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State of charge estimation by finite difference extended kalman filter with HPPC parameters identification

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Science China(Technological Sciences) 2020年第3期63卷 410-421页

作者： HE Lin HU MinKang WEI YuJiang LIU BingJiao SHI Qin Automotive Research Institute Hefei University of TechnologyHefei 230009China School of Automotive and Transportation Engineering Hefei University of TechnologyHefei 230009China

State of charge(SOC) is a key parameter of lithium-ion battery. In this paper, a finite difference extended kalman filter(FDEKF)with Hybrid Pulse Power Characterization(HPPC) parameters identification is proposed to estimate the SOC. The finite difference(FD) algorithm is benefit to compute the partial derivative of nonlinear function, which can reduce the linearization error generated by the extended kalman filter(EKF). The FDEKF algorithm can reduce the computational load of controller in engineering practice without solving the Jacobian matrix. It is simple of dynamic model of lithium-ion battery to adopt a secondorder resistor-capacitor(2 RC) network, the parameters of which are identified by the HPPC. Two conditions, both constant current discharge(CCD) and urban dynamometer driving schedule(UDDS), are utilized to validate the FDEKF *** convergence rate and accuracy between the FDEKF and the EKF algorithm, it can be seen that the former is a better candidate to estimate the SOC.

关键词： state of charge lithium-ion battery parameters identification finite difference algorithm extended kalman filter

Time-domain identification of dynamic properties of layered soil by using extended kalman filter and recorded seismic data

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Earthquake Engineering and Engineering Vibration 2004年第2期3卷 237-247页

作者：郑亦斌王满生刘荷姚英周锡元 University of Virginia CharlottesvilleVA 22904-4743USA Assistant Professor Institute of Geophysics China Earthquake AdministrationBeijing 100036China Graduate Student University of Alaska Anchorage.USA Associate Professor University of Virginia CharlottesvilleVA 22904-4743USA Researcher Beijing University of Technology Beijing 100083 China Professor

A novel time-domain identification technique is developed for the seismic response analysis of soil-structure interaction.A two-degree-of-freedom (2DOF) model with eight lumped parameters is adopted to model the frequency- dependent behavior of *** layered soil,the equivalent eight parameters of the 2DOF model are identified by the extended kalman filter (EKF) method using recorded seismic *** polynomial approximations for derivation of state estimators are applied in the EKF procedure.A realistic identification example is given for the layered-soil of a building site in Anchorage,Alaska in the United *** of the example demonstrate the feasibility and practicality of the proposed identification *** 2DOF soil model and the identification technique can be used for nonlinear response analysis of soil-structure interaction in the time-domain for layered or complex soil *** identified parameters can be stored in a database tor use in other similar soil conditions,lfa universal database that covers information related to most soil conditions is developed in the thture,engineers could conveniently perform time history analyses of soil-structural interaction.

关键词： soil-structure interaction identification extended kalman filter 2DOF model equivalent lumped parameters polynomial approximation seismic data

FPGA Implementation of extended kalman filter for Parameters Estimation of Railway Wheelset

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Computers, Materials & Continua 2023年第2期74卷 3351-3370页

作者： Khakoo Mal Tayab Din Memon Imtiaz Hussain Kalwar Bhawani Shankar Chowdhry Department of Electronic Engineering Mehran University of Engineering&TechnologyJamshoro76062Pakistan Sukkur IBA University Sukkur65200Pakistan Design and Creative Technology Torrens University Australia196 Flinders StreetMelbourne3000VICAustralia Department of Electronics and Power Engineering Pakistan Navy Engineering College NUSTKarachi75350Pakistan NCRA-Condition Monitoring Systems Lab Mehran University of Engineering&TechnologyJamshoro76062Pakistan

It is necessary to know the status of adhesion conditions between wheel and rail for efficient accelerating and decelerating of railroad *** proper estimation of adhesion conditions and their real-time implementation is considered a challenge for *** this paper,the development of simulation model of extended kalman filter(EKF)in MATLAB/Simulink is presented to estimate various railway wheelset parameters in different contact conditions of *** to concurrent in nature,the Xilinx®System-on-Chip Zynq Field Programmable Gate Array(FPGA)device is chosen to check the onboard estimation ofwheel-rail interaction parameters by using the National Instruments(NI)myRIO®development *** NImyRIO®development board is flexible to deal with nonlinearities,uncertain changes,and fastchanging dynamics in real-time occurring in wheel-rail contact conditions during vehicle *** simulated dataset of the railway nonlinear wheelsetmodel is tested on FPGA-based EKF with different track conditions and with accelerating and decelerating operations of the *** proposed model-based estimation of railway wheelset parameters is synthesized on FPGA and its simulation is carried out for functional verification on *** obtained simulation results are aligned with the simulation results obtained through *** the best of our knowledge,this is the first time study that presents the implementation of a model-based estimation of railway wheelset parameters on FPGA and its functional *** functional behavior of the FPGA-based estimator shows that these results are the addition of current knowledge in the field of the railway.

关键词： Adhesion force extended kalman filter FPGA implementation railway wheelset real-time estimation wheel-rail interaction

Kernel Entropy Based extended kalman filter for GPS Navigation Processing

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Computers, Materials & Continua 2021年第7期68卷 857-876页

作者： Dah-Jing Jwo Jui-Tao Lee Department of Communications Navigation and Control EngineeringTaiwan Ocean UniversityKeelung202301Taiwan

This paper investigates the kernel entropy based extended kalman filter(EKF)as the navigation processor for the Global Navigation Satellite Systems(GNSS),such as the Global Positioning System(GPS).The algorithm is effective for dealing with non-Gaussian errors or heavy-tailed(or impulsive)interference errors,such as the *** kernel minimum error entropy(MEE)and maximum correntropy criterion(MCC)based filtering for satellite navigation system is involved for dealing with non-Gaussian errors or heavy-tailed interference errors or outliers of the *** standard EKF method is derived based on minimization of mean square error(MSE)and is optimal only under Gaussian assumption in case the system models are precisely *** GPS navigation algorithm based on kernel entropy related principles,including the MEE criterion and the MCC will be performed,which is utilized not only for the time-varying adaptation but the outlier type of interference *** kernel entropy based design is a new approach using information from higher-order signal *** information theoretic learning(ITL),the entropy principle based measure uses information from higher-order signal statistics and captures more statistical information as compared to *** improve the performance under non-Gaussian environments,the proposed filter which adopts the MEE/MCC as the optimization criterion instead of using the minimum mean square error(MMSE)is utilized for mitigation of the heavy-tailed type of multipath *** assessment will be carried out to show the effectiveness of the proposed approach for positioning improvement in GPS navigation processing.

关键词： GPS satellite navigation extended kalman filter entropy correntropy multipath non-Gaussian

Limit behaviors of extended kalman filter as a parameter estimator for a sinusoidal signal

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Control Theory and Technology 2018年第3期16卷 203-211页

作者： Li XIE State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing 102206 China

In this note, the basic limit behaviors of the solution to Riccati equation in the extended kalman filter as a parameter estimator for a sinusoidal signal are analytically investigated by using lira sup and lim inf in... 详细信息

关键词： extended kalman filter parameter estimator sinusoidal signal covariance matrix limit behavior

Estimation of Quaternion Motion for GPS-Based Attitude Determination Using the extended kalman filter

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Computers, Materials & Continua 2021年第2期66卷 2105-2126页

作者： Dah-Jing Jwo Department of Communications Navigation and Control EngineeringTaiwan Ocean UniversityKeelung202-24Taiwan

In this paper,the Global Positioning System(GPS)interferometer provides the preliminarily computed quaternions,which are then employed as the measurement of the extended kalman filter(EKF)for the attitude determination *** estimated quaternion elements from the EKF output with noticeably improved precision can be converted to the Euler angles for navigation *** aim of the study is ***,the GPS-based computed quaternion vector is utilized to avoid the singularity ***,the quaternion estimator based on the EKF is adopted to improve the estimation *** of the unknown baseline vector between the antennas sits at the heart of GPS-based attitude *** utilization of the carrier phase observables enables the relative positioning to achieve centimeter level accuracy,however,the quaternion elements derived from the GPS interferometer are inherently *** is due to the fact that the baseline vectors estimated by the least-squares method are based on the raw double-differenced *** of the transformation matrix is accessible according to the estimate of baseline vectors and thereafter the computed quaternion elements can be *** the Euler angle method,the process becomes meaningless when the angles are at 90where the singularity problem occurs.A good alternative is the quaternion approach,which possesses advantages over the equivalent Euler angle based transformation since they apply to all *** results on the attitude estimation performance based on the proposed method will be presented and compared to the conventional *** results presented in this paper elucidate the superiority of proposed algorithm.

关键词： Global positioning system(GPS) quaternion extended kalman filter attitude determination

Dynamic Optimization of Feedforward Automatic Gauge Control Based on extended kalman filter

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Journal of Iron and Steel Research International 2008年第2期15卷 39-42页

作者： YANG Bin-hu YANG Wei-dong CHEN Lian-gui QU Lei School of Information Engineering University of Science and Technology Beijing Beijing 100083 China

Automatic gauge control is an essentially nonlinear process varying with time delay,and stochastically varying input and process noise always influence the target gauge control *** improve the control capability of feedforward automatic gauge control,kalman filter was employed to filter the noise signal transferred from one stand to *** linearized matrix that the kalman filter algorithm needed was concluded;thus,the feedforward automatic gauge control architecture was dynamically *** theoretical analyses and simulation show that the proposed algorithm is reasonable and effective.

关键词： automatic gauge control feedforward control extended kalman filter

Decision-Aided extended kalman filter Based Adaptive Timing Recovery for Wavelet Packet Modulated Signals

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Tsinghua Science and Technology 2010年第3期15卷 329-334页

作者：孙懿郝久玉 School of Electronic Information Engineering Tianjin University

One of the major issues with multi-carrier systems is their vulnerability to timing synchronization errors resulting in the loss of time synchronization which causes loss of orientation of incoming data at the receiver. This paper presents an acquisition algorithm to timing recovery using the decision-aided extended kalman filtering （EKF） technique for nonlinear disturbance channels in a wavelet packet transform-based multicarrier modulation communication system. This timing recovery algorithm gives faster convergence, smaller root mean square （RMS） errors, and better bit error rate （BER） performance than traditional timing recovery methods, such as the phase-locked loop （PLL）, maximum likelihood （ML）, and kalman filter （KF） methods. Thus, the algorithm is able to handle larger timing errors more reliably and to provide better timing recovery, since the scheme takes into account the nonlinear relationship between the signal samples and timing errors. Simulations for various time-varying channels show that the timing recovery algorithm works well for wavelet packet transform-based multicarrier modulation communication systems.

关键词： wavelet packet transform multi-carrier modulation adaptive timing recovery extended kalman filter

Notes on Convergence and Modeling for the extended kalman filter

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Computers, Materials & Continua 2023年第11期77卷 2137-2155页

作者： Dah-Jing Jwo Department of Communications Navigation and Control EngineeringTaiwan Ocean UniversityKeelung202301TaiwanChina

The goal of this work is to provide an understanding of estimation technology for both linear and nonlinear dynamical systems.A critical analysis of both the kalman filter(KF)and the extended kalman filter(EKF)will be provided,along with examples to illustrate some important issues related to filtering convergence due to system modeling.A conceptual explanation of the topic with illustrative examples provided in the paper can help the readers capture the essential principles and avoid making mistakes while implementing the *** fictitious process noise to the system model assumed by the filter designers for convergence assurance is being investigated.A comparison of estimation accuracy with linear and nonlinear measurements is *** identification by the state estimation method through the augmentation of the state vector is also *** intended readers of this article may include researchers,working engineers,or engineering *** article can serve as a better understanding of the topic as well as a further connection to probability,stochastic process,and system *** lesson learned enables the readers to interpret the theory and algorithms appropriately and precisely implement the computer codes that nicely match the estimation algorithms related to the mathematical *** is especially helpful for those readers with less experience or background in optimal estimation theory,as it provides a solid foundation for further study on the theory and applications of the topic.

关键词： kalman filter extended kalman filter convergence modeling optimization