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An Investigation on parameter identification method of Controlling Chaos in Generalized Lotka-Volterra Systems Via Hybrid Projective Difference Combination Synchronization Technique

An Investigation on Parameter Identification Method of Contr...

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Congress on Advances in Materials Science and Engineering, CAMSE 2020

作者： Khan, Taqseer Chaudhary, Harindri Department of Mathematics Jamia Millia Islamia New Delhi India

ISBN: (纸本)9789811609411

This manuscript puts forward the chaos controlling in the dynamics of the generalized Lotka-Volterra biological system. Firstly, the phase diagrams and Lyapunov exponents are presented to illustrate the chaotic behaviour of generalized Lotka-Volterra system. Secondly, a parameter identification method has been investigated for chaos control in the given system using hybrid projective difference combination synchronization technique. The discussed approach derives the global asymptotical stability condition using Lyapunov stability theory. Numerical simulation is performed via MATLAB environment to depict the efficacy of the discussed control function design. Remarkably, both our theoretical and computational results are in complete agreement. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Chaotic system Combination synchronization Difference synchronization Generalized Lotka-Volterra system Hybrid projective synchronization parameter identification method

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A parameter identification method based on time-frequency analysis for time-varying vehicle dynamics

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2016年第1期230卷 3-17页

作者： Zhang, Ning Xiao, Hong Winner, Hermann Tech Univ Darmstadt Fahrzeugtech Darmstadt D-64287 Darmstadt Germany

This paper proposes a novel time-frequency analysis-based parameter identification method for time-varying vehicle dynamics under harmonic conditions. The motivation is to identify the potential time-varying system parameters from experimental data corresponding to a linear single-track model, which has the aim of model identification in order to build simulation models. Based on the single-track model and time-frequency analysis, many vehicle dynamics parameters, such as the (normalized) cornering stiffness of the axle and the instantaneous friction coefficient, are available with the assistance of this method. The method has the prominent advantage that it is capable of identifying the time-varying system parameters within the range of linear lateral dynamics. The coupling between the vertical dynamics and the horizontal dynamics is also considered with an effective axle load evaluation algorithm, by which the influence of a specific dynamic axle load on the cornering stiffness of the axle can be described. It is also integrated into the parameter identification method. Finally the method is applied to validate a complicated simulation model of a car-trailer combination obtained with IPG CarMaker (R) software using the experimental data.

关键词： Time-frequency analysis parameter identification method time-varying systems single-track model cornering stiffness

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A comparative study of parameter identification methods for equivalent circuit models for lithium-ion batteries and their application to state of health estimation

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JOURNAL OF ENERGY STORAGE 2025年 114卷

作者： Sun, Jinghua Liu, Yixin Kainz, Josef Tech Univ Munich Energy Technol Campus Straubing Biotechnol & SustainabilSchulgas D-94315 Straubing Germany Weihenstephan Triesdorf Univ Appl Sci Schulgasse 16 D-94315 Straubing Germany

Accurate estimation of the battery state is a crucial requirement for advanced battery management systems (BMS). Model-based state estimation methods represent the most promising option to meet BMS requirements, where the equivalent circuit model (ECM) is an effective balance between modelling complexity and accuracy. ECM's accuracy is influenced by the combination of chosen model type and parameter identification method. In this paper, batteries are aged under various conditions. Both frequency and time domain measurements are performed on batteries in a variety of aging states. These measurements are employed for comparing all combinations of 7 existing models with 7 common identification methods. In addition, the accuracy of SOH models based on ECM parameters is investigated. The experimental results indicate that for frequency and time domain measurements, the same identification algorithm may exhibit distinct performances. Overall, PSO, GWO and LSQ are ideal candidates. Among them, PSO and GWO perform optimally in the frequency domain environment, while LSQ is superior in the time domain environment. Furthermore, this conclusion does not change with battery aging. Meanwhile, a simpler model structure is even beneficial for efficiently monitoring SOH when utilizing the aforementioned superior identification methods.

