing systems.
A Recursive Semi-Circular Fractal Patch Antenna with Alternating Conductive-Void Arc Topology for UWB Applications
2026-10-27
PIER C
Vol. 174, 22-33, 2026
download: 21
Design of Multi-Band Microstrip Rectenna Based on Characteristic Mode Analysis for Ambient RF Energy Harvesting
Srinivasan Vijay, R. Ashok Bakkiyaraj and Mohamed Mohamed Ismail
This paper presents a compact (80 × 80 mm2, approximately 0.66λ at 2.48 GHz) tri-band microstrip rectenna design guided by Characteristic Mode Analysis (CMA) for harvesting ambient RF energy. Modal significance characteristics are used to analyse both the fundamental and higher-order modes, and the required characteristic modes are tuned to the target bands by reshaping the surface current path so that the rectenna operates at S-band (2.48 GHz), 5G band (3.5 GHz), and C-band (4.7 GHz). An RF-to-DC rectifier, comprising an impedance matching network, two SMS7630-079LF Schottky diodes, a 100 pF DC-block capacitor, a low-pass filter, and a smoothing capacitor, is integrated on the same substrate as the multiband antenna. The antenna shows satisfactory impedance matching at its 50-Ω port and stable radiation performance, with fractional impedance bandwidths of 3.2%, 4.31%, and 2.57% at the three bands and a peak realized gain of 7.2 dBi over the operating range. At an input power of -30 dBm, harmonic-balance circuit simulation of the rectifier alone, driven by a 50-Ω source, predicts a peak RF-to-DC conversion efficiency of 52% into a 270 Ω load. Under ambient RF exposure, the fabricated rectenna delivers a measured DC output of 237.2 mV (0.208 mW) across the same load, corresponding to an area-normalized DC output power of approximately 32.5 mW/m2 over its 80 × 80 mm2 footprint. The incident RF power density at the aperture was not independently measured, so this result is reported as demonstrated DC output rather than measured conversion efficiency. These simulated and experimental results indicate that the proposed CMA-based rectenna is a promising candidate for self-powered IoT devices, wireless sensor networks, and other low-power autonomous electronics.
Design of Multi-Band Microstrip Rectenna Based on Characteristic Mode Analysis for Ambient RF Energy Harvesting
2026-10-27
PIER C
Vol. 174, 11-21, 2026
download: 21
Physics-Informed Neural Network Inverse System Decoupling Control for Six-Pole Radial Hybrid Magnetic Bearings Optimized by Hybrid Particle Swarm Optimization Algorithm
Yuechu Ma, Yichen Liu and Huangqiu Zhu
To address severe radial coupling that significantly degrades rotor suspension precision and stability in six-pole radial hybrid magnetic bearings (HMBS), we propose a novel decoupling control that combines a physics-informed neural network (PINN) with a role-adaptive, heterogeneous, improved dynamic multi-swarm particle swarm optimization (HPSO) algorithm. First, we introduce the structure and working principle of the six-pole radial HMBS and derive its mathematical model using the Maxwell tensor method. Second, we construct an inverse system model with a PINN and propose an HPSO algorithm to resolve issues of initial weight sensitivity and gradient vanishing. Subsequently, we establish a six-pole radial HMBS simulation system to evaluate its floating, anti-interference, and decoupling performance. Finally, validation experiments on an experimental platform confirm the method's effectiveness and feasibility. Compared with the backpropagation neural network (BPNN) inverse system control, the proposed HPSO-PINN method reduces the coupling ratio by 37.74\%, effectively suppressing coupling in x- and y-directions.
Physics-Informed Neural Network Inverse System Decoupling Control for Six-Pole Radial Hybrid Magnetic Bearings Optimized by Hybrid Particle Swarm Optimization Algorithm
2026-10-25
PIER C
Vol. 174, 1-10, 2026
download: 14
Multi-Objective Optimization Design of Outer Rotor Permanent Magnet Brushless DC Motor with Cos-Chamfering Magnets
Xiaoting Ye, Xianhai Yu, Zirui Chen and Tao Zhang
To suppress high-order non-working harmonics in the air gap and improve the efficiency of the outer-rotor permanent-magnet brushless DC motor (OPMBLDC), this paper proposes a novel OPMBLDC design using cos-chamfering permanent magnets. First, based on air-gap field modulation theory, we design cos-chamfering permanent magnets. Second, a proxy optimization model of the no-load air-gap magnetic flux density and load torque is constructed by the finite element method and a regression model. Then, the multi-objective optimization design is carried out by the chaotic particle swarm algorithm (CPSO), and the performance indices of the OPMBLDC are compared and analyzed. Finally, the 80 W OPMBLDC with cos-chamfering permanent magnets is manufactured, and experimental results verify that the proposed OPMBLDC with cos-chamfering permanent magnets achieves effective suppression of high-order non-working air-gap harmonics and high efficiency.
Multi-Objective Optimization Design of Outer Rotor Permanent Magnet Brushless DC Motor with Cos-Chamfering Magnets