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A Joint Estimation Method of SOC and SOH for Lithium-ion Battery Considering Cyber-Attacks Based on GA-BP

Computers, Materials & Continua 2024年第9期80卷 4497-4512页

作者： Tianqing Yuan Na Li Hao Sun Sen Tan Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Department of Electrical Engineering Northeast Electric Power UniversityJilin132012China College of Information and Control Engineering Jilin Institute of Chemical TechnologyJilin132022China Center for Research on Microgrids Department of EnergyAalborg UniversityAalborg9220Denmark

To improve the estimation accuracy of state of charge(SOC)and state of health(SOH)for lithium-ion batteries,in this paper,a joint estimation method of SOC and SOH at charging cut-off voltage based on genetic algorithm(GA)combined with back propagation(BP)neural network is proposed,the research addresses the issue of data manipulation resulting ***,anomalous data stemming fromcyber-attacks are identified and eliminated using the isolated forest algorithm,followed by data ***,the incremental capacity(IC)curve is derived fromthe restored data using theKalman filtering algorithm,with the peak of the ICcurve(ICP)and its corresponding voltage serving as the health factor(HF).Thirdly,the GA-BP neural network is applied to map the relationship between HF,constant current charging time,and SOH,facilitating the estimation of SOH based on ***,SOC estimation at the charging cut-off voltage is calculated by inputting the SOH estimation value into the trained model to determine the constant current charging time,and by updating the maximum available *** show that the root mean squared error of the joint estimation results does not exceed 1%,which proves that the proposed method can estimate the SOC and SOH accurately and stably even in the presence of false data injection attacks.

关键词： Lithium-ion batteries state of charge state of health cyber-attacks genetic algorithm back propagation neural network

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Knowledge and data jointly driven aeroengine gas path performance assessment method

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Chinese Journal of Aeronautics 2024年第5期37卷 533-557页

作者： Zhe WANG Xuyun FU Rui ZHANG Zhengfeng BAI Xiangzhao XIA Wei JIANG Department of Mechanical Engineering Harbin Institute of TechnologyWeihai 264209China Weihai Key Laboratory of Intelligent Operation and Maintenance Harbin Institute of TechnologyWeihai 264209China Control System Design Laboratory AECC ShenYang Engine Research InstituteShenyang 110015China

Aeroengines,as the sole power source for aircraft,play a vital role in ensuring flight *** gas path,which represents the fundamental pathway for airflow within an aeroengine,directly impacts the aeroengine's performance,fuel efficiency,and ***,timely and accurate evaluation of gas path performance is of paramount *** paper proposes a knowledge and data jointly driven aeroengine gas path performance assessment method,combining Fingerprint and gas path parameter deviation ***,Fingerprint is used to correct gas path parameter deviation values,eliminating parameter shifts caused by non-component performance ***,coarse errors are removed using the Romanovsky criterion for short-term data divided by an equal-length overlapping sliding ***,an Ensemble Empirical Mode Decomposition and Non-Local Means(EEMD-NLM)filtering method is designed to“clean”data noise,completing the preprocessing for gas path parameter deviation ***,based on the characteristics of gas path parameter deviation values,a Dynamic Temporary Blended Network(DTBN)model is built to extract its temporal features,cascaded with Multi-Layer Perceptron(MLP),and combined with Fingerprint to construct a Dynamic Temporary Blended AutoEncoder(DTB-AutoEncoder).Eventually,by training this improved autoencoder,the aeroengine gas path multi-component performance assessment model is formed,which can sufficiently decouple the nonlinear mapping relationship between aeroengine gas path multi-component performance degradation and gas path parameter deviation values,thereby achieving the performance assessment of engine gas path *** practical application cases,the effectiveness of this model in assessing the aeroengine gas path multi-component performance is verified.

关键词： Performance assessment Aeroengine Fingerprint Gas path parameter deviation values Jointly drive

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Time-Varying Formation Tracking control of Heterogeneous Multi-Agent systems With Intermittent Communications and Directed Switching Networks

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 294-296页

作者： Yuhan Wang Zhuping Wang Hao Zhang Huaicheng Yan the Shanghai Research Institute for Intelligent Autonomous Systems Tongji University the National Key Laboratory of Autonomous Intelligent Unmanned Systems the Frontiers Science Center for Intelligent Autonomous System of Ministry of Education the College of Electronic and Information Engineering the Department of Control Science and Engineering Tongji University the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education the School of Information Science and Engineering East China University of Science and Technology

Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so... 详细信息

关键词： Switches Topology Observers Formation control Event detection Switched systems Multi-agent systems control theory Autonomous systems Stability

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Learning-based MPC of sampled-data systems with partially unknown dynamics

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ISA Transactions 2025年 162卷 64-74页

作者： Han, Seungyong Guo, Xuyang Kommuri, Suneel Kumar Department of Mechanical System Engineering Jeonbuk National University 567 Baekje-daero Deokjin-gu Jeonju54896 Korea Republic of Department of Control Science and Engineering Tongji University Shanghai China Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University Suzhou215123 China

In this paper, a novel learning-based model predictive control (LMPC) method is proposed for sampled-data control systems with partially unknown dynamics. Many real-world processes are subject to time-varying parameters and irregular data sampling, making accurate modeling and stability guarantees extremely challenging. To address this, the proposed method uses a neural ordinary differential equation (NODE) to learn unknown time-varying parameter dynamics from irregularly observed data. This learned model is then integrated into the sampled-data MPC framework. In particular, the LMPC method guarantees the system's ultimate boundedness by deriving conditions based on the Gronwall–Bellman inequality. Finally, two practical examples illustrate the applicability of the LMPC method to real-world systems and demonstrate its quantitative stability analysis. © 2025

关键词： Sampled data control systems

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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Short-Term Photovoltaic Prediction Based on Transfer Learning and LSTM 7

Short-Term Photovoltaic Prediction Based on Transfer Learnin...