关键词： Lithium-ion battery Equivalent circuit model parameter identification method Comparative study State of health

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Multi-physics modeling and equivalent circuit parameters estimation for electrolytic hydrogen production systems

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2025年 97卷 1357-1364页

作者： Xu, Wanwan Wang, Bin Cheng, Yan Chen, Xuxuan Wuhan Univ Sci & Technol Sch Informat Sci & Engn Wuhan 430081 Peoples R China Wuhan Univ Sci & Technol Key Lab Met Automat & Detect Technol Minist Educ Wuhan 430081 Peoples R China

Achieving "carbon neutrality" is a critical environmental goal, and hydrogen production from renewable energy is a key strategy. However, the absence of a robust parameter identification method for hydrogen production loads presents a significant challenge. This paper addresses this gap by developing a multi-physics proton exchange membrane electrolysis cell (PEMEC) electrolyzer model and estimating its parameters based on actual operational data. Additionally, the parameters of the power conversion system's equivalent circuit are determined. To ascertain the accuracy of our comprehensive model, a third-order generalized integrator is used to extract harmonic currents, thereby enabling precise calculations of harmonic power. Finally, the effectiveness of the strategy is validated by three cases in Matlab/Simulink and hardware-in-loop (HIL) environment.

关键词： Hydrogen production parameter identification method Multi-physics model Equivalent circuit Hardware-in-loop

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parameter identification of direct-drive permanent magnet synchronous generator based on EDMPSO-EKF

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IET RENEWABLE POWER GENERATION 2022年第5期16卷 1073-1086页

作者： Xiao, Qianghui Liao, Kaixian Shi, Chuandong Zhang, Yang Hunan Univ Technol Coll Elect & Informat Engn Zhuzhou Hunan Peoples R China

Aiming at the problem that extended Kalman filter (EKF) is difficult to determine the appropriate system and measurement noise matrices in parameter identification of direct-drive permanent magnet synchronous generator (D-PMSG), a parameter identification method of D-PMSG based on mean particle swarm optimization with extreme disturbance (EDMPSO)-EKF is proposed. Firstly, by analysing the principle of EKF, a dual-thread identification model is established, then the particle swarm optimization (PSO) algorithm is improved to jump out of the local optimum by adding extremum interference and taking average extremum, and a suitable fitness function is designed. Finally, the improved PSO algorithm is applied to the adaptive optimization of EKF system noise matrix and measurement noise matrix, and the system performs the parameter identification after obtaining the optimal noise matrix. The simulation and experiment results show that the proposed method has better convergence speed and can more accurately identify the parameters of stator resistance, inductance and flux linkage, and it has better identification accuracy and generalization ability than the traditional method.

关键词： measurement noise matrix extremum interference stators power generation control improved PSO algorithm taking average extremum appropriate system dual-thread identification model measurement noise matrices machine control adaptive optimization particle swarm optimisation permanent magnet generators mean particle swarm optimization parameter estimation synchronous generators Kalman filters identification accuracy particle swarm optimization algorithm direct-drive permanent magnet synchronous generator optimal noise matrix extreme disturbance-EKF generalization ability parameter identification method EDMPSO-EKF nonlinear filters

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Design and implementation of a parametric battery emulator based on a power converter

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IET ELECTRIC POWER APPLICATIONS 2022年第11期16卷 1300-1316页

作者： Li, Ruihua Ji, Yunqiu Fu, Yiyang Hu, Bo Hu, Hao Tongji Univ Dept Elect Engn 4800 Caoan Highway Shanghai 201804 Peoples R China State Grid Shanghai Jiading Elect Power Supply Co Shanghai Peoples R China Tongji Univ Inst Rail Transit Shanghai Peoples R China

Real batteries used for the performance testing and evaluation of the drive systems of electric vehicles (EVs) are being replaced by battery emulators (BEs) because of the high test costs, long test cycles, and difficulty in adapting to extreme operating conditions associated with the use of real batteries. A parametric BE for a lithium-ion battery based on a voltage source converter is presented. First, a Thevenin model of the battery is established, and a parameter identification method is proposed to obtain the relationship between the parameters of the battery model and the characteristics of the external electrical port (i.e. I-V characteristics) of the battery. Subsequently, based on the I-V characteristics, the topological structure of the power electronic device of the BE is designed, and the working modes under charging and discharging conditions are presented. Finally, an experimental prototype of the BE is designed and tested. The experimental results show that the proposed BE power converter can successfully simulate the external port voltage and current characteristics of the battery, which can replace the real battery to provide an effective test environment for the test and evaluation of the electric drive system of EVs.

