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学者姓名：黄若辰
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To address the issues of optimizing the operation of island electric-hydrogen coupled systems and high curtailment rates, a dispatch optimization strategy considering refined hydrogen energy modeling is proposed. The article analyzes the operational characteristics and electrolysis efficiency of alkaline electrolyzers and develops a refined model, balancing the economic and reliability aspects of the integrated energy system. An island integrated energy dispatch operation model is established. Case study results show that, compared to traditional electrolyzer models, the proposed model effectively reduces the number of start-stop cycles, extends the lifespan of the electrolyzer array, and enhances system economics. © 2025 IEEE.
Keyword ：
Economics Economics Electric load dispatching Electric load dispatching Electrolytic cells Electrolytic cells Hydrogen Hydrogen Optimization Optimization
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| GB/T 7714 | Meng, Chen , Lin, Qiongbin , Huang, Ruochen et al. Optimized scheduling of integrated energy systems on islands considering refined utilization of hydrogen energy [C] . 2025 : 1377-1382 . |
| MLA | Meng, Chen et al. "Optimized scheduling of integrated energy systems on islands considering refined utilization of hydrogen energy" . (2025) : 1377-1382 . |
| APA | Meng, Chen , Lin, Qiongbin , Huang, Ruochen , Liu, Ruirui , Wang, Wu . Optimized scheduling of integrated energy systems on islands considering refined utilization of hydrogen energy . (2025) : 1377-1382 . |
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Eddy current testing (ECT), as a noncontact and nondestructive testing (NDT) technology, has been widely applied to various industrial fields for pipeline defect detection. In this article, a combined defect parameter estimation method using a novel arc-shaped differential probe with orthogonal receivers is proposed to detect circumferential defects in pipelines. The sensitivity between coils is analyzed to optimize the probe parameters. The scanning signals of defects on the complex plane are characterized by the shell curves (SCs), and a Lissajous curve (LC) model is employed for curve fitting. It is observed that a monotonous relationship holds between fitting parameters and defect dimensions. From the fit scanning curve, the defect depth and length can be estimated by employing the K-nearest neighbors (KNNs) algorithm. Experiments have been conducted to verify the proposed defect parameter estimation method by testing aluminum pipelines with cracks. The experimental results show that the estimation of defect parameters achieves an average accuracy (ACC) of more than 96.78% for various dimensions of cracks.
Keyword ：
Coils Coils Conductivity Conductivity Defect detection Defect detection Defect testing Defect testing eddy-current testing (ECT) eddy-current testing (ECT) estimation method estimation method Feature extraction Feature extraction Permeability Permeability pipeline inspection pipeline inspection Pipelines Pipelines Probes Probes Receivers Receivers Sensitivity Sensitivity sensor design sensor design Testing Testing
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| GB/T 7714 | Zeng, Huade , Huang, Ruochen , Xia, Zihan et al. A Novel Pipeline Defect Detection Method Using an Arc-Shaped Eddy Current Probe [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
| MLA | Zeng, Huade et al. "A Novel Pipeline Defect Detection Method Using an Arc-Shaped Eddy Current Probe" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 74 (2025) . |
| APA | Zeng, Huade , Huang, Ruochen , Xia, Zihan , Lin, Qiongbin , Yin, Wuliang . A Novel Pipeline Defect Detection Method Using an Arc-Shaped Eddy Current Probe . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
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With the widespread adoption of electric vehicles (EVs) and energy storage in renewable energy systems, the use of lithium-ion batteries has increased significantly, making the battery safety performance a primary concern. The accurate state of charge (SOC) estimation can help mitigate the safety risks for the utilisation of EVs and renewable energy systems. Due to the dynamic and non-linear properties of batteries, an adaptive online SOC estimation is proposed in this paper by combining the online parameters estimation using equivalent circuit model (ECM) and the improved particle filter (PF) algorithm. It firstly deduces ECM parameters equations using bilinear transformation with the elimination of the variation caused by the ambient temperature. Then, the seeker optimization algorithm (SOA)-based fixed-length weighted least square (LS) algorithm is introduced to online estimate the battery parameters accurately. With the established ECM, the battery SOC can be estimated by the improved genetic algorithm (IGA) resampling-based PF algorithm, which effectively alleviates the particle degeneracy problem during the estimation, consequently, offering a better performance in SOC estimation. Both simulations and experiments have been conducted to validate the effectiveness of the proposed method. Compared with other existing algorithms, it shows that the proposed algorithm can accurately model the battery with the root mean squared error (RMSE) <0.1 % and achieve the real-time SOC estimation with less computation burden and high accuracy.
