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Journal articles on the topic 'Theveninův model'

Author: Grafiati
Published: 28 June 2021
Last updated: 2 February 2022

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1

Zhang, Liang, Shunli Wang, Daniel-Ioan Stroe, Chuanyun Zou, Carlos Fernandez, and Chunmei Yu. "An Accurate Time Constant Parameter Determination Method for the Varying Condition Equivalent Circuit Model of Lithium Batteries." Energies 13, no. 8 (April 20, 2020): 2057. http://dx.doi.org/10.3390/en13082057.

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An accurate estimation of the state of charge for lithium battery depends on an accurate identification of the battery model parameters. In order to identify the polarization resistance and polarization capacitance in a Thevenin equivalent circuit model of lithium battery, the discharge and shelved states of a Thevenin circuit model were analyzed in this paper, together with the basic reasons for the difference in the resistance capacitance time constant and the accurate characterization of the resistance capacitance time constant in detail. The exact mathematical expression of the working characteristics of the circuit in two states were deduced thereafter. Moreover, based on the data of various working conditions, the parameters of the Thevenin circuit model through hybrid pulse power characterization experiment was identified, the simulation model was built, and a performance analysis was carried out. The experiments showed that the accuracy of the Thevenin circuit model can become 99.14% higher under dynamic test conditions and the new identification method that is based on the resistance capacitance time constant. This verifies that this method is highly accurate in the parameter identification of a lithium battery model.
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2

Jin, Enshu, Zhenyu Song, Xiaofan Yang, and Xin Yu. "Improved Thevenin Equivalent Model of MMC Considering Pre-charge Conditions and DC Side Fault Conditions." Applied Computational Electromagnetics Society 36, no. 6 (August 6, 2021): 796–805. http://dx.doi.org/10.47037/2020.aces.j.360622.

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The traditional Thevenin equivalent Modular Multilevel Converter (MMC) model has poor versatility for the two working conditions of pre-charging and DC-side faults. In this paper, an improved Thevenin equivalent MMC model considering pre-charge conditions and DC side fault conditions is proposed. The model divides the pre-charging condition into a Controllable charging stage and an Uncontrollable charging stage. The DC-side fault condition is divided into the pre-blocking and post-blocking conditions of the converter. The circuit characteristics are analyzed, and the equivalent model topology is comprehensively improved to make it suitable for full-condition simulation, and a control strategy suitable for the equivalent model is proposed. The detailed model and the proposed improved equivalent model were built in PSCAD/EMTDC for comparison and analysis. The simulation results shows that the improved equivalent model can be applied to various working conditions, and the versatility of the traditional Thevenin equivalent model is improved.
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3

Fang, Yuan Qi, Xi Ming Cheng, and Yi Lin Yin. "SOC Estimation of Lithium-Ion Battery Packs Based on Thevenin Model." Applied Mechanics and Materials 299 (February 2013): 211–15. http://dx.doi.org/10.4028/www.scientific.net/amm.299.211.

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Due to the immeasurability of SOC in battery and inevitability of error in current collection, SOC estimation of Lithium-ion battery has become a focus of EV research. With Thevenin equivalent circuit model, this paper employs EKF algorithm to estimate SOC, which takes into consideration both precision requirement of the estimation and amount of computation involved in online estimation. Based on above-mentioned objectives and principles, a test platform composed of Digatron battery test system and thermostat was built. Experimental result has confirmed that the combination of EKF algorithm with Thevenin model can improve precision and reduce amount of computation.
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4

Di Fazio, Anna Rita, Giuseppe Fusco, and Mario Russo. "Islanding detection method based on a Thevenin-like model." IET Generation, Transmission & Distribution 9, no. 13 (October 1, 2015): 1747–54. http://dx.doi.org/10.1049/iet-gtd.2014.0721.

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5

Lugo-Muñoz, Denise, Juan Muci, Adelmo Ortiz-Conde, Francisco J. García-Sánchez, Michelly De Souza, Denis Flandre, and Marcelo Antonio Pavanello. "Modeling of Thin-Film Lateral SOI PIN Diodes with an Alternative Multi-Branch Explicit Current Model." Journal of Integrated Circuits and Systems 7, no. 2 (December 27, 2012): 92–99. http://dx.doi.org/10.29292/jics.v7i2.360.

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We propose the use of an alternative multi-exponential model to describe multiple conduction mechanisms in thin-film SOI PIN diodes with parasitic series resistance over a wide operating temperature range, from 90 to 390 K. This alternative multi-exponential model can be used for semiconductor junctions which exhibit multiple conduction mechanisms with series and shunt resistances. Using Thevenin’s theorem and the Lambert W function, the terminal current is expressed explicitly as a function of the terminal voltage. Its explicit nature allows higher computational efficiency and makes this model better suited for repetitive simulation applications than conventional implicit models. Additionally, direct analytic differentiation and integration are possible. This alternative model is used to describe the I-V characteristics of real SOI PIN diodes.
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6

Sona, Alessandro. "Augmented Thevenin Model for the Harmonic Analysis of Switching Circuits." IEEE Transactions on Electromagnetic Compatibility 62, no. 4 (August 2020): 1342–48. http://dx.doi.org/10.1109/temc.2019.2935511.

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7

Li, Shaowu. "Circuit Parameter Range of Photovoltaic System to Correctly Use the MPP Linear Model of Photovoltaic Cell." Energies 14, no. 13 (July 2, 2021): 3997. http://dx.doi.org/10.3390/en14133997.

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The real-time linearization of a photovoltaic (PV) cell has been implemented well by the proposition of two maximum power point (MPP) linear models (MPP Thevenin cell model and MPP Norton cell model). However, there is no work to specially analyze the circuit parameter range (CPR) to correctly use them, which seriously impedes the development of the linear control theory involving them. To deal with this problem, in this paper, PV systems with three usual outputs are analyzed and the expressions of their CPR are proposed under ideal conditions. Meanwhile, these expressions are improved to match the practical application. They disclose the relationships between load (or bus voltage) and model parameters of the MPP Thevenin cell model (MPP-TCM) when the MPP of PV system always exists. They also reveal the constraints of load (or bus voltage) when the MPP-TCM is always available. Finally, by some simulation experiments, the accuracy of the expressions of the CPR is verified, the regular patterns of the CPR changing with weather are disclosed, and the comparison of the CPR for different PV systems are made. In this work, the relationships between MPP-TCM and circuit parameters are successfully found, disclosing the constraints among parameters when the MPP-TCM is used to implement the overall linearization of a PV system.
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8

Wei, Ke Xin, and Qiao Yan Chen. "Battery SOC Estimation Based on Multi-Model Adaptive Kalman Filter." Advanced Materials Research 403-408 (November 2011): 2211–15. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.2211.

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This paper introduces multi-model adaptive kalman filter estimation algorithm.Based on the battery thevenin model,the multi-model adaptive kalman filter is applied to the battery SOC(state of charge) estimation, which solute the battery SOC estimation in conditions that the battery model parameters change caused by temperature changing. Simulation results show that compared to the single model kalman filter algorithm, Multi-Model adaptive kalman filter algorithm improves the estimation precision and reliability greatly.
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9

Hinz, Hartmut. "Comparison of Lithium-Ion Battery Models for Simulating Storage Systems in Distributed Power Generation." Inventions 4, no. 3 (August 6, 2019): 41. http://dx.doi.org/10.3390/inventions4030041.

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Lithium-ion batteries are well known in numerous commercial applications. Using accurate and efficient models, system designers can predict the behavior of batteries and optimize the associated performance management. Model-based development comprises the investigation of electrical, electro-chemical, thermal, and aging characteristics. This paper focuses on the analysis of models describing the electrical behavior. In particular, it investigates how cell voltage and state of charge can be determined with sufficient accuracy for a given load profile. For this purpose, the Thevenin-based, the Rint, and the Shepherd’s models, as well as a generic library model of an electronic circuit simulation software package, are compared. The procedure for determining model parameters is discussed in detail. All models are evaluated for the application in the analysis of distributed power generation. The validation is carried out by comparing simulation and measurement results with the help of a case study.
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10

Liu, Xintian, Xuhui Deng, Yao He, Xinxin Zheng, and Guojian Zeng. "A Dynamic State-of-Charge Estimation Method for Electric Vehicle Lithium-Ion Batteries." Energies 13, no. 1 (December 25, 2019): 121. http://dx.doi.org/10.3390/en13010121.

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With the increasing environmental concerns, plug-in electric vehicles will eventually become the main transportation tools in future smart cities. As a key component and the main power source, lithium-ion batteries have been an important object of research studies. In order to efficiently control electric vehicle powertrains, the state of charge (SOC) of lithium-ion batteries must be accurately estimated by the battery management system. This paper aims to provide a more accurate dynamic SOC estimation method for lithium-ion batteries. A dynamic Thevenin model with variable parameters affected by the temperature and SOC is established to model the battery. An unscented Kalman particle filter (UPF) algorithm is proposed based on the unscented Kalman filter (UKF) algorithm and the particle filter (PF) algorithm to generate nonlinear particle filter according to the advantages and disadvantages of various commonly used filtering algorithms. The simulation results show that the unscented Kalman particle filter algorithm based on the dynamic Thevenin model can predict the SOC in real time and it also has strong robustness against noises.
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11

Tian, Ning, Yebin Wang, Jian Chen, and Huazhen Fang. "One-shot parameter identification of the Thevenin’s model for batteries: Methods and validation." Journal of Energy Storage 29 (June 2020): 101282. http://dx.doi.org/10.1016/j.est.2020.101282.

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12

Patel, K. R., and V. D. Patel. "Virtual Experiments in Physics through Computer Technology: Simulation Model of Thevenin Theorem." i-manager's Journal on Embedded Systems 4, no. 1 (April 15, 2015): 28–31. http://dx.doi.org/10.26634/jes.4.1.3693.

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13

Bao, Hui, Wei Jiang, and Dan Wei. "Electric Vehicle Battery SOC Estimation Based on EKF." Advanced Materials Research 926-930 (May 2014): 927–31. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.927.

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In order to estimate the battery state of charge (SOC) accurately, an improved Thevenin model of a battery is established, its mathematical relation is very simple, and also it is easy to realize. In addition, we identify the model parameters, and then use extended Calman filter algorithm to estimate the battery state of charge. The simulation results show that, this model can well reflect the dynamic and static characteristics of a battery, and the Calman algorithm can keep good accuracy in the estimation process.
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14

Gerritsen, T. A., D. O. Racansky, and H. Kunov. "A source impedance compensated artificial voice for mask speech intelligibility testing: Thevenin model." Journal of the Acoustical Society of America 100, no. 5 (November 1996): 3408–16. http://dx.doi.org/10.1121/1.416982.

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15

Chen, Guan-Jhu, Yi-Hua Liu, Yu-Shan Cheng, and Hung-Yu Pai. "A Novel Optimal Charging Algorithm for Lithium-Ion Batteries Based on Model Predictive Control." Energies 14, no. 8 (April 16, 2021): 2238. http://dx.doi.org/10.3390/en14082238.

