Deep Learning Hybrid Model for Lithium-Ion Battery Aging Estimation and Prediction

The degradation process of lithium-ion batteries is intricately linked to their entire lifecycle as power sources and energy storage devices,encompassing aspects such as performance delivery and cycling utilization.Consequently,the accurate and expedient estimation or prediction of the aging state of lithium-ion batteries has garnered extensive attention.Nonetheless,prevailing research predominantly concentrates on either aging estimation or prediction,neglecting the dynamic fusion of both facets.This paper proposes a hybrid model for capacity aging estimation and prediction based on deep learning,wherein salient features highly pertinent to aging are extracted from charge and discharge relaxation processes.By amalgamating historical capacity decay data,the model dynamically furnishes estimations of the present capacity and forecasts of future capacity for lithium-ion batteries.Our approach is validated against a novel dataset involving charge and discharge cycles at varying rates.Specifically,under a charging condition of 0.25 C,a mean absolute percentage error(MAPE)of 0.29%is achieved.This outcome underscores the model's adeptness in harnessing relaxation processes commonly encountered in the real world and synergizing with historical capacity records within battery management systems(BMS),thereby affording estimations and prognostications of capacity decline with heightened precision.

State of health prediction for lithium-ion batteries based on ensemble Gaussian process regression

The performance of lithium-ion batteries(LIBs)gradually declines over time,making it critical to predict the battery’s state of health(SOH)in real-time.This paper presents a model that incorporates health indicators and ensemble Gaussian process regression(EGPR)to predict the SOH of LIBs.Firstly,the degradation process of an LIB is analyzed through indirect health indicators(HIs)derived from voltage and temperature during discharge.Next,the parameters in the EGPR model are optimized using the gannet optimization algorithm(GOA),and the EGPR is employed to estimate the SOH of LIBs.Finally,the proposed model is tested under various experimental scenarios and compared with other machine learning models.The effectiveness of EGPR model is demonstrated using the National Aeronautics and Space Administration(NASA)LIB.The root mean square error(RMSE)is maintained within 0.20%,and the mean absolute error(MAE)is below 0.16%,illustrating the proposed approach’s excellent predictive accuracy and wide applicability.

Remaining useful life estimation based on Wiener degradation processes with random failure threshold

Remaining useful life(RUL) estimation based on condition monitoring data is central to condition based maintenance(CBM). In the current methods about the Wiener process based RUL estimation, the randomness of the failure threshold has not been studied thoroughly. In this work, by using the truncated normal distribution to model random failure threshold(RFT), an analytical and closed-form RUL distribution based on the current observed data was derived considering the posterior distribution of the drift parameter. Then, the Bayesian method was used to update the prior estimation of failure threshold. To solve the uncertainty of the censored in situ data of failure threshold, the expectation maximization(EM) algorithm is used to calculate the posteriori estimation of failure threshold. Numerical examples show that considering the randomness of the failure threshold and updating the prior information of RFT could improve the accuracy of real time RUL estimation.

Fault Diagnosis in Chemical Process Based on Self-organizing Map Integrated with Fisher Discriminant Analysis

Fault diagnosis and monitoring are very important for complex chemical process. There are numerous methods that have been studied in this field, in which the effective visualization method is still challenging. In order to get a better visualization effect, a novel fault diagnosis method which combines self-organizing map (SOM) with Fisher discriminant analysis (FDA) is proposed. FDA can reduce the dimension of the data in terms of maximizing the separability of the classes. After feature extraction by FDA, SOM can distinguish the different states on the output map clearly and it can also be employed to monitor abnormal states. Tennessee Eastman (TE) process is employed to illustrate the fault diagnosis and monitoring performance of the proposed method. The result shows that the SOM integrated with FDA method is efficient and capable for real-time monitoring and fault diagnosis in complex chemical process.

SPC在键合工艺中的应用

键合工艺是集成电路中芯片功能引出到管壳引脚的桥梁,键合质量的好坏直接影响电路的功能和可靠性,所以键合工艺处在可控状态下,对于保证键合质量尤为重要。SPC是一种先进的控制方式,应用于键合工艺,解决了传统键合控制的弊端,CPK以数据形式直接反应键合质量,均值极差图预测键合工艺是否存在问题,并及时纠正解决,使键合工艺处在时时可控状态下。

Statistical damage model for quasi-brittle materials under uniaxial tension

Based on the parallel bar system, combining with the synergetic method, the catastrophe theory and the acoustic emission test, a new motivated statistical damage model for quasi-brittle solid was developed. Taking concrete for instances, the rationality and the flexibility of this model and its parameters-determining method were identified by the comparative analyses between theoretical and experimental curves. The results show that the model can simulate the whole damage and fracture process in the fracture process zone of material when the materials arc exposed to quasi-static uniaxial tensile traction. The influence of the mesoscopic damage mechanism on the macroscopic mechanical properties of quasi-brittle materials is summarized into two aspects, rupture damage and yield damage. The whole damage course is divided into the statistical even damage phase and the local breach phase, corresponding to the two stages described by the catastrophe theory. The two characteristic states, the peak nominal stress state and the critical state are distinguished, and the critical state plays a key role during the whole damage evolution course.