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7th IEEE Conference on Energy Internet and Energy system Integration, EI2 2023

作者： Zhang, Tianyu Zheng, Kedi Chen, Qixin Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing China

ISBN: (纸本)9798350345094

With the proposal of carbon peaking and carbon neutrality goals, the proportion of renewable energy generation continues to increase and the number of new photovoltaic power stations is growing rapidly. Accurate photovoltaic power prediction is of great significance for the safe, stable and operation of power system. In order to solve the problem of insufficient historical data of newly constructed PV power plants, this paper proposes a short-term PV power prediction model based on Long Short Term Memory and transfer learning. The model uses meteorological data, numerical weather forecast data and PV power as features. According to the transfer learning theory, the Long Short Term Memory model is pre-trained using the historical data of other previously-built PV power plants, and then a small amount of local operation data is used to fine-adjust the model. Case study based on Hebei open source photovoltaic and meteorological data set proves that the proposed transfer learning model can effectively improve the short-term PV power prediction accuracy, and the MAPE can be improved by up to 15%. © 2023 IEEE.

关键词： Long short-term memory

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Optimal Design of Full-Bridge Three-Level LLC Converter Based on Time-Domain Analysis 2

Optimal Design of Full-Bridge Three-Level LLC Converter Base...

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2nd IEEE International Power Electronics and Application Symposium, PEAS 2023

作者： Liu, Zengyang Sun, Kai Yi, Zheyuan Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing China

ISBN: (纸本)9798350313765

Fully DC wind turbine generator system is a promising substitute for conventional AC one. In the system, the LLC step-up converter plays a key role. Mode analysis and time-domain expressions can provide more accurate estimation of the resonant performance than the conventional First Harmonic Analysis method. The circuit works at different modes as the load rate varies. This paper categorizes these resonant behaviors into four modes, with time-domain expressions of each mode obtained. The variation regular of these modes is given and is applied in the program to realize recognizing the working mode automatically. The simulation and experiment have verified the effectiveness of the proposed method. © 2023 IEEE.

关键词： fully DC wind turbine generator system LLC converter mode analysis Pareto Front optimization time-domain expression

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Effect of Photoionization Mechanism on Numerical Simulation of Transformer Oil Streamer Discharge 19th

Effect of Photoionization Mechanism on Numerical Simulation ...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Liang, Shaobin Zhou, Yuanxiang Chen, Jianning He, Zhiyang Li, Yuhang School of Electrical Engineering Xinjiang University Urumqi China State Key Laboratory of Power System Operation and Control Beijing China Department of Electrical Engineering Tsinghua University Beijing China

ISBN: (纸本)9789819613861

Discharge in transformer oil is one of the primary causes of transformer failures. The physical mechanisms of oil discharges are not yet fully understood. However, the prevailing electrohydrodynamics models primarily adopt field ionization and collision ionization, neglecting photoionization, which could potentially affect the discharge of liquid dielectric streamers. To reveal the discharge characteristics of transformer oil, this paper improves the field ionization term in electrohydrodynamics model, establishes a function of the ionization energy of transformer oil in relation to the recombination strength of carriers, and proposes a simulation model of streamer discharge in oil considering photoionization. The effects of photoionization on the characteristics of streamer discharge in transformer oil are studied, by examining the morphology and propagation velocity of streamers. The results show that the introduction of the photoionization mechanism promotes the formation of streamer branches and makes the energy in the streamer channel more concentrated. Moreover, photoionization facilitates the rapid propagation of streamers, which is key to the formation of the third mode of streamers. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Electrohydrodynamics

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Online Optimization in Power systems With High Penetration of Renewable Generation:Advances and Prospects

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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A control Strategy for Bidirectional Buck Converter with Combining Continuous and Active Discontinuous Conducting Modes 25

A Control Strategy for Bidirectional Buck Converter with Com...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Stolyarov, Evgeniy Lashkevich, Maxim Kulik, Egor Ali, Yousef Demidova, Galina Anuchin, Alecksey Department of Electric Drives Moscow Power Engineering Institute Moscow Russia Faculty of Control System and Robotics ITMO University Saint Petersburg Russia

ISBN: (纸本)9798350389234

The hybrid electric powertrains can utilize bidirectional buck converters to charge the battery while driving and discharge it when extra power is required. In order to increase the power density, the wide-bandgap switches should be used. These switches have bidirectional conductivity mode as they are metal–oxide–semiconductor field-effect transistors (MOSFET) and the utilization of the freewheeling diode is undesirable due to high voltage drop across it and much higher losses in conducting mode. This paper proposes the combined control strategy which implements continuous conducting mode at high and active discontinuous conducting mode at low currents. The use of model predictive control allows to minimize the conducting losses by means of reverse conductivity mode of the switches. The paper provides derivation of the combined control strategy. Then, the simulation results show the effectiveness of the proposed method. Finally, the simulation was performed with various errors in the definition of the system parameters. © 2024 IEEE.

关键词： Buck converter

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