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Lithium-ion (Li-ion) batteries play a substantial role in portable consumer electronics, electric vehicles and large power energy storage systems. For Li-ion batteries, developing an optimal charging algorithm that simultaneously takes rises in charging time and charging temperature into account is essential. In this paper, a model predictive control-based charging algorithm is proposed. This study uses the Thevenin equivalent circuit battery and transforms it into the state-space equation to develop the model predictive controller. The usage of such models in the battery optimal control context has an edge due to its low computational cost, enabling the realization of the proposed technique using a low-cost Digital Signal Processor (DSP). Compared with the widely employed constant current-constant voltage charging method, the proposed charging technique can improve the charging time and the average temperature by 3.25% and 0.76%, respectively.
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16

Guo, Xiangwei, Xiaozhuo Xu, Jiahao Geng, Xian Hua, Yan Gao, and Zhen Liu. "SOC Estimation with an Adaptive Unscented Kalman Filter Based on Model Parameter Optimization." Applied Sciences 9, no. 19 (October 6, 2019): 4177. http://dx.doi.org/10.3390/app9194177.

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State of charge (SOC) estimation is generally acknowledged to be one of the most important functions of the battery management system (BMS) and is thus widely studied in academia and industry. Based on an accurate SOC estimation, the BMS can optimize energy efficiency and protect the battery from being over-charged or over-discharged. The accurate online estimation of the SOC is studied in this paper. First, it is proved that the second-order resistance capacitance (RC) model is the most suitable equivalent circuit model compared with the Thevenin and multi-order models. The second-order RC equivalent circuit model is established, and the model parameters are identified. Second, the reasonable optimization of model parameters is studied, and a reasonable optimization method is proposed to improve the accuracy of SOC estimation. Finally, the SOC is estimated online based on the adaptive unscented Kalman filter (AUKF) with optimized model parameters, and the results are compared with the results of an estimation based on pre-optimization model parameters. Simulation experiments show that, without affecting the convergence of the initial error of the AUKF, the model after parameter optimization has a higher online SOC estimation accuracy.
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17

Yao, Low Wen, Wirun A/l Prayun, Mohd Junaidi Bin Abdul Aziz, and Tole Sutikno. "Battery State-of-Charge Estimation with Extended Kalman-Filter using Third-Order Thevenin Model." TELKOMNIKA (Telecommunication Computing Electronics and Control) 13, no. 2 (June 1, 2015): 401. http://dx.doi.org/10.12928/telkomnika.v13i2.1467.

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18

Lyu, Zhiqiang, and Renjing Gao. "Li‐ion battery state of health estimation through Gaussian process regression with Thevenin model." International Journal of Energy Research 44, no. 13 (July 17, 2020): 10262–81. http://dx.doi.org/10.1002/er.5647.

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19

Ding, Xiaofeng, Donghuai Zhang, Jiawei Cheng, Binbin Wang, and Patrick Chi Kwong Luk. "An improved Thevenin model of lithium-ion battery with high accuracy for electric vehicles." Applied Energy 254 (November 2019): 113615. http://dx.doi.org/10.1016/j.apenergy.2019.113615.

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20

Huang, Jian Long, Ying Nan Wang, Zhong Feng Wang, Feng Li Han, and Li Gang Li. "The Experiments of Dual Kalman Filter in Lithium Battery SOC Estimation." Applied Mechanics and Materials 494-495 (February 2014): 1509–12. http://dx.doi.org/10.4028/www.scientific.net/amm.494-495.1509.

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We use Thevenin battery model and Kalman filter algorithm to online estimate lithium-ion battery pack state of charge (SOC) in this paper. In order to improve the accuracy of the model we use least square method and Dual Kalman filter (DEKF) algorithms to identify the parameters of model. The battery model can reflect the true state of internal battery well. The principle of Kalman filter algorithm is introduced. The relevant battery testing laboratory is designed. The algorithm has better accuracy when online estimate SOC and adapt to the environment well from experimental results. Finally, the convergence and robustness of DEKF algorithm are verified. It solves the problems that initial estimates are not accuracy and cumulative error.
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21

Shen, Hong Yu, Wen Jun Zhang, Yu Bo Duan, and Jian Jun Xu. "A New PMU-Based Fault Location Algorithm for Three-Terminal." Advanced Materials Research 634-638 (January 2013): 3925–29. http://dx.doi.org/10.4028/www.scientific.net/amr.634-638.3925.

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Existing two-terminal fault location method can not be directly applied to the three-terminal transmission lines, this paper presents a new PMU-based fault location algorithm for three-terminal transmission lines. The development of the algorithm takes advantage of PMU measurement data synchronization, uses distributed parameter line model, first of all judging the fault zone after a failure, uses Thevenin's Theorem to merge the non-slip fault, so the three-terminal system is simplified the two-terminal system, Then we can use the two-terminal fault location principle of fault location. Through MATLAB simulation shows the correctness of the algorithm.
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22

Huang, Jian Long, Zhong Feng Wang, Kun Ya Guo, Xiao Tian Wang, Li Gang Li, and Zhe Zhu Huang. "The Analysis of Modeling of Dual Kalman Filter in Lithium Battery SOC Estimates." Applied Mechanics and Materials 513-517 (February 2014): 4294–97. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.4294.

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In order to online estimate the state of charge (SOC) of lithium-ion battery pack in this paper. This article establishes a dual Kalman filter (DEKF) algorithms for it. We establish a battery model of state space expression based on Thevenin battery model and Kalman filter algorithms. We use least square method and DEKF algorithms to identify the parameters of battery model in order to improve the accuracy of battery model. It can make battery model reflect true state of internal battery well. It introduces the principle which is dual Kalman filter algorithm online estimate the state of charge. Finally, it verifies DEKF algorithm has better convergence and robustness which can effectively resolve the problems of initial estimates error and cumulative error issue.
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23

Al-Khusaibi, T. M., K. A. Ellithy, and M. R. Irving. "State-of-the-Art Methods for Electric Power Systems Voltage Stability Analysis." Sultan Qaboos University Journal for Science [SQUJS] 5 (December 1, 2000): 247. http://dx.doi.org/10.24200/squjs.vol5iss0pp247-263.