Keyword ：
Batteries Batteries Equivalent circuit model Equivalent circuit model Genetic algorithm Genetic algorithm Parameter estimation Parameter estimation Particle filter algorithm Particle filter algorithm State of charge State of charge
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| GB/T 7714 | Lin, Qiongbin , Hong, Huiyang , Huang, Ruochen et al. An adaptive hybrid approach for online battery state of charge estimation [J]. | JOURNAL OF ENERGY STORAGE , 2025 , 115 . |
| MLA | Lin, Qiongbin et al. "An adaptive hybrid approach for online battery state of charge estimation" . | JOURNAL OF ENERGY STORAGE 115 (2025) . |
| APA | Lin, Qiongbin , Hong, Huiyang , Huang, Ruochen , Fan, Yuhang , Chen, Jia , Wang, Yaxiong et al. An adaptive hybrid approach for online battery state of charge estimation . | JOURNAL OF ENERGY STORAGE , 2025 , 115 . |
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Bi-directional DC-AC converters are widely used in the field of electric vehicle-to-grid. However, the inductance of the grid-side interface filter is affected by the length of the grid connection and the power level, which presents nonlinear characteristics. This poses challenges for high-performance grid waveform control. In this paper, a modeling method for bi-directional DC-AC grid-connected converters based on type-II T-S fuzzy models is proposed, and the corresponding type-II T-S fuzzy control strategy is designed to address the parameter uncertainty and non-linearity issues. Simulation results show that type-II T-S fuzzy control offers superior control performance and better current waveform quality compared to type-I T-S fuzzy control under uncertainty parameter conditions. The effectiveness of the proposed strategy is further validated through a 1 kW prototype of a bi-directional DC-AC converter.
Keyword ：
DC-AC inverters DC-AC inverters dual-buck bi-directional inverter dual-buck bi-directional inverter model building model building nonlinear inductance nonlinear inductance type-II T-S fuzzy model type-II T-S fuzzy model
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| GB/T 7714 | Chen, Zhihua , Huang, Ruochen , Lin, Qiongbin et al. Nonlinear Modeling and Control Strategy Based on Type-II T-S Fuzzy in Bi-Directional DC-AC Converter [J]. | ELECTRONICS , 2024 , 13 (9) . |
| MLA | Chen, Zhihua et al. "Nonlinear Modeling and Control Strategy Based on Type-II T-S Fuzzy in Bi-Directional DC-AC Converter" . | ELECTRONICS 13 . 9 (2024) . |
| APA | Chen, Zhihua , Huang, Ruochen , Lin, Qiongbin , Yu, Xinhong , Dan, Zhimin . Nonlinear Modeling and Control Strategy Based on Type-II T-S Fuzzy in Bi-Directional DC-AC Converter . | ELECTRONICS , 2024 , 13 (9) . |
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Advanced wind power prediction technique plays an essential role in the stable operation of the grid with largescale grid integration of wind power. Most research focuses on distance-based static classification where the subjective nature of initial center selection increases the uncertainty of the prediction. And the data classification on a daily basis neglects the potentially significant climate changes at smaller time scales. To address these issues, the improved snake optimization-long short-term memory (ISO-LSTM) model with Gaussian mixture model (GMM) clustering is proposed to forecast wind power from an adaptive perspective. By exploiting the merits of the probabilistic classification, the K-means optimized GMM clustering enables an appropriate feature modelling for substantial climate changes at smaller time scales. Then the ISO algorithm exhibits higher search accuracy and is better suited for finding hyperparameter combinations for LSTM neural networks. The data from the National Aeronautics and Space Administration (NASA) of the US is used to validate the effectiveness of the proposed method. Compared to the traditional K-means clustering, the K-means optimized GMM clustering has increased accuracy by 2.63 %. Simultaneously, with the adoption of the enhanced ISO algorithm, the accuracy further increases by 7.27 %. Different existing models have also been tested; it shows that the proposed model demonstrates higher prediction accuracy.
Keyword ：
Gaussian mixture model Gaussian mixture model Improved snake optimization Improved snake optimization K -means algorithm K -means algorithm Long short-term memory network Long short-term memory network Probabilistic classification Probabilistic classification
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| GB/T 7714 | Zhou, Yu , Huang, Ruochen , Lin, Qiongbin et al. Probabilistic optimization based adaptive neural network for short-term wind power forecasting with climate uncertainty [J]. | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 157 . |
| MLA | Zhou, Yu et al. "Probabilistic optimization based adaptive neural network for short-term wind power forecasting with climate uncertainty" . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 157 (2024) . |
| APA | Zhou, Yu , Huang, Ruochen , Lin, Qiongbin , Chai, Qinqin , Wang, Wu . Probabilistic optimization based adaptive neural network for short-term wind power forecasting with climate uncertainty . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 157 . |
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Eddy-current (EC) testing is one of the contactless nondestructive testing techniques for the physical property measurement (e.g., thickness, electrical conductivity, and magnetic permeability) of steel plates in various industrial applications. In this study, an estimation method of plate thickness and permeability is proposed using the triple-frequency coil inductance with probe lift-off. The functional relationship between the plate properties, probe lift-off, and characteristics of coil inductance is indicated by the simplified analytical model, which is employed for the initial guesses of optimization. The proposed method can decrease the influence of the local minimum on property estimation. Numerical simulations and experiments have been performed to evaluate the proposed method with various plate properties and probe lift-off. Compared with the estimation results without the appropriate initial guesses, the proposed method is more robust and accurate for various cases, with a relative estimation error smaller than 8%.
