Multi-time scale identification of key kinetic processes for lithium-ion batteries considering variable characteristic frequency

The electrification of vehicles puts forward higher requirements for the power management efficiency of integrated battery management systems as the primary or sole energy supply.In this paper,an efficient adaptive multi-time scale identification strategy is proposed to achieve high-fidelity modeling of complex kinetic processes inside the battery.More specifically,a second-order equivalent circuit model network considering variable characteristic frequency is constructed based on the high-frequency,medium-high-frequency,and low-frequency characteristics of the key kinetic processes.Then,two coupled sub-filters are developed based on forgetting factor recursive least squares and extended Kalman filtering methods and decoupled by the corresponding time-scale information.The coupled iterative calculation of the two sub-filter modules at different time scales is realized by the voltage response of the kinetic diffusion process.In addition,the driver of the low-frequency subalgorithm with the state of charge variation amount as the kernel is designed to realize the adaptive identification of the kinetic diffusion process parameters.Finally,the concept of dynamical parameter entropy is introduced and advocated to verify the physical meaning of the kinetic parameters.The experimental results under three operating conditions show that the mean absolute error and root-mean-square error metrics of the proposed strategy for voltage tracking can be limited to 13 and 16 mV,respectively.Additionally,from the entropy calculation results,the proposed method can reduce the dispersion of parameter identification results by a maximum of 40.72%and 70.05%,respectively,compared with the traditional fixed characteristic frequency algorithms.The proposed method paves the way for the subsequent development of adaptive state estimators and efficient embedded applications.

Distributed Cooperative Learning for Discrete-Time Strict-Feedback Multi Agent Systems Over Directed Graphs

This paper focuses on the distributed cooperative learning(DCL)problem for a class of discrete-time strict-feedback multi-agent systems under directed graphs.Compared with the previous DCL works based on undirected graphs,two main challenges lie in that the Laplacian matrix of directed graphs is nonsymmetric,and the derived weight error systems exist n-step delays.Two novel lemmas are developed in this paper to show the exponential convergence for two kinds of linear time-varying(LTV)systems with different phenomena including the nonsymmetric Laplacian matrix and time delays.Subsequently,an adaptive neural network(NN)control scheme is proposed by establishing a directed communication graph along with n-step delays weight updating law.Then,by using two novel lemmas on the extended exponential convergence of LTV systems,estimated NN weights of all agents are verified to exponentially converge to small neighbourhoods of their common optimal values if directed communication graphs are strongly connected and balanced.The stored NN weights are reused to structure learning controllers for the improved control performance of similar control tasks by the“mod”function and proper time series.A simulation comparison is shown to demonstrate the validity of the proposed DCL method.

Self-supporting and dual-active 3D Co-S nanosheets constructed by ligand replacement reaction from MOF for rechargeable Al battery

Metal sulfides with high theoretical capacities are expected as promising cathode materials of Al batteries(AIBs). However, powdery active materials are mainly synthesized and loaded on current collector by insulating binder without capacity. Meanwhile, S as inert element in metal sulfides can not usually provide capacity. So, powdery metal sulfides only exhibit limiting practical capacity and poor cycling stability due to weak conductivity and low mass utilization. Herein, the novel self-supporting and dual-active Co-S nanosheets on carbon cloth (i.e. Co-S/CC) with hierarchically porous structure are constructed as cathode of AIBs. Co-S nanosheets are derived from ZIF-67 nanosheets on CC by a facile ligand replacement reaction. As a result, the binder-free Co-S/CC cathode with good conductivity delivers excellent initial discharge capacity of 383.4 m Ah g^(-1)(0.211 m Ah cm^(-2)) at current density of 200 m A g^(-1)and maintain reversible capacity of 156.9 m Ah g^(-1)(0.086 m Ah cm^(-2)) with Coulombic efficiency of 95.8% after 500 cycles,which are much higher than those of the traditional slurry-coating cathodes. Both Co and S as active elements in Co-S/CC contribute to capacity, which leads to a high mass utilization. This work provides a significant strategy for the construction of self-supporting metallic cathode for advanced high-energy density Al battery.

On-chip stimulated Brillouin scattering[Invited]

On-chip stimulated Brillouin scattering(SBS)has attracted extensive attention by introducing acousto-optic coupling interactions in all-optical signal processing systems.A series of chip-level applications such as Brillouin lasers,amplifiers,gyroscopes,filters,and nonreciprocal devices are realized based on Brillouin acousto-optic interaction.Here,we first introduce the fundamental principle of SBS in integrated photonics and a method for calculating Brillouin gain;then we illustrate the Brillouin effect on different material platforms with diverse applications.Finally,we make a concise conclusion and offer prospects on the future developments of on-chip SBS.

A pre-generated matrix-based method for real-time robotic drilling chatter monitoring

Currently, due to the detrimental effects on surface finish and machining system, chatter has been one crucial factor restricting robotic drilling operations, which improve both quality and efficiency of aviation manufacturing. Based on the matrix notch filter and fast wavelet packet decomposition, this paper presents a novel pre-generated matrix-based real-time chatter monitoring method for robotic drilling. Taking vibration characteristics of robotic drilling into account, the matrix notch filter is designed to eliminate the interference of spindle-related components on the measured vibration signal. Then, the fast wavelet packet decomposition is presented to decompose the filtered signal into several equidistant frequency bands, and the energy of each sub-band is obtained. Finally, the energy entropy which characterizes inhomogeneity of energy distribution is utilized as the feature to recognize chatter on-line, and the effectiveness of the presented algorithm is validated by extensive experimental data. The results show that the proposed algorithm can effectively detect chatter before it is fully developed. Moreover, since both filtering and decomposition of signal are implemented by the pre-generated matrices, calculation for an energy entropy of vibration signal with 512 samples takes only about 0.690 ms. Consequently, the proposed method achieves real-time chatter monitoring for robotic drilling, which is essential for subsequent chatter suppression.

Plasmon resonant amplification of a hot electron-driven photodiode

We report plasmon resonant excitation of hot electrons in a photodetector based on a metal/oxide/metal （Au/Al2O3/graphene） heterostructure. In this device, hot electrons, excited optically in the gold layer, jump over the oxide barrier and are injected into the graphene layer, producing a photocurrent. To amplify this process, the bottom gold electrode is patterned into a plasmon resonant grating structure with a pitch of 500 nm. The photocurrent produced in this device is measured using 633-nm-wavelength light as a function of incident angle. We observe the maximum photocurrent at ＋10° from normal incidence under irradiation with light polarized parallel to the incident plane （p-polarization） and perpendicular to the lines on the grating, and a constant （angle-independent） photocurrent under irradiation with light polarized perpendicular to the incident plane （s-polarization） and parallel to the grating. These data show an amplification factor of 4.6× under resonant conditions. At the same angle （±10°）, we also observe sharp dips in the photoreflectance corresponding to wavevector matching between the incident light and the plasmon mode in the grating. In addition, finite-difference time-domain simulations predict sharp dips in the photoreflectance at ±10°, and the electric field intensity profiles show clear excitation of a plasmon resonant mode when illuminated with p-polarized light at this angle.