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This paper presents a literature survey on the subject of voltage stability analysis of power systems. The survey describes several published methods and techniques used to determine voltage stability indices. These indices predict proximity to voltage instability and collapse problems. The Q-V and P-V curves; singular value decomposition; modal analysis; test function; reduced determinant; loading margin by multiple power flow solutions; local load margins; thevenin/load impedance; and energy function are the methods which have been decribed in the paper. The methods described are based on the original work that first proposed them. They are based on the power-flow system model, where the variation of real and reactive powers are assumed to be the main parameters driving the system to voltage instability. Some of the described methods were applied on the IEEE 30-bus power system.
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24

JIANG, Minglu, Zhangcai HUANG, Atsushi KUROKAWA, Shuai FANG, and Yasuaki INOUE. "Accurate Method for Calculating the Effective Capacitance with RC Loads Based on the Thevenin Model." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E92-A, no. 10 (2009): 2531–39. http://dx.doi.org/10.1587/transfun.e92.a.2531.

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25

Xiong, Rui, Hongwen He, and Kai Zhao. "Research on an Online Identification Algorithm for a Thevenin Battery Model by an Experimental Approach." International Journal of Green Energy 12, no. 3 (October 22, 2014): 272–78. http://dx.doi.org/10.1080/15435075.2014.891512.

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26

Aberbour, Adel, Kassa Idjdarene, and Abdelmounaïm Tounzi. "Performance Analysis of a Self-excited Induction Generator Mathematical Dynamic Model with Magnetic Saturation, Cross Saturation Effect and Iron Losses." Mathematical Modelling of Engineering Problems 7, no. 4 (December 18, 2020): 527–38. http://dx.doi.org/10.18280/mmep.070404.

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Construction of appropriate mathematical model of plant (object to be modeled) has especially important meaning for designing controller. A reliable and good control performance requires more detailed model. Nevertheless, the latter must be established from at least two viewpoints of preciseness and compactness. In this paper, the considered plant is a self-excited induction generator (SEIG). In order to improve the accuracy, we take into consideration in the SEIG modeling: magnetic saturation phenomenon, cross saturation effect and iron losses. To our best knowledge, this is the first time that the three mentioned phenomena have been integrated into the same and single SEIG model which is presented in an inherent mathematical form. As we will see in the results, the contribution of these three phenomena in the accuracy improvement is really significant. In addition, to achieve compactness of the proposed model, a simpler configuration is obtained for the electrical equivalent circuit associated to the studied model by using Thevenin transformation. The proposed model is built in MATLAB-SIMULINK environment and used to study and analyze the performance of a SEIG under various operating point conditions. The obtained results are compared to measurements and also to the values obtained from models without the three discussed phenomena.
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27

Srivastava, Sachin, U. J. Shenoy, Abhinna Chandra Biswal, and Ganesan Sethuraman. "Impedance seen by Distance Relays on Lines Fed from Fixed Speed Wind Turbines." International Journal of Emerging Electric Power Systems 14, no. 1 (May 30, 2013): 17–24. http://dx.doi.org/10.1515/ijeeps-2013-0026.

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Abstract This paper deals with line protection challenges experienced in a system having substantial wind generation penetration. Two types of generators, thermal synchronous generators and fixed speed wind turbines based on squirrel-cage induction generators, are simulated as thevenin equivalent model, connected to grid with single-circuit transmission line. The paper gives comparative discussion and summarizes analytical investigations carried out on the impedance seen by distance relays by varying fault resistances and grid short circuit MVA, for the protection of such transmission lines during faults.
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28

Feng, Kaihui, Bibin Huang, Qionghui Li, and Hu Yan. "Online Estimation of Li-ion Battery SOC for Electric Vehicles Based on An Improved AEKF." E3S Web of Conferences 118 (2019): 02025. http://dx.doi.org/10.1051/e3sconf/201911802025.

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The purpose of this paper is to discuss how to eliminate the influence of noise time -varying characteristics on the accuracy of SOC estimation. Based on the matlab/simulink platform, the Thevenin equivalent circuit model of the battery is built, and an improved Adaptive Extend Kalman Filter (AEKF) is designed, which is compared with the Extend Kalman filter algorithm (EKF).The simulation results are shown that the improved AEKF algorithm results in effective online estimation SOC and the estimation accuracy is higher than the EKF algorithm.
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29

Wang, Zhang Quan, You Rong Chen, and Yue Ruan. "Modeling of Arbitrary Power Level PV Array Based on Circuit Equivalent Mechanism." Advanced Materials Research 424-425 (January 2012): 586–91. http://dx.doi.org/10.4028/www.scientific.net/amr.424-425.586.

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According to the equivalent circuit of single solar cell and the V-I equation of PV cell based on physical mechanism, a simulation model of single solar cell is established. According to this model and structure feature of PV array, the Thevenin circuit equivalent transform theory is used. The control relationship between single solar cell and PV array is given. Then a simple modeling method for arbitrary power level PV array is proposed. To verify the model effectiveness, a Pspice simulation model is established. Output characteristics of the model and its feasibility in PV power generation system are simulated. Simulation results show that the output characteristics of simulation model are in good consistency with actual PV array, and the model can be effectively applied in simulation of PV power generation system. The modeling method is simple and can be used for simulation on some control algorithms of PV power generation system
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30

Jutong, N., D. Sompongse, P. Rakpongsiri, and Apirat Siritaratiwat. "Dependence of Flex on Suspension Capacitance on Human-Body-Model-Electrostatic-Discharge Affected TMR Head." Solid State Phenomena 152-153 (April 2009): 439–42. http://dx.doi.org/10.4028/www.scientific.net/ssp.152-153.439.