关键词： electric vehicles lithium-ion battery BE power converter voltage source converter voltage-source convertors long test cycles lithium compounds secondary cells electric drive system electric drives I-V characteristics parameter identification method parametric battery emulator power electronic device performance testing power electronics parameter estimation battery powered vehicles

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Friction torque field distribution of a permanent-magnet spherical motor based on multi-physical field coupling analysis

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IET ELECTRIC POWER APPLICATIONS 2021年第8期15卷 1045-1055页

作者： Li, Haolin Li, Guoli Wang, Qunjing Ju, Bin Wen, Yan Anhui Univ Sch Elect Engn & Automat Hefei Peoples R China Anhui Univ Natl Engn Lab Energy Saving Motor & Control Techn Hefei Peoples R China Anhui Univ Anhui Prov Lab Elect Economize & Safety Hefei Peoples R China Anhui Univ Collaborat Innovat Ctr Ind Energy Saving & Power Hefei Peoples R China Anhui Univ Sch Internet Hefei Peoples R China

Non-linear friction between the rotor and the rotor support mandrels would occur during the movement of the permanent-magnet spherical motor (PMSpM). The friction which varies with the position causes PMSpM jitter or even stop it when running at low speeds, and the system operation accuracy is reduced. To solve these problems, this work proposes a parameter identification method of the Coulomb friction model. First, a dynamics model with the Coulomb friction of PMSpM is established by using generalised Euler angles and the Lagrangian energy method. Then, a parameter identification method of the Coulomb friction model based on COMSOL Multi physics coupled simulation and MEMS experiment is proposed to obtain the friction torque data of the PMSpM. Finally, the friction torque compensation in a closed-loop control experiment is completed by using the friction data. The results show that the accuracy of trajectory tracking control is significant, and the error is reduced by 49.32%. Hence, the distribution of the friction torque field is accurate and effective.

关键词： Spatial variables control COMSOL Multiphysics nonlinear friction friction PMSpM jitter parameter identification method friction data Control of electric power systems Numerical analysis dynamics model permanent-magnet spherical motor Lagrangian energy method rotor support mandrels Mechanical components friction torque data closed loop systems Tribology (mechanical engineering) Mechanical variables control friction torque field distribution Coulomb friction model torque permanent magnet motors friction torque compensation machine control system operation accuracy multiphysical field position control finite element analysis parameter estimation rotors torque control

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Study of parameters identification method of Li-Ion Battery Model for EV Power Profile Based on Transient Characteristics Data

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2021年第1期22卷 661-672页

作者： Sun, Bingxiang He, Xitian Zhang, Weige Ruan, Haijun Su, Xiaojia Jiang, Jiuchun Beijing Jiaotong Univ Sch Elect Engn Beijing 100044 Peoples R China

Power simulation of lithium ion battery through battery model is of great significance for dynamic response simulation, heat generation calculation and charge-discharge strategy development. The accuracy and applicability of the model become crucial. In order to demonstrate the battery transient characteristics more effectively, a novel identification method for parameters of the 2(nd) order RC equivalent circuit model was proposed. Based on the derived evolution law of battery transient characteristics under the continuous pulse excitation, four feature points are extracted for parameter identification in each cycle. The proposed method reduced the time cost of identification from 11796.88s to 0.06s while ensuring that the error of voltage doesn't exceed 2.2mV. In order to verify the power profiles applicability of the proposed method, applicability analysis of power profile for different identification methods was carried out including the methods using different amount of data (4N points, 200 points, 6000 points) under unidirectional current pulse excitation (UCPE), bidirectional current pulse excitation (BCPE) and unidirectional voltage pulse excitation (UVPE). It was illustrated that the identification process using data of multiple cycles could significantly reduce errors, including maximum error and average error. What's more, the proposed method under UCPE had the lowest maximum error of 0.420% in voltage simulation and -0.421% in the current simulation of power profiles. Compared with the conventional method (using 200 points of single pulse data for parameter identification), the proposed method can reduce the average voltage error and the maximum error by 62.5% and 11.8% respectively under the DST power profile.