Keyword ：
Analytical model Analytical model Analytical models Analytical models eddy-current (EC) testing eddy-current (EC) testing Estimation Estimation Frequency estimation Frequency estimation Inductance Inductance Mathematical models Mathematical models Permeability Permeability permeability measurement permeability measurement probe lift-off probe lift-off Probes Probes thickness measurement thickness measurement
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| GB/T 7714 | Xia, Zihan , Huang, Ruochen , Lu, Mingyang et al. Thickness and Permeability Estimation of Metallic Plates by Triple-Frequency Eddy-Current Testing With Probe Lift-Off [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2024 , 73 . |
| MLA | Xia, Zihan et al. "Thickness and Permeability Estimation of Metallic Plates by Triple-Frequency Eddy-Current Testing With Probe Lift-Off" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 73 (2024) . |
| APA | Xia, Zihan , Huang, Ruochen , Lu, Mingyang , Yin, Wuliang . Thickness and Permeability Estimation of Metallic Plates by Triple-Frequency Eddy-Current Testing With Probe Lift-Off . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2024 , 73 . |
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Battery state-of-health (SOH) estimation is an effective approach to evaluate battery reliability and reduce maintenance costs for battery-based backup power supply systems. This paper proposes a novel SOH estimation method for batteries, which only uses the response characteristics of load surges and is, therefore, non-destructive to the estimated battery and its system. The discrete wavelet transform (DWT) method based on multi-resolution analysis (MRA) is used for wavelet energy features extraction, and the fuzzy cerebellar model neural network (FCMNN) is introduced to design the battery SOH estimator. The response voltage signals to load surges are used in the training and detection process of the FCMNN. Compared to conventional methods, the proposed method only exploits characteristics of online response signals to the inrush currents rather than injecting interference signals into the battery. The effectiveness of the proposed method is validated by detailed simulation analysis and experiments.
Keyword ：
dynamical battery state-of-health estimation dynamical battery state-of-health estimation fuzzy cerebellar model neural network fuzzy cerebellar model neural network non-invasive detection non-invasive detection response characteristic of load surges response characteristic of load surges wavelet transform wavelet transform
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| GB/T 7714 | Fan, Yuhang , Lin, Qiongbin , Huang, Ruochen . Non-Invasive Method-Based Estimation of Battery State-of-Health with Dynamical Response Characteristics of Load Surges [J]. | ENERGIES , 2024 , 17 (3) . |
| MLA | Fan, Yuhang et al. "Non-Invasive Method-Based Estimation of Battery State-of-Health with Dynamical Response Characteristics of Load Surges" . | ENERGIES 17 . 3 (2024) . |
| APA | Fan, Yuhang , Lin, Qiongbin , Huang, Ruochen . Non-Invasive Method-Based Estimation of Battery State-of-Health with Dynamical Response Characteristics of Load Surges . | ENERGIES , 2024 , 17 (3) . |
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Eddy -current (EC) testing is one of the contactless nondestructive testing techniques that has been frequently applied to evaluate the defects on metallic objects. In this paper, an estimation method of defect depth on metallic plates is proposed based on the approximate analytical model. An EC coil array sensitive to various defect orientation is designed to scan the plate surface. The independent inductance from various ferritecore coil pairs can be found by the approximate analytical model. The influence of defect on measurements, including depth and edges, is regarded as the variation of probe lift-off in the tested region, defined as the equivalent lift-off. Based on the approximate analytical model, when defect edges have relatively smaller influence, the defect depth on the plate surface can be approximately obtained by estimating the equivalent probe lift-off through optimization. In numerical simulations and experiments, the proposed method is evaluated by testing the aluminum and stainless -steel plates with cracks by the coil array. The reconstructed equivalent lift-off distribution closely relates to the position and dimensions of defects on plates.