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Electrostatic discharge (ESD) effects on GMR recording heads have been reported as the major cause of head failure. Since the information density in hard-disk drives has dramatically increased, the GMR head will be no longer used. The tunneling magnetoresistive (TMR) read heads are initially introduced for a 100 Gbit/in2 density or more. Although the failure mechanism of ESD in GMR recording head has not been explicitly understood in detail, study to protect from this effect has to be undergone. As the TMR head has been commercially started, the ESD effect is closely watched. This is the first time report of the TMR equivalent circuit in order to evaluate the ESD effect. A standard human body model (HBM) is discharged across R+ and R- where the capacitance of flex on suspension (FOS) is varied. It is intriguingly found that the electrical characteristic of the TMR head during discharge period depends on discharge position. This may be explained in terms of asymmetry impedance of TMR by using adapted Thevenin’s theory. The effect of FOS component on TMR recording head is also discussed.
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31

Wang, Hao, Yanping Zheng, and Yang Yu. "Lithium-Ion Battery SOC Estimation Based on Adaptive Forgetting Factor Least Squares Online Identification and Unscented Kalman Filter." Mathematics 9, no. 15 (July 22, 2021): 1733. http://dx.doi.org/10.3390/math9151733.

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In order to improve the estimation accuracy of the battery state of charge (SOC) based on the equivalent circuit model, a lithium-ion battery SOC estimation method based on adaptive forgetting factor least squares and unscented Kalman filtering is proposed. The Thevenin equivalent circuit model of the battery is established. Through the simulated annealing optimization algorithm, the forgetting factor is adaptively changed in real-time according to the model demand, and the SOC estimation is realized by combining the least-squares online identification of the adaptive forgetting factor and the unscented Kalman filter. The results show that the terminal voltage error identified by the adaptive forgetting factor least-squares online identification is extremely small; that is, the model parameter identification accuracy is high, and the joint algorithm with the unscented Kalman filter can also achieve a high-precision estimation of SOC.
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32

Balouktsis, A., T. D. Karapantsios, K. Anastasiou, A. Antoniadis, and I. Balouktsis. "Load matching in a direct-coupled photovoltaic system-application to Thevenin's equivalent loads." International Journal of Photoenergy 2006 (2006): 1–7. http://dx.doi.org/10.1155/ijp/2006/27274.

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A methodology is developed for the assessment of load matching and further estimation of the optimum photovoltaic (PV) arrays arrangement over a prolonged period of time. The method calls for the calculation of the appropriate effectiveness factor defined as the ratio of the load energy over the maximum energy that can be produced by the PV array for a specific time period. The effectiveness factor depends on the PV array characteristics, the load characteristics, and the solar irradiance conditions. To produce realistic predictions for the effectiveness factor and the PV arrays arrangement with validity over long periods of time, the present statistical model describing irradiance employs a stochastic variation of solar radiation over a long period of time and not just a fixed diurnal variation as traditionally done in the past. Simulations are performed for the case of Thevenin's equivalent loads. In order to generalize the analysis, the simulation results are presented in a reduced form based on the values of the voltage and current corresponding to the maximum power of the PV array. The results are presented in multiple-curve comprehensive plots, which allow to determine the optimum photovoltaic array panel's arrangement without engaging sophisticated mathematical calculations.
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33

Díaz-Araujo, Marcolino Humberto, Aurelio Medina-Rios, Manuel Madrigal-Martínez, and Luis Arthur Cleary-Balderas. "Analysis of Grid-Connected Photovoltaic Generation Systems in the Harmonic Domain." Energies 12, no. 24 (December 16, 2019): 4785. http://dx.doi.org/10.3390/en12244785.

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In this contribution, a harmonic domain (HD) model of grid-connected photovoltaic (PV) generation systems is proposed. The topology of the PV generation system contains a PV array connected to a DC/DC converter and a DC/AC converter, coupled to the grid through a filter. The individual components of the PV system are modeled in the HD. The PV array is represented as a Thevenin equivalent, whereas the DC/DC converter and the DC/AC converter are represented in the HD using switching function matrices. The periodic steady-state solution of the PV system is obtained through simple matrix/vector operations. The results obtained by the proposed model are validated against the response obtained with the PSCAD/EMTDC® simulator, widely accepted by the power industry.
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34

Sun, Bing Xiang, Jiu Chun Jiang, and Zhan Guo Wang. "SOC Estimation of Ni-MH Battery Pack Based on Approved HPPC Test and EKF Algorithm for HEV." Advanced Materials Research 403-408 (November 2011): 4398–402. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.4398.

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In this paper, Methods of SOC estimation of Extended Kalman Filter (EKF) is studied based on the characteristics of Nickel-Metal Hydride (Ni-MH) battery pack with 120 cells in series and 8Ah capacity for HEV. In the study of EKF-based SOC estimation, the improved Thevenin circuit model is adopted, and a new hybrid pulse power characterization （HPPC） test is designed to identify the model parameters by using piecewise linear regression method. In this way, the precision of the circuit model is improved. In addition, The Kalman gain matrix is optimized for EKF iterative algorithm by two ways: a constant gain is increased taking into account the entire process; a dynamic gain which increases at the beginning of abrupt change and decreases rapidly after abrupt change is set up. The improvement achieves a good tracing prediction.
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35

Chen, Qiao Yan, and Ke Xin Wei. "Estimation of Electric Vehicle Battery Ohmic Resistance Using Dual Extend Kalman Filter." Applied Mechanics and Materials 391 (September 2013): 246–49. http://dx.doi.org/10.4028/www.scientific.net/amm.391.246.

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Using the traditional measurement analysis methods to estimate electric vehicle lithium ion battery ohmic resistance, it is difficult to realize on line. We in this paper use dual extend kalman filter (DEKF) based on thevenin model to solve this problem. DEKF is a kind of circulative iteration algorithm of two kalman filters, applied in the estimation which the systems state and parameter both are unknown. Using DEKF on the estimation of battery ohmic resistance only need the battery current and terminal voltage, therefore, it can be realized on line easily. This paper verified the effectiveness of DEKF through simulation and analysis of the test data.
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36

Xu, Zhu, Shibin Gao, and Shunfeng Yang. "LiFePO4 battery state of charge estimation based on the improved Thevenin equivalent circuit model and Kalman filtering." Journal of Renewable and Sustainable Energy 8, no. 2 (March 2016): 024103. http://dx.doi.org/10.1063/1.4944335.