关键词： Mathematical model Transient analysis Integrated circuit modeling Data models Electronic countermeasures Lithium-ion batteries Lithium ion battery power profile equivalent circuit model parameter identification method pulse excitation

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A new iterative identification algorithm for estimating the LuGre friction model parameters

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Mechanism and Machine Theory 2024年 203卷

作者： Mahmoudkhani, Saeed Gorenstein, Johnathan Ahmadi, Keivan Faculty of New Technologies and Aerospace Engineering Shahid Beheshti University Tehran Iran Department of Mechanical Engineering University of Victoria VictoriaBCV8 W 2Y2 Canada

The parameters of dynamic friction models like the LuGre model are commonly identified by computationally intensive nonlinear optimization methods. In this paper, an alternative least-square-based iterative algorithm is proposed to simultaneously identify the LuGre model parameters and the inertial properties from a limited set of measurements. The LuGre model, expressed in two forms allowed independent identification of the static and dynamic parameters. Moreover, since the method uses response-input time–history instead of numerous constant velocity experiments (CVEs), both the inertial and friction parameters can be identified in much fewer experiments (theoretically one). A variant of the Sparse identification of Nonlinear Dynamics method called SR3 is embedded in the algorithm to capture the nonlinear viscous friction and Stribeck effects in the friction model. Application of the algorithm to an industrial robot joint shows that the convergence of the algorithm is fast and the identified model is accurate in predicting the joint's dynamics in a wide range of velocities. The friction-velocity curves resulting from the identified model are compared to those obtained by traditional CVEs to confirm the accuracy of the identified model. © 2024 Elsevier Ltd

关键词： LuGre friction model parameter identification method SINDy-SR3 Sparse regression

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Fractional Viscoelastic Models for Asphalt Concrete: From parameter identification to Pavement Mechanics Analysis

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JOURNAL OF ENGINEERING MECHANICS 2022年第8期148卷 04022036-04022036页

作者： Quan, Weiwen Zhao, Kaiwen Ma, Xianyong Dong, Zejiao Harbin Inst Technol Sch Transportat Sci & Engn Harbin 150090 Peoples R China

The fractional viscoelastic model has been applied to characterize the viscoelasticity of asphalt concrete (AC), but it rarely is adopted in pavement structure analysis due to the complicated calculating process. Therefore, simple methods of applying the fractional viscoelastic models in the pavement mechanic analysis are proposed. First, based on the derived complex modulus expressions of the typical fractional viscoelastic model of AC, combined with the particle swarm optimization and interior-point algorithm, a novel global optimization algorithm for the parameter identification of fractional viscoelastic models is proposed. Then, based on the dynamic modulus and phase angle data obtained in laboratory experiments, the viscoelastic parameters of AC were identified, and the performance of different viscoelastic models was evaluated. Subsequently, based on the Grunwald-Letnikov definition of the fractional operator and the Newton-Raphson integration scheme, the numerical implementation algorithm of some typical fractional viscoelastic models of AC in finite element analysis is proposed, followed by compiled user material subroutines (UMATs). Finally, the thermoviscoelastic analysis of an asphalt pavement structure under impact load was conducted, and the mechanical response laws revealed by different viscoelastic models were investigated. The results showed that the fractional viscoelastic model could yield a more accurate prediction of the viscoelasticity of AC in a wider frequency domain compared with the integer-order viscoelastic model. Moreover, due to the ability to simulate the mechanic behavior of the pavement structure in all temperature ranges with fewer parameters, the modified fractional Zener model is recommended for pavement mechanics analysis.

关键词： Fractional viscoelastic model parameter identification method Dynamic responses analysis Asphalt pavement Finite-element method

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