Controlled Telecloning and Teleflipping for One-Qubit Pure States

We propose a scheme for realizing controlled 1→2 telecloning and 1 →1 teleflipping for one-qubit pure states via a quantum network including N agents. The quantum operations used in the information-transmission process are just only one Bell-state measurement, and a series of single-qubit operation. It is shown that the fidelities of the controlled telecloning and teleflipping are independent of the initial states and reach their optimal values of 5/6 and 2/3 respectively on the condition that all the agents collaborate. If any one agent does not cooperate, the fidelities become state-dependent and are always smaller than the corresponding optimal values. The average fidelities are equal to the balanced value 1/2, which implies that on average the state ineepted by any one of the receivers is a fuUy mixed state. Thus no information leaks out to any dishonest receivers. The security of telecloning and teleflipping have been increased greatly.

高三物理复习审题规范性思维训练探讨

对高三物理复习审题规范性思维训练进行探讨,以两个例子来做比较详细地讲解,如何按照审题的四个步骤＂明对象、画简图、析过程（状态）、找关键条件＂进行审题的方法。

A Real-time Updated Model Predictive Control Strategy for Batch Processes Based on State Estimation

Nonlinear model predictive control(NMPC) is an appealing control technique for improving the performance of batch processes, but its implementation in industry is not always possible due to its heavy on-line computation. To facilitate the implementation of NMPC in batch processes, we propose a real-time updated model predictive control method based on state estimation. The method includes two strategies: a multiple model building strategy and a real-time model updated strategy. The multiple model building strategy is to produce a series of sim-plified models to reduce the on-line computational complexity of NMPC. The real-time model updated strategy is to update the simplified models to keep the accuracy of the models describing dynamic process behavior. The me-thod is validated with a typical batch reactor. Simulation studies show that the new method is efficient and robust with respect to model mismatch and changes in process parameters.

Study on law of raw coal seepage during loading process at different gas pressures

In order to reveal the law of raw coal seepage at different gas pressures, the gravity constant load seepage experimental system was developed and used. The law of raw coal seepage at different gas pressures with He, N2 and CO2 was investigated. The results show that, in a given state of stress during the experiment, with the increase of gas pressure, the permeability of raw coal sample prone to outburst exhibits a significantly decrease, and then exhibits an increasing trend when reaching the extreme point. The law of Klingberg coefficient related to the stress state and the gas adsorption properties was also obtained. Under the same experimental conditions, the Klingberg coefficient of He is greater than that of N2; and the Klingberg coefficient of CO2 has minimum value; so the stronger the gas adsorption is, the smaller the Klingberg coefficient of gas goes. Klinkenberg coefficient decreases with the increase of effective stress. Under the same conditions, the permeability of He is greater than that of N2; the permeability of CO2 has minimum value; so the stronger the gas adsorption is, the lower the permeability of the coal sample goes. The results have important significance in revealing the mechanism of gas seenage. Dredicting coal mine gas disaster, and gas drainage and safety nroduction.

Effect of meridional wind on gap-leaping western boundary current

Using a 1.5-layer reduced-gravity nonlinear shallow-water equation model, we studied the effect of the meridional wind on the western boundary currents (WBC) at critical states with hysteresis courses. The results of the simulation indicate that the WBC is prone to penetrating into the gap under northerly winds, and its path is more difficult to alter due to the larger interval between the two critical transition curves (C1P and C1L). For southerly winds, the WBC is prone to leaping across the gap, and its path is easier to alter due to the smaller interval between the two critical transition curves. The simulation results also indicate that the meridional winds over the southern region of the gap are the dominant factor determining the formation of the WBC. The dynamic mechanism influencing the transport of WBC near the gap is both Ekman transport and the blocking of Ekman transport. Ekman transport induced by northerly winds may reduce the transport of the WBC, causing the β-effect to dominate the meridional advection (promoting the penetration). Southerly winds, however, may enhance the transport of the WBC, causing the meridional advection to dominate the β-effect (promoting the leaping state). These results explain some structural features of the Kuroshio at the Luzon Strait.

On-line Estimation in Fed-batch Fermentation Process Using State Space Model and Unscented Kalman Filter

On-line estimation of unmeasurable biological variables is important in fermentation processes,directly influencing the optimal control performance of the fermentation system as well as the quality and yield of the targeted product.In this study,a novel strategy for state estimation of fed-batch fermentation process is proposed.By combining a simple and reliable mechanistic dynamic model with the sample-based regressive measurement model,a state space model is developed.An improved algorithm,swarm energy conservation particle swarm optimization(SECPSO) ,is presented for the parameter identification in the mechanistic model,and the support vector machines(SVM) method is adopted to establish the nonlinear measurement model.The unscented Kalman filter(UKF) is designed for the state space model to reduce the disturbances of the noises in the fermentation process.The proposed on-line estimation method is demonstrated by the simulation experiments of a penicillin fed-batch fermentation process.