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37

Muratoglu, Y., and A. Alkaya. "Unscented Kalman Filter based State of Charge Estimation for the Equalization of Lithium-ion Batteries on Electrical Vehicles." Engineering, Technology & Applied Science Research 9, no. 6 (December 1, 2019): 4876–82. http://dx.doi.org/10.48084/etasr.3111.

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Accurate state of charge estimation and robust cell equalization are vital in optimizing the battery management system and improving energy management in electric vehicles. In this paper, the passive balance control based equalization scheme is proposed using a combined dynamic battery model and the unscented Kalman filter based state of charge estimation. The lithium-ion battery is modeled with a 2nd order Thevenin equivalent circuit. The combined dynamic model of the lithium-ion battery, where the model parameters are estimated depending on the state of charge, and the unscented Kalman filter based state of charge, are used to improve the performance of the passive balance control based equalization. The experimental results verified the superiority of the combined dynamic battery model and the unscented Kalman filter algorithm with very tight error bounds. Furthermore, these results showed that the presented passive balance control based equalization scheme is suitable for the equalization of series-connected lithium-ion batteries.
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38

Yu, Zhong An, and Jun Peng Jian. "Study on Battery Management System Design of Electric Vehicle and Strategy of the SOC Estimation." Advanced Materials Research 945-949 (June 2014): 1500–1506. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.1500.

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In order to improve the efficiency and service life of Lithium batteries for electric vehicle. A structure diagram of battery management system with the digital signal processor as the main controller was designed; in addition, some design modules were expatiated clearly, including the sample circuits of the batterys voltage, current and equalization circuit. The state-space representation of the battery model was established based on Thevenin battery model and extended Kalman filter (EKF) algorithm.According to the estimates and performance characteristics of battery, a new improved-way by amending the Kalman filter gain with the actual situation for raised the SOC estimation accuracy was proposed. The simulation and test results under the condition of simulated driving show that this new way really can increase the SOC accuracy; the equalization scheme can effectively compensate the performance inconsistency of battery pack.
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39

Ma, Xiao, Danfeng Qiu, Qing Tao, and Daiyin Zhu. "State of Charge Estimation of a Lithium Ion Battery Based on Adaptive Kalman Filter Method for an Equivalent Circuit Model." Applied Sciences 9, no. 13 (July 9, 2019): 2765. http://dx.doi.org/10.3390/app9132765.

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Due to its accuracy, simplicity, and other advantages, the Kalman filter method is one of the common algorithms to estimate the state-of-charge (SOC) of batteries. However, this method still has its shortcomings. The Kalman filter method is an algorithm designed for linear systems and requires precise mathematical models. Lithium-ion batteries are not linear systems, so the establishment of the battery equivalent circuit model (ECM) is necessary for SOC estimation. In this paper, an adaptive Kalman filter method and the battery Thevenin equivalent circuit are combined to estimate the SOC of an electric vehicle power battery dynamically. Firstly, the equivalent circuit model is studied, and the battery model suitable for SOC estimation is established. Then, the parameters of the corresponding battery charge and the discharge experimental detection model are designed. Finally, the adaptive Kalman filter method is applied to the model in the unknown interference noise environment and is also adopted to estimate the SOC of the battery online. The simulation results show that the proposed method can correct the SOC estimation error caused by the model error in real time. The estimation accuracy of the proposed method is higher than that of the Kalman filter method. The adaptive Kalman filter method also has a correction effect on the initial value error, which is suitable for online SOC estimation of power batteries. The experiment under the BBDST (Beijing Bus Dynamic Stress Test) working condition fully proves that the proposed SOC estimation algorithm can hold the satisfactory accuracy even in complex situations.
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40

Savard, Christophe, Pascal Venet, Eric Niel, Laurent Pietrac, and Ali Sari. "Insert Switches Inside to Increase Battery Lifespan." European Journal of Engineering Research and Science 5, no. 2 (February 26, 2020): 201–9. http://dx.doi.org/10.24018/ejers.2020.5.2.1769.

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This paper shows the possible gain on time before the end of useful time brought by switches addition in a multicell battery. In a first time, it presents a battery electric model. A battery includes many identical electrical energy cells that electrically interact. From a behavioral standpoint, cell performance is measured by fundamental parameters: State of Charge (SoC) and State of Health (SoH). To simulate cell electrical behavior, the Thevenin model or the Nernst model are often used. However, these models do not take into account the cells aging or the possible interactions on aging. A cell ages mainly in two ways: cyclic and calendar. This aging impacts both the elements of the equivalent electrical model and the fundamental parameters (SoC and SoH). Thus, the conventional electric model of a cell does not accurately reflect the cell aging. In this paper, another formal model based on the fundamental curve that relates electrical and behavioral parameters is proposed. It integrates aging into the equivalent electric model estimation. In a second time, in order to validate this model, this cell model is used to simulate parallel-series association. To improve battery lifespan, in addition to the usual balancing techniques, it may be relevant to require some traditional reliability and operating safety solutions. This requires to add switches inside battery. The presented simulation shows adding switches solution is currently not deployed. This is justified in this paper by examining the impact provide on lifespan improvement on an example, which is pretty weak. But it also shows that however, by managing active cells in a different way, adding switches and spare cells can really reach this improvement.
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de la Hoz, David, Guillermo Salinas, Vladimir Šviković, and Pedro Alou. "Simplification of Thermal Networks for Magnetic Components in Space Power Electronics." Energies 13, no. 11 (June 5, 2020): 2903. http://dx.doi.org/10.3390/en13112903.

