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

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 novel parameter identification method for induction motors 5

A novel parameter identification method for induction motors

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5th International Conference on Electrical Machines and Systems

作者： Wu, J Li, SY Pan, MC Natl Univ Def Technol Changsha 410073 Hunan Peoples R China

This paper presents a novel parameter identification method for induction motors, using least square estimation algorithm. It simplified practical applications, due to certain models and filters. Finally, promising re... 详细信息

ISBN: (纸本)7506251159

关键词： variable speed drives induction motor drives machine control velocity control parameter estimation least squares approximations control system analysis machine theory induction motors parameter identification method least square estimation algorithm practical applications models filters variable speed motor drives

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parameter identification method for Ship Swaying Motion Differential Equations

Parameter Identification Method for Ship Swaying Motion Diff...

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The Third International Joint Conference on Computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

作者： Lei Yang Xiaoyong Li GuimingChen Zhonghua Zhang Yi Wu China Satellite Maritime Tracking and Control Department Jiangyin Jiangsu 214431 China School of Science National University of Science and Technology Changsha 410073 China

This paper Introduces a solution method for ship swaying motion differential equations—maximum likelihood parameter identification method. To evaluate its data processing effects, we have taken the real-time measurement data as a research object and computed with several algorithms, at the same time compared their prediction results. The results show that parameter identification method for differential equation is reliable in calculation, whose accuracy can satisfy the demand for shipboard equipments to accurately track space targets, which is recommended to use for ship swaying measurement data processing.

关键词： ship swaying motion differential equation parameter identification method maximum likelihood estimation

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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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The modeling and parameter identification method of hydraulic engine mounts

The modeling and parameter identification method of hydrauli...

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2008建模、辨识与控制国际会议

作者： Qian Li School of Mechanical Engineering, Shanghai Jiao tong University, Shanghai 200240, P.R. China Jiancai Zhao School of Mechanical Engineering, Shanghai Jiao tong University, Shanghai 200240, P.R. China Bo Zhao School of Mechanical Engineering, Henan Polytechnic University, Jiaozuo 454000, P.R. China Xunsheng Zhu School of Mechanical Engineering, Shanghai Jiao tong University, Shanghai 200240, P.R. China

Hydraulic engine mounts (HEMs) are important vibration isolation parts in vehicle powertrain mounting systems. The vibration isolation characteristics of HEMs may greatly affect the noise, vibration and harshness (NVH) properties of vehicles, so it has great significance to acquire the vibration isolation characteristics of HEMs. A simplified lumped model and a new method to identify the parameters in this model are proposed in this study. Experiments are also done to validate the model and parameter identification method. The results imply the simulation vibration isolation characteristics agree well with the experimental results. The vibration isolation characteristics of HEMs can be easily obtained by this model and parameter identification method. This parameter identification method is instructive for the design and tuning of the vibration isolation characteristics of HEMs.

关键词： hydraulic engine mount (HEM) vibration isolation characteristic noise, vibration and harshness (NVH) parameter identification method

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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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Two-step method for the online parameter identification of a new simplified composite load model

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IET GENERATION TRANSMISSION & DISTRIBUTION 2016年第16期10卷 4048-4056页

作者： Yu, Songtai Zhang, Shuqing Zhang, Xinran Tsinghua Univ Dept Elect Engn Beijing Peoples R China

The electrical load is one of the most important parts of power systems. parameter identification of load model is critical for power system stability analysis. The composite load model, which comprises a static load and a dynamic load, is one of the most widely used models in power system simulation and control. As the load characteristics could change considerably over time, online parameter identification is needed. However, because of the non-linearity and complexity, online parameter identification for load models remains difficult to achieve, and there is rarely an effective solution. This study proposes a load model simplification and parameter identification method to solve this problem. First, the composite load model is preliminarily simplified by choosing the dominant parameters. Next, the load model is further simplified based on a second-ordered state equation of the induction motor. Subsequently, a two-step method for online parameter identification is presented. The first step is the electrical parameter identification based on the multi-layer searching method proposed in this study. The second step is the mechanical parameter identification via the Newton method. Finally, an example for a typical case system is presented to demonstrate the effectiveness, efficiency and accuracy of the two-step method.

关键词： load (electric) parameter estimation power system stability induction motors online parameter identification composite load model electrical load power systems power system stability analysis static load dynamic load power system simulation power system control load characteristics parameter identification method second-ordered state equation induction motor multilayer searching method Newton method

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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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Novel Supercapacitor Model parameter identification methods 2

Novel Supercapacitor Model Parameter Identification Methods

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2nd International Conference on Power and Renewable Energy (ICPRE)

作者： Chang, Xiao Lei, Da Zhang, Shifeng Li, Shengwen Yang, Yunlei State Grid Shanxi Elect Power Co Elect Power Res Inst Taiyuan 030001 Shanxi Peoples R China

ISBN: (纸本)9781538621561

Supercapacitor based energy storage system has been applied in different power level applications for years. Due to its ultra-high capacitance and capacitor characteristics, it is ideal for high power short duration circumstances, such as regenerative braking in electric vehicle, transient frequency control in power grid. For all such supercapacitor applications, an accurate model of supercapacitor is essential for analysing its behaviour under various operating conditions. Many different electrical models have been proposed to improve accuracy under different conditions, such as the three branch model, ladder model, and transmission line model. The associated parameter identification methods are also important in improving model accuracy. Different models are reviewed in this paper, and its applicable conditions for each model are discussed. Two novel parameter identification methods are proposed, which provides better accuracy in describing supercapacitor discharge behaviour with a simplified experimental test. The mathematical model and experimental comparison are provided to verify the new parameter identification method.

关键词： supercapacitor model parameter identification method energy storage

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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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