Keyword ：
Analytical model Analytical model Defect testing Defect testing Eddy current testing Eddy current testing Metallic plate testing Metallic plate testing
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| GB/T 7714 | Xia, Zihan , Huang, Ruochen , Shao, Yuchun et al. Estimation of defect depth on plates by eddy-current coil array [J]. | SENSORS AND ACTUATORS A-PHYSICAL , 2024 , 369 . |
| MLA | Xia, Zihan et al. "Estimation of defect depth on plates by eddy-current coil array" . | SENSORS AND ACTUATORS A-PHYSICAL 369 (2024) . |
| APA | Xia, Zihan , Huang, Ruochen , Shao, Yuchun , Bai, Xue , Yin, Wuliang . Estimation of defect depth on plates by eddy-current coil array . | SENSORS AND ACTUATORS A-PHYSICAL , 2024 , 369 . |
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The forward model of eddy-current (EC) testing can predict the measurement signals, provided the known measurement conditions and physical properties of test pieces. In the analytical forward model, the test pieces are characterized by the reflection coefficient (RC), which describes the reflection characteristics of test pieces regarding incident electromagnetic (EM) waves and determines the phase of EC signals. The RC is calculated analytically with boundary conditions, which is sophisticated for analyzing complex geometries. In this study, the analytical model of plate and pipe testing using second-order vector potential (SOVP) is investigated. It is found that the numerical RC can be obtained from the source EM field in the air and counterparts in the presence of test pieces. In numerical simulations, the numerical RC is compared with the analytical RC for plate and pipe in a 2-D axisymmetric model. In the 3-D model, the calculated numerical RC corresponds to the dimensions of the measured plate and pipe with defects. In both 2-D and 3-D models, the phase of coil inductance from the numerical RC aligns with the finite-element solutions. It is validated that the RC is a characteristic of test pieces independent of the source field.
Keyword ：
Analytical model Analytical model Coils Coils eddy-current (EC) testing eddy-current (EC) testing electromagnetic (EM) sensing electromagnetic (EM) sensing Finite element analysis Finite element analysis Inductance Inductance Mathematical models Mathematical models Numerical models Numerical models numerical solution numerical solution reflection coefficient (RC) reflection coefficient (RC) Solid modeling Solid modeling Testing Testing
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| GB/T 7714 | Xia, Zihan , Bai, Xue , Huang, Ruochen et al. Insight Into the Eddy-Current Reflection Coefficient of Plates and Pipes [J]. | IEEE TRANSACTIONS ON MAGNETICS , 2024 , 60 (11) . |
| MLA | Xia, Zihan et al. "Insight Into the Eddy-Current Reflection Coefficient of Plates and Pipes" . | IEEE TRANSACTIONS ON MAGNETICS 60 . 11 (2024) . |
| APA | Xia, Zihan , Bai, Xue , Huang, Ruochen , Lu, Mingyang , Yin, Wuliang . Insight Into the Eddy-Current Reflection Coefficient of Plates and Pipes . | IEEE TRANSACTIONS ON MAGNETICS , 2024 , 60 (11) . |
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This article proposed a method to simultaneously estimate the permeability, conductivity, thickness, and lift-off of metallic plates using sweep frequency eddy current measurement combined with machine learning (ML). The whole processing was mainly divided into characteristic extractions and a data-driven machine learning model. According to the classical Dodd and Deeds analytical solution, the characteristic value of mutual inductance signal related to metallic plate parameters is extracted based on theoretical derivation. The parameters of metallic plates are inherently coupled together; thus, the parameters of metallic plates cannot be directly and accurately obtained using only characteristic information. In this article, the machine learning modeling combining the extracted features is established to achieve decoupling and high-precision inversion. The data required for model training comes from the customized fast finite element method (FEM) solver and analytical solution. While the experiment data act as the test set to verify the performance of the proposed method. The results show the proposed method can be applied to accurately estimate the parameters of metallic plates, and the relative errors of inverted parameters are within 3.5%.
Keyword ：
Characteristic extraction Characteristic extraction machine learning (ML) model machine learning (ML) model parameters decoupling parameters decoupling sweep frequency eddy current measurement sweep frequency eddy current measurement
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| GB/T 7714 | Huang, Pu , Bao, Zhenyu , Huang, Ruochen et al. Decoupling Permeability, Conductivity, Thickness, Lift-Off for Eddy Current Testing Using Machine Learning [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2023 , 72 . |
| MLA | Huang, Pu et al. "Decoupling Permeability, Conductivity, Thickness, Lift-Off for Eddy Current Testing Using Machine Learning" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 72 (2023) . |
| APA | Huang, Pu , Bao, Zhenyu , Huang, Ruochen , Jia, Jieshu , Liu, Kuanyao , Yu, Xing et al. Decoupling Permeability, Conductivity, Thickness, Lift-Off for Eddy Current Testing Using Machine Learning . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2023 , 72 . |
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