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The volume of magnetic components for space applications, directly related to the launch cost, and their performance are critically influenced by their capability to dissipate the internal electromagnetic power losses. This is the reason why accurate thermal models are required. Furthermore, these models need to be simple and versatile to allow a fast analysis of many different designs. In this study, a specific methodology to analyze inductors and transformers by thermal networks and a simplification based on the Thevenin’s theorem leading to a simple equation are proposed. The specific details to address thermal modelling for space magnetic components are discussed. A generic 50 W Flyback transformer for space applications is analyzed in this study and experimental validation is provided, showing that the proposed method leads to a deviation in the temperature estimation between 1 °C and 5 °C, which is considered quite a good result from the literature review carried out.
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42

Khalfi, Jaouad, Najib Boumaaz, Abdallah Soulmani, and El Mehdi Laadissi. "An electric circuit model for a lithium-ion battery cell based on automotive drive cycles measurements." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 4 (August 1, 2021): 2798. http://dx.doi.org/10.11591/ijece.v11i4.pp2798-2810.

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The on-board energy storage system plays a key role in electric vehicles since it directly affects their performance and autonomy. The lithium-ion battery offers satisfactory characteristics that make electric vehicles competitive with conventional ones. This article focuses on modeling and estimating the parameters of the lithium-ion battery cell when used in different electric vehicle drive cycles and styles. The model consists of an equivalent electrical circuit based on a second-order Thevenin model. To identify the parameters of the model, two algorithms were tested: Trust-Region-Reflective and Levenberg-Marquardt. To account for the dynamic behavior of the battery cell in an electric vehicle, this identification is based on measurement data that represents the actual use of the battery in different conditions and driving styles. Finally, the model is validated by comparing simulation results to measurements using the mean square error (MSE) as model performance criteria for the driving cycles (UDDS, LA-92, US06, neural network (NN), and HWFET). The results demonstrate interesting performance mostly for the driving cycles (UDDS and LA-92). This confirms that the model developed is the best solution to be integrated in a battery management system of an electric vehicle.
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43

Xia, Bizhong, Guanghao Chen, Jie Zhou, Yadi Yang, Rui Huang, Wei Wang, Yongzhi Lai, Mingwang Wang, and Huawen Wang. "Online Parameter Identification and Joint Estimation of the State of Charge and the State of Health of Lithium-Ion Batteries Considering the Degree of Polarization." Energies 12, no. 15 (July 31, 2019): 2939. http://dx.doi.org/10.3390/en12152939.

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The state of charge (SOC) and the state of health (SOH) are the two most important indexes of batteries. However, they are not measurable with transducers and must be estimated with mathematical algorithms. A precise model and accurate available battery capacity are crucial to the estimation results. An improved speed adaptive velocity particle swarm optimization algorithm (SAVPSO) based on the Thevenin model is used for online parameter identification, which is used with an unscented Kalman filter (UKF) to estimate the SOC. In order to achieve the cyclic update of the SOH, the concept of degree of polarization (DOP) is proposed. The cyclic update of available capacity is thus obtainable to conversely promote the estimation accuracy of the SOC. The estimation experiments in the whole aging process of batteries show that the proposed method can enhance the SOC estimation accuracy in the full battery life cycle with the cyclic update of the SOH, even in cases of operating aged batteries and under complex operating conditions.
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44

Li, Peng, and Huan Chen. "An Estimation Algorithm of Extended Kalman Filter based on improved Thevenin Model for the management of Lithium Battery System." IOP Conference Series: Earth and Environmental Science 310 (September 5, 2019): 032048. http://dx.doi.org/10.1088/1755-1315/310/3/032048.

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45

Cui, Zhen Ping, Yong Xin Qin, and Hao Li. "Prediction Method of Lithium Battery's State of Charge Based on No Trace of Calman Filter." Advanced Materials Research 912-914 (April 2014): 1888–91. http://dx.doi.org/10.4028/www.scientific.net/amr.912-914.1888.

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The Thevenin equivalent circuit model is established for single lithium battery,current and voltage data to identify the parameters of the equivalent circuit is obtained by the discharge experiment, and the open circuit voltage and charge state relationship curve was obtained by curve fitting.On this basis, design the extended Kalman filter algorithm and unscented Kalman filter algorithm on the lithium battery state of charge, then use Matlab/Simulik simulation, the results of the state prediction of the two different algorithms are compared. The analysis results show that two kinds of algorithm are effective for single lithium battery state of charge estimation, and no trace of Calman filter algorithm can effectively solve the the problem of accuracy is not high of the extended Calman filter ,which due to the linear approximation.
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46

Pereira, Polyanna Mara, Felipe Campelo, Takuya Mori, Hajime Igarashi, and Ricardo Adriano. "A passive SPICE model for rectennas." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 37, no. 6 (November 5, 2018): 1905–17. http://dx.doi.org/10.1108/compel-04-2017-0163.

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Purpose This paper aims to present a SPICE model to represent antennas in receiving mode. The model can be used to evaluate the performance of the antenna when it is coupled to several different nonlinear electric circuits. The proposed methodology is particularly suitable for rectenna applications, as it allows the analysis of different configurations for a rectenna more efficiently than using full-wave analysis simulators coupled directly to each rectifier circuit. Design/methodology/approach The model presented uses reciprocity theory to calculate the ideal voltage source of the Thevenin-equivalent circuit for an antenna. Vector fitting is then used to approximate the model to rational functions that can be converted to Resistor, Inductor and Capacitor circuits. Additional components are added to the circuit to prevent numerical instability. Findings Two rectennas are used to illustrate the performance of the proposed model, one based on a 2.45-GHz rectangular patch antenna and another based on a planar spiral antenna. The second antenna has impedance with positive and negative real parts along the frequency range, which could lead to numerical instabilities. The proposed method is shown to be stable while working with these negative resistance values, which may appear during circuit parameterization. Research limitations/implications The equivalent SPICE circuit model for the antenna makes it easy to simulate nonlinear circuits connected to the antenna and perform transient analyses. The computational cost of antenna analysis is reduced, being more computationally efficient than methods that involve full-wave simulation. This characteristic makes it an interesting approach for working with rectennas, or any application where the time constant of the circuit is much longer than the period of the incident wave. Originality/value For most antenna applications, the numerical stability of the circuit can be achieved using passive enforcement. However, depending on the phase response of the antenna, the impedance that represents its far-field characteristic may present a negative real part, in which case, passive enforcement will fail. In this paper, the problem of numerical instability is solved by introducing an offset resistance and a current-controlled voltage source to the model.
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Fan, Yongcun, Haotian Shi, Shunli Wang, Carlos Fernandez, Wen Cao, and Junhan Huang. "A Novel Adaptive Function—Dual Kalman Filtering Strategy for Online Battery Model Parameters and State of Charge Co-Estimation." Energies 14, no. 8 (April 17, 2021): 2268. http://dx.doi.org/10.3390/en14082268.

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This paper aims to improve the stability and robustness of the state-of-charge estimation algorithm for lithium-ion batteries. A new internal resistance-polarization circuit model is constructed on the basis of the Thevenin equivalent circuit to characterize the difference in internal resistance between charge and discharge. The extended Kalman filter is improved through adding an adaptive noise tracking algorithm and the Kalman gain in the unscented Kalman filter algorithm is improved by introducing a dynamic equation. In addition, for benignization of outliers of the two above-mentioned algorithms, a new dual Kalman algorithm is proposed in this paper by adding a transfer function and through weighted mutation. The model and algorithm accuracy is verified through working condition experiments. The result shows that: the errors of the three algorithms are all maintained within 0.8% during the initial period and middle stages of the discharge; the maximum error of the improved extension of Kalman algorithm is over 1.5%, that of improved unscented Kalman increases to 5%, and the error of the new dual Kalman algorithm is still within 0.4% during the latter period of the discharge. This indicates that the accuracy and robustness of the new dual Kalman algorithm is better than those of traditional algorithm.
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48

Du, Xin, Min Fang Peng, Hong Mei Zeng, Liang Zhu, Hong Wei Che, and Zheng Yi Liu. "Fault Section Location in Distribution Network with DG Based on Voltage Sag Correlation Coefficient." Advanced Materials Research 787 (September 2013): 902–8. http://dx.doi.org/10.4028/www.scientific.net/amr.787.902.

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A fault location method based on correlation coefficient was proposed in the paper for the distribution system with distributed generation (DG). At first, by acquiring the Thevenin equivalent parameters of each DG to establish simulation model of the actual distribution network. Then voltage sag feature vectors of each bus would be obtained by simulating short-circuit fault at the location of each bus, respectively. Afterwards, by calculating and analyzing the correlation coefficient between each bus and the actual fault node,, suspicious fault sections can be determined. Finally, the fault section was identified by utilizing the associated node of every suspicious fault section .The method could reduce the fault search range obviously, without a massive requirement of measuring devices, and the required data can be obtained easily. Simulation results of a 10kV distribution network with DG showed that the proposed method was accuracy and effective.
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Ohlsson, KE Anders, Ronny Östin, and Thomas Olofsson. "Step-transient method for measurement of the heat transfer coefficient at surfaces exposed to simulated building outdoor environments using the sol-air thermometer." Journal of Building Physics 42, no. 3 (April 17, 2018): 373–87. http://dx.doi.org/10.1177/1744259118764823.

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The environmental boundary conditions of the building exterior surface could be expressed in terms of the sol-air temperature To and the heat transfer coefficient ho. This has previously been derived by applying Thevenin’s theorem to the linear thermal network model of the convective and radiative environment. Here, the sol-air thermometer, previously used only for measurement of To, was applied for accurate measurement of ho. The step-transient method was used, where the temperature of the sol-air thermometer was initially raised to above To and then monitored during its transient return to thermal equilibrium. This method was validated by (1) comparison of ho results against values obtained with a steady-state method and (2) comparison of predicted heat flux against the electrical heater power, supplied for validation purpose. Accurate results were obtained, with 7.3% measurement uncertainty. The present sol-air thermometer time constant τ was around 1 h. Based on predictions from dynamic modelling, the τ could be reduced 10-fold, with only small effects on the accuracy from heat loss through the insulation layer.
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Roy, Sanjay Kumar, Kamal Kumar Sharma, Cherry Bhargava, and Brahmadeo Prasad Singh. "Mathematical Modelling and Simulation of Band Pass Filters using the Floating Admittance Matrix Method." WSEAS TRANSACTIONS ON CIRCUITS AND SYSTEMS 20 (August 10, 2021): 208–14. http://dx.doi.org/10.37394/23201.2021.20.24.

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This article aims to develop a band pass filter's mathematical model using the Floating Admittance Matrix (FAM) method. The use of the conventional methods of analysis based KCL, KVL, Thevenin's, Norton's depends on the type of the particular circuit. The proposed mathematical modeling using the floating admittance matrix method is unique, and the same can be used for all types of circuits. This method uses the partitioning technique for large network. The sum property of all the elements of any row or any column equal to zero provides the assurance to proceed further for analysis or re-observe the very first equation. This saves time and energy. The FAM method presented here is so simple that anybody with slight knowledge of electronics but understating the matrix maneuvering, can analyze any circuit to derive all types of transfer functions. The mathematical modeling using the FAM method provides leverage to the designer to comfortably adjust their design at any stage of analysis. These statements provide compelling reasons for the adoption of the proposed process and demonstrate its benefits
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