Flexible Analytics for Management of Grid Assets

This paper presents a case study about a condition monitoring project for asset management implementing an advanced decision process for maintenance and asset replacement in the Qatar electricity distribution network. It describes the principles used to produce an assessment of the health of the entire fleet of assets, together with the concepts retained to prioritize the interventions on the distribution network equipment. The paper goes through the actual steps taken for the preparation and execution mode of the overall project. It covers the following project phases： definition of the problem ＆ business objectives, process definition and preparation tasks, presentation of solutions and execution phase. The project being still in the implementation phase, the conclusions are preliminary but already demonstrate concrete and tangible benefits.

The feature on the posterior conditional probability of finite state Markov channel

The feature of finite state Markov channel probability distribution is discussed on condition that original I/O are known. The probability is called posterior condition probability. It is also proved by Bayes formula that posterior condition probability forms stationary Markov sequence if channel input is independently and identically distributed. On the contrary, Markov property of posterior condition probability isn’t kept if the input isn’t independently and identically distributed and a numerical example is utilized to explain this case. The properties of posterior condition probability will aid the study of the numerical calculated recurrence formula of finite state Markov channel capacity.

Single Server Queueing Models and Birth-Death Process

A transition diagram is used to describe the behavior of systems. Birth-death equations were derived from transition diagram depicting the state of the birth-death processes. Queue models and characteristics of queue models are also derivable from birth-death processes. These queue models consist of mathematical formulas and relationships that can be used to determine the operating characteristics （performance measures） for a waiting line. Schematic and transition diagrams of different single server queue models were shown. Relationships between birth-death processes, waiting lines （queues） and transition diagrams were given. While M/M/I/K queue model states was limited by K customers and had （K＋I） states, M/M/1/1 queue model had only two states. M/G/1/∝/∝ and M/M/1/∝/∝ shared similar characteristics. Many ideal queuing situations employ M/M/1 queueing model.

Unscented Transformation Based Robust Kalman Filter and Its Applications in Fermentation Process

State estimation is the precondition and foundation of a bioprocess monitoring and optimal control. However,there are many difficulties in dealing with a non-linear system,such as the instability of process, un-modeled dynamics,parameter sensitivity,etc.This paper discusses the principles and characteristics of three different approaches,extended Kalman filters,strong tracking filters and unscented transformation based Kalman filters.By introducing the unscented transformation method and a sub-optimal fading factor to correct the prediction error covariance,an improved Kalman filter,unscented transformation based robust Kalman filter,is proposed. The performance of the algorithm is compared with the strong tracking filter and unscented transformation based Kalman filter and illustrated in a typical case study for glutathione fermentation process.The results show that the proposed algorithm presents better accuracy and stability on the state estimation in numerical calculations.

A Note on Black Hole Information Paradox in de Sitter Spacetimes

The possibility of stable or quasi-stable Planck mass black hole remnants as solution to the black hole information paradox is commonly believed phenomenologically unacceptable. Since we need a black hole remnant for every possible initial state, the number of remnants is expected to be infinite and that would lead to remnant pair production in any physical process with a total available energy roughly exceeding the Planck mass. In this note I point out that a positive cosmological constant of the Universe would naturally lead to an upper bound on the number of possible remnants.

Waste Plastic Conversion into Hydrocarbon Fuel Materials

The increased demand and high price for energy sources are driving efforts to convert organic compounds into useful hydrocarbon fuels. Although much of this work has focused on biomass, there are strong benefits to deriving fuels from waste plastic material. Natural State Research Inc. （NSR） has invented a simple and economically viable process to decompose the hydrocarbon polymers of waste plastic into the shorter chain hydrocarbon of liquid fuel （patent pending）. The method and principle of the production/process will be discussed. Initial tests with several widely used polymers indicate a high potential for commercialization.

A navigation method based on POMDP for smart wheelchair in uncertain environments

A navigation method based on the partially observable markov decision process （POMDP） for smart wheelchairs in uncertain environments is presented in this paper. The design key factors for the navigation system of a smart wheelchair are discussed. A kinematics model of the smart wheelchair is given, and the model and principle of POMDP are introduced. In order to respond in uncertain local environments, a novel navigation methodology based on POMDP using the sensors perception and the user＇s joystick input is presented. The state space, the action set, the observations and the sensor fusion of the navigation method are given in detail, and the optimal policy of the POMDP model is proposed. Experimental results demonstrate the feasibility of this navigation method. Analysis is also conducted to investigate performance evaluation, advantages of the approach and potential generalization of this paper.

Asymptotic Bifurcation Solutions for Perturbed Kuramoto-Sivashinsky Equation

Stability and dynamic bifurcation in the perturbed Kuramoto-Sivashinsky （KS） equation with Dirichlet boundary condition are investigated by using central manifold reduction procedure. The result shows, as the bifurcation parameter crosses a critical value, the system undergoes a pitchfork bifurcation to produce two asymptotically stable solutions. Furthermore, when the distance from bifurcation is of comparable order ε2 （｜ε｜≤1）, the first two terms in e-expansions for the new asymptotic bifurcation solutions are derived by multiscale expansion method. Such information is useful to the bifurcation control.