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Accuracy comparison and improvement for state of health estimation of lithium-ion battery based on random partial recharges and feature engineering

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Journal of Energy Chemistry 2024年第5期92卷 591-604页

作者： Xingjun Li dan Yu søren Byg Vilsen daniel Ioan stroe Department of Energy Aalborg UniversityAalborg 9220Denmark Department of Mathematical sciences Aalborg UniversityAalborg 9220Denmark Walker Department of Mechanical Engineering The University of Texas at AustinAustinTX 78712USA

state of health(sOH)estimation of e-mobilities operated in real and dynamic conditions is essential and *** of existing estimations are based on a fixed constant current charging and discharging aging profiles,which overlooked the fact that the charging and discharging profiles are random and not complete in real *** work investigates the influence of feature engineering on the accuracy of different machine learning(ML)-based sOH estimations acting on different recharging sub-profiles where a realistic battery mission profile is *** features were extracted from the battery partial recharging profiles,considering different factors such as starting voltage values,charge amount,and charging sliding ***,features were selected based on a feature selection pipeline consisting of filtering and supervised ML-based subset *** linear regression(MLR),Gaussian process regression(GPR),and support vector regression(sVR)were applied to estimate sOH,and root mean square error(RMsE)was used to evaluate and compare the estimation *** results showed that the feature selection pipeline can improve sOH estimation accuracy by 55.05%,2.57%,and 2.82%for MLR,GPR and sVR *** was demonstrated that the estimation based on partial charging profiles with lower starting voltage,large charge,and large sliding window size is more likely to achieve higher *** work hopes to give some insights into the supervised ML-based feature engineering acting on random partial recharges on sOH estimation performance and tries to fill the gap of effective sOH estimation between theoretical study and real dynamic application.

关键词： Feature engineering Dynamic forklift aging profile state of health comparison Machine learning Lithium-ion batteries

Non-Deterministic Liveness-Enforcing supervisor Tolerant to sensor-Reading Modification Attacks

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IEEE/CAA Journal of Automatica sinica 2024年第1期11卷 240-248页

作者： dan You shouguang Wang IEEE the school of Information and Electronic Engineering Sussex Artificial Intelligence InstituteZhejiang Gongshang UniversityHangzhou 310018China

In this paper, we study the supervisory control problem of discrete event systems assuming that cyber-attacks might occur. In particular, we focus on the problem of liveness enforcement and consider a sensor-reading modification attack(sM-attack) that may disguise the occurrence of an event as that of another event by intruding sensor communication channels. To solve the problem, we introduce non-deterministic supervisors in the paper, which associate to every observed sequence a set of possible control actions offline and choose a control action from the set randomly online to control the system. specifically, given a bounded Petri net(PN) as the reference formalism and an sMattack, an algorithm that synthesizes a liveness-enforcing nondeterministic supervisor tolerant to the sM-attack is proposed for the first time.

关键词： Cyber-attacks cyber-physical system(CPs) liveness non-deterministic supervisors Petri net(PN)

Neural dynamics for improving optimiser in deep learning with noise considered

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 722-737页

作者： dan su Predrag s.stanimirović Ling Bo Han Long Jin school of Information science and Engineering Lanzhou UniversityLanzhouChina Faculty of sciences and Mathematics University of NišNišSerbia school of Electronics and Information Engineering Guangdong Ocean UniversityZhanjiangChina

As deep learning evolves,neural network structures become increasingly sophisticated,bringing a series of new optimisation *** example,deep neural networks(DNNs)are vulnerable to a variety of *** neural networks under privacy constraints is a method to alleviate privacy leakage,and one way to do this is to add noise to the ***,the existing optimisers suffer from weak convergence in the presence of increased noise during training,which leads to a low robustness of the *** stabilise and improve the convergence of DNNs,the authors propose a neural dynamics(ND)optimiser,which is inspired by the zeroing neural dynamics originated from zeroing neural *** authors first analyse the relationship be-tween DNNs and control ***,the authors construct the ND optimiser to update network ***,the proposed ND optimiser alleviates the non-convergence problem that may be suffered by adding noise to the gradient from different ***,experiments are conducted on different neural network structures,including ResNet18,ResNet34,Inception-v3,MobileNet,and long and short-term memory *** results using CIFAR,YouTube Faces,and R8 datasets demonstrate that the ND optimiser improves the accuracy and stability of DNNs under noise-free and noise-polluted *** source code is publicly available at https://***/LongJin-lab/ND.

