A comparative study of data-driven battery capacity estimation based on partial charging curves

With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.

Performance analysis of deep borehole heat exchangers for decarbonization of heating systems

Meeting the climate change mitigation targets will require a substantial shift from fossil to clean fuels in the heating sector.Heat pumps with deep borehole exchangers are a promising solution to reduce emissions.Here the thermal behavior of deep borehole exchangers(DBHEs)ranging from 1 to 2 km was analyzed for various heat flow profiles.A strong correlation between thermal energy extraction and power output from DBHEs was found,also influenced by the heating profile employed.Longer operating time over the year typically resulted in higher energy production,while shorter one yielded higher average thermal power output,highlighting the importance of the choice of heating strategy and system design for optimal performance of DBHEs.Short breaks in operation for regenerating the borehole,for example,with waste heat,proved to be favorable for the performance yielding an overall heat output close to the same as with continuous extraction of heat.The results demonstrate the usefulness of deep boreholes for dense urban areas with less available space.As the heat production from a single DBHE in Finnish conditions ranges from half up to even a few GWh a year,the technology is best suitable for larger heat loads.

IR-YOLO: Real-Time Infrared Vehicle and Pedestrian Detection

Road traffic safety can decrease when drivers drive in a low-visibility environment.The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents.To tackle the challenges posed by the low recognition accuracy and the substan-tial computational burden associated with current infrared pedestrian-vehicle detection methods,an infrared pedestrian-vehicle detection method A proposal is presented,based on an enhanced version of You Only Look Once version 5(YOLOv5).First,A head specifically designed for detecting small targets has been integrated into the model to make full use of shallow feature information to enhance the accuracy in detecting small targets.Second,the Focal Generalized Intersection over Union(GIoU)is employed as an alternative to the original loss function to address issues related to target overlap and category imbalance.Third,the distribution shift convolution optimization feature extraction operator is used to alleviate the computational burden of the model without significantly compromising detection accuracy.The test results of the improved algorithm show that its average accuracy(mAP)reaches 90.1%.Specifically,the Giga Floating Point Operations Per second(GFLOPs)of the improved algorithm is only 9.1.In contrast,the improved algorithms outperformed the other algorithms on similar GFLOPