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An Online Adaptive Internal Short Circuit Detection Method of Lithium-Ion Battery

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Automotive Innovation 2021年第1期4卷 93-102页

作者： Jian Hu Zhongbao Wei Hongwen He National Engineering Laboratory of Electric Vehicles School of Mechanical EngineeringBeijing Institute of Technology5 ZhongGuanCun South StreetHaidian DistrictBeijing 100181China

Internal short circuit(ISC)is a critical cause for the dangerous thermal runaway of lithium-ion battery(LIB);thus,the accurate early-stage detection of the ISC failure is critical to improving the safety of electric *** this paper,a model-based and self-diagnostic method for online ISC detection of LIB is proposed using the measured load current and terminal *** equivalent circuit model is built to describe the characteristics of ISC cell.A discrete-time regression model is formulated for the faulty cell model through the system transfer function,based on which the electrical model parameters are adapted online to keep the model ***,an online ISC detection method is exploited by incorporating an extended Kalman filter-based state of charge estimator,an abnormal charge depletion-based ISC current estimator,and an ISC resistance estimator based on the recursive least squares method with variant forgetting *** proposed method shows a self-diagnostic merit relying on the single-cell measurements,which makes it free from the extra uncertainty caused by other cells in the *** results suggest that the online parameterized model can accurately predict the voltage dynamics of *** proposed diagnostic method can accurately identify the ISC resistance online,thereby contributing to the early-stage detection of ISC fault in the LIB.

关键词： Lithium-ion battery Internal short circuit recursive least squares Extended Kalman filter

Prediction of Time Series Empowered with a Novel SREKRLS Algorithm

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Computers, Materials & Continua 2021年第5期67卷 1413-1427页

作者： Bilal Shoaib Yasir Javed Muhammad Adnan Khan Fahad Ahmad Rizwan Majeed Muhammad Saqib Nawaz Muhammad Adeel Ashraf Abid Iqbal Muhammad Idrees School of Computer Science Minhaj University LahoreLahore54000Pakistan Prince Sultan University Riyadh11586Saudi Arabia Department of Computer Science Riphah International University Lahore CampusLahore54000Pakistan Department of Basic Sciences Deanship of Common First YearJouf UniversitySakakaAljouf72341Saudi Arabia Directorate of IT The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Computer Science University of Management and TechnologyLahore54770Pakistan PUCIT University of the PunjabLahore54000Pakistan

For the unforced dynamical non-linear state–space model,a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this *** proposed algorithm lends itself towards the parallel implementation as in the FPGA *** the help of an ortho-normal triangularization method,which relies on numerically stable givens rotation,matrix inversion causes a computational burden,is *** computation possesses many excellent numerical properties such as singularity,symmetry,skew symmetry,and triangularity is achieved by using this *** proposed method is validated for the prediction of stationary and non-stationary Mackey–Glass Time Series,along with that a component in the x-direction of the Lorenz Times Series is also predicted to illustrate its *** the learning curves regarding mean square error(MSE)are witnessed for demonstration with prediction performance of the proposed algorithm from where it’s concluded that the proposed algorithm performs better than *** new SREKRLS based design positively offers an innovative era towards non-linear systolic arrays,which is efficient in developing very-large-scale integration(VLSI)applications with non-linear input *** experiments are carried out to validate the reliability,effectiveness,and applicability of the proposed algorithm and with different noise levels compared to the Extended kernel recursive least-squares(EKRLS)algorithm.

关键词： Kernel methods square root adaptive filtering givens rotation mackey glass time series prediction recursive least squares kernel recursive least squares extended kernel recursive least squares square root extended kernel recursive least squares algorithm

Approach to estimation of vehicle-road longitudinal friction coefficient

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Journal of Southeast University(English Edition) 2013年第3期29卷 310-315页

作者：宋翔李旭张为公陈伟徐启敏东南大学仪器科学与工程学院南京210096

According to the road adaptive requirements for the vehicle longitudinal safety assistant system an estimation method of the road longitudinal friction coefficient is *** method can simultaneously be applied to both the high and the low slip ratio conditions. Based on the simplified magic formula tire model the road longitudinal friction coefficient is preliminarily estimated by the recursive least squares *** estimated friction coefficient and the tires model parameters are considered as extended states. The extended Kalman filter algorithm is employed to filter out the noise and adaptively adjust the tire model parameters. Then the final road longitudinal friction coefficient is accurately and robustly estimated. The Carsim simulation results show that the proposed method is better than the conventional algorithm. The road longitudinal friction coefficient can be quickly and accurately estimated under both the high and the low slip ratio *** error is less than 0.1 and the response time is less than 2 s which meets the requirements of the vehicle longitudinal safety assistant system.

关键词： road friction coefficient recursive least squares extended Kalman filter vehicle longitudinal safety assistantsystem

Application of Fast and Robust Equalization in Communication Technology

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High Technology Letters 2003年第4期9卷 74-77页

作者：叶桦 Zhou Wanlei Ye Lin Lanham Elicia Raitman Ruth School of Information Technology Deakin University 221 Burwood HWY BurwoodAustralia School of Adults Education Harbin Institute of TechnologyHarbin 150001P.R.China

In this paper, the authors explore the potential of several popular equalization techniques while overcoming their disadvantages. First, extensive literature survey on equalization is conducted. The focus is on popular linear equalization algorithms such as the conventional least mean square (LMS ) algorithm, the recursive least squares ( RLS ) algorithm, the filtered X LMS algorithm and their development. To overcome the slow convergence problem while keeping the simplicity of the LMS based algorithms, an H 2 optimal initialization is proposed.

关键词： least mean square discrete cosine transform recursive least squares filtered X LMS H 2

Bus mass estimation algorithm based on kinetic energy theorem

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Journal of Measurement Science and Instrumentation 2015年第2期6卷 103-110页

作者：张文娟秦静谢辉马红杰黄登高天津大学内燃机燃烧学国家重点实验室天津300072

Bus mass is an important factor that affects fuel consumption and one of the key input parameters associated with automatic shift and hybrid electric vehicle （HEV） energy management strategy. A city bus mass estimation method based on kinetic energy theorem was proposed in this paper. The real-time data including vehicle speed and engine torque were collected by a remote data acquisition system. The samples in the process of being accelerated were selected to conduct vehicle mass estimation at the same bus stop with the same gear. The average estimation error is 2. 92% after the verification by actual data. Compared with the method based on recursive least squares, the algorithm based on kinetic energy theorem requires less sample length and the estimation error is smaller. Therefore, the method is more suitable for the bus mass estimation. The influences of gear, rolling resistance coefficient, wind resistance coefficient and road slope on mass estimation accuracy were analyzed.

关键词： bus mass kinetic energy theorem recursive least squares

RLS and LMS blind adaptive multi-user detection method and comparison in acoustic communication

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Instrumentation 2015年第2期2卷 47-54页

作者： WANG Zhongqiu WANG Hongru MENG Qingming Shandong Provincial Key Laboratory of Ocean Environment Monitoring Technology Institute of Oceanographic Instrumentation Shandong Academy of Science

RLS and LMS blind adaptive multi-user detection algorithm and multi-user detector was proposed to solve the problem of multi-user signal detection problem encountered in underwater acoustic communication *** simulation analysis,RLS and the LMS blind adaptive multi-user detector were designed and tested for synchronous and asynchronous multi-user communication *** results of SIR comparison and MMSE comparison show that,both of the two methods can realize blind adaptive detection when any user change in multi-user communication,during this process,the training communication sequences are not *** RLS algorithm has about 5 dB higher in SIR compared with LMS algorithm,and the convergence velocity of RLS algorithm is also higher than LMS algorithm when the communication users *** algorithm has better ability in multi-user detection than that of LMS algorithm,and it has great attraction and guiding significance for solving the problem of multiple access interference(MAI) in multi-user communication.

关键词： recursive least squares least mean square method multi-user detection blind adaptive acoustic communication

Updating Methods for Real Time Flood Forecasting： A Comparison through Senegal River Basin Upstream Bakel

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Journal of Environmental Science and Engineering(A) 2012年第1期1卷 58-72页

作者： Soussou Sambou Seni Tamba Clement Diatta Cheikh Mohamed Fadel Kebe Department of Physics Faculty of Science and TechnicsThe University of Cheikh Anta DIOPDakar 99000Senegal Department of Civil Engineering The Polytechnical School of ThibsDakar 99004Senegal The Polytechnical High School Dakar 99000Senegal

Heavy floods occur frequently in the Senegal River Basin, causing catastrophic flooding downstream the river rating station of Bakel. Anticipating the occurrence of such phenomena is the only way to reduce the resulting damages. Flood forecasting is a necessity. Flood forecasting plays also an important role in the implementation of flood management scenarios and in the protection of hydro electric structures. Many methods are applied. The most complete are based on the conservation laws of physics governing the free surface flow. These methods need a complete description of the geometry of the river and their implementation requires also huge investments. In practice the river basin can be considered as a system of inputs-outputs related by a transfer function. In this paper the authors first used a multiple linear regression model with constant parameters estimated by the ordinary least square method to simulate the propagation of the floods in the upstream part of the Senegal river basin. The authors then apply statistical and graphical criteria of goodness-of-fit to test the suitability of this model. Three procedures of parameters updating have then been added to this linear model： the Kalman filter method, the recursive least square method, and the stochastic gradient method The criteria of goodness-of-fit used above have shown that the stochastic gradient method, although more rudimentary, represents better the flood propagation in the head basin of the Senegal river upstream Bakel. This result is particularly interesting because data influenced by Manantali Dam are used.

关键词： Hydrology multiple linear regression models Kalman filtering recursive least squares stochastic gradient floodforecasting Senegal river head basin.

Research of internet worm warning system based on system identification

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控制理论与应用（英文版） 2006年第4期4卷 409-412页

作者： Tao ZHOU Guanzhong DAI Huimin YE College of Automatic Control Northwestern Polytechnical University Xi＇an Shaanxi 710072 China

The frequent explosion of Internet worms has been one of the most serious problems in cyberspace security. In this paper, by analyzing the worm＇s propagation model, we propose a new worm warning system based on the method of system identification, and use recursive least squares algorithm to estimate the worm＇s infection rate. The simulation result shows the method we adopted is an efficient way to conduct Internet worm warning.

关键词： Cyberspace security Internet worm System identification recursive least squares

Parameter identification to an approximated function of the Weierstrass approximation formula

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Parameter identification to an approximated function of the ...