关键词： deep learning deep neural networks

On the Factors Influencing the High stretch-Flangeability of a Low-Density 1180 MPa Fe-Mn-Al-C-Nbδ-QP steel

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Acta Metallurgica sinica(English Letters) 2024年第8期37卷 1291-1300页

作者： dan‑dan Cui Peng Chen Peng‑Fei Wang Xiao‑Wu Li Department of Materials Physics and Chemistry School of Materials Science and Engineeringand Key Laboratory for Anisotropy and Texture of Materials(Ministry of Education)Northeastern UniversityShenyang 110819China state Key Laboratory of Rolling and Automation Northeastern UniversityShenyang 110819China

Low-densityδ-quenching and partitioning(δ-QP)steels with excellent strength and ductility have been recently ***,there are still rare reports on the formability of δ-QP steels,which are critical for satisfying the manufacture of structural parts during the application in automotive *** the present work,an 1180 MPa Fe–Mn–Al–C–Nbδ-QP steel with a high ductility was adopted for the stretch–flangeability ***δ-QP steel was developed by separated quenching and partitioning processes.A good hole expansion ratio(HER)of 34.9±0.9%was obtained in the quenched steel,but it has been further increased to 52.2%by the tempering *** improved stretch–flangeability was attributed to the enhanced austenite stability and deformation *** the one hand,the stability of austenite was increased by carbon partitioning during tempering,which reduced crack possibility via the suppression of the fresh martensite *** the other hand,the tempering treatment released the internal stress caused by martensitic transformation and reduced the difference in strength among different phases,resulting in an increase in the resistance to crack initiation and propagation.

关键词： Hole expansion ratio Low-densityδ-quenching and partitioning(δ-QP)steel stretch-flangeability Austenite stability Deformation uniformity

Variational quantum algorithms for scanning the complex spectrum of non-Hermitian systems

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Frontiers of physics 2024年第4期19卷 275-285页

作者： Xu-dan Xie Zheng-Yuan Xue dan-Bo Zhang Key Laboratory of Atomic and subatomic structure and Quantum Control(Ministry of Education) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matterand School of PhysicsSouth China Normal UniversityGuangzhou 510006China Guangdong Provincial Key Laboratory of Quantum Engineering and Quantum Materials Guangdong–Hong Kong Joint Laboratory of Quantum Matterand Frontier Research Institute for PhysicsSouth China Normal UniversityGuangzhou 510006China

solving non-Hermitian quantum many-body systems on a quantum computer by minimizing the variational energy is challenging as the energy can be ***,we propose a variational quantum algorithm for solving the non-Hermitian Hamiltonian by minimizing a type of energy variance,where zero variance can naturally determine the eigenvalues and the associated left and right ***,the energy is set as a parameter in the cost function and can be tuned to scan the whole spectrum efficiently by using a two-step optimization *** numerical simulations,we demonstrate the algorithm for preparing the left and right eigenstates,verifying the biorthogonal relations,as well as evaluating the *** also investigate the impact of quantum noise on our algorithm and show that its performance can be largely improved using error mitigation ***,our work suggests an avenue for solving non-Hermitian quantum many-body systems with variational quantum algorithms on near-term noisy quantum computers.

关键词： quantum algorithm non-Hermitian physics quantum manybody systems

Challenges and Opportunities in Preserving Key structural Features of 3D-Printed Metal/Covalent Organic Framework

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Nano-Micro Letters 2024年第8期16卷 362-381页

作者： Ximeng Liu dan Zhao John Wang Department of Materials science and Engineering National University of SingaporeSingapore 117574Singapore Department of Chemical and Biomolecular Engineering National University of SingaporeSingapore 117585Singapore National University of singapore(Chongqing)Research Institute Chongqing 401123People’s Republic of China

Metal-organic framework(MOF)and covalent organic framework(COF)are a huge group of advanced porous materials exhibiting attractive and tunable microstructural features,such as large surface area,tunable pore size,and functional surfaces,which have significant values in various application *** emerging 3D printing technology further provides MOF and COFs(M/COFs)with higher designability of their macrostructure and demonstrates large achievements in their performance by shaping them into advanced 3D ***,the currently available 3D printing M/COFs strategy faces a major challenge of severe destruction of M/COFs’microstructural features,both during and after 3D *** is envisioned that preserving the microstructure of M/COFs in the 3D-printed monolith will bring a great improvement to the related *** this overview,the 3D-printed M/COFs are categorized into M/COF-mixed monoliths and M/COF-covered *** differences in the properties,applications,and current research states are *** up-to-date advancements in paste/scaffold composition and printing/covering methods to preserve the superior M/COF microstructure during 3D printing are further discussed for the two types of 3D-printed M/*** the analysis of the current states of 3D-printed M/COFs,the expected future research direction to achieve a highly preserved microstructure in the 3D monolith is proposed.

关键词： Metal-organic frameworks Covalent organic frameworks 3D printing Microstructure Monolith

A credible traffic prediction method based on self-supervised causal discovery

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science China(Information sciences) 2024年第5期67卷 244-258页

作者： dan WANG Yingjie LIU Bin sONG state Key Laboratory of Integrated services Networks Xidian University

Next-generation wireless network aims to support low-latency, high-speed data transmission services by incorporating artificial intelligence(AI) technologies. To fulfill this promise, AI-based network traffic prediction is essential for pre-allocating resources, such as bandwidth and computing power. This can help reduce network congestion and improve the quality of service(Qos) for users. Most studies achieve future traffic prediction by exploiting deep learning and reinforcement learning, to mine spatio-temporal correlated variables. Nevertheless, the prediction results obtained only by the spatio-temporal correlated variables cannot reflect real traffic changes. This phenomenon prevents the true prediction variables from being inferred, making the prediction algorithm perform poorly. Inspired by causal science, we propose a novel network traffic prediction method based on self-supervised spatio-temporal causal discovery(ssTCD). We first introduce the Granger causal discovery algorithm to build a causal graph among prediction variables and obtain spatio-temporal causality in the observed data, which reflects the real reasons affecting traffic ***, a graph neural network(GNN) is adopted to incorporate causality for traffic prediction. Furthermore,we propose a self-supervised method to implement causal discovery to to address the challenge of lacking ground-truth causal graphs in the observed data. Experimental results demonstrate the effectiveness of the ssTCD method.

关键词： wireless network traffic prediction causal discovery self-supervised

Recent Advance in synaptic Plasticity Modulation Techniques for Neuromorphic Applications

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Nano-Micro Letters 2024年第10期16卷 403-434页

作者： Yilin sun Huaipeng Wang dan Xie school of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100081People's Republic of China school of Integrated Circuits Beijing National Research Center for Information Science and Technology(BNRist)Tsinghua UniversityBeijing 100084People's Republic of China

Manipulating the expression of synaptic plasticity of neuromorphic devices provides fascinating opportunities to develop hardware platforms for artifi-cial ***,great efforts have been devoted to exploring biomimetic mechanisms of plasticity simulation in the last few *** progress in various plasticity modulation techniques has pushed the research of synaptic electronics from static plasticity simulation to dynamic plasticity modulation,improving the accuracy of neuromorphic computing and providing strategies for implementing neuromorphic sensing ***,several fascinating strategies for synap-tic plasticity modulation through chemical techniques,device structure design,and physical signal sensing are *** chemical techniques,the underly-ing mechanisms for the modification of functional materials were clarified and its effect on the expression of synaptic plasticity was also *** on device structure design,the reconfigurable operation of neuromorphic devices was well demonstrated to achieve programmable neuromorphic ***,integrating the sensory units with neuromorphic processing circuits paved a new way to achieve human-like intelligent perception under the modulation of physical signals such as light,strain,and ***,considering that the relevant technology is still in the basic exploration stage,some prospects or development suggestions are put forward to promote the development of neuromorphic devices.

关键词： Plasticity modulation Dynamic plasticity Chemical techniques Programmable operation Neuromorphic sensing

The First Five Years of a Phase Theory for Complex systems and Networks

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IEEE/CAA Journal of Automatica sinica 2024年第8期11卷 1728-1743页

作者： dan Wang Wei Chen Li Qiu Division of Decision and Control systems KTH Royal Institute of TechnologyStockholm 10044Sweden Department of Mechanics and Engineering science&the state Key Laboratory for Turbulence and Complex systems Peking UniversityBeijing 100871China Hong Kong University of science and Technology Hong KongChinaand also with the Southern University of Science and TechnologyShenzhen 518055China

In this paper,we review the development of a phase theory for systems and networks in its first five years,represented by a trilogy:Matrix phases and their properties;The MIMO LTI system phase response,its physical interpretations,the small phase theorem,and the sectored real lemma;The synchronization of a multi-agent network using phase *** the end,we also summarize a list of ongoing research on the phase theory and speculate what will happen in the next five years.

关键词： Consensus and synchronization matrix phases multi-agent systems phase theory sectored real lemma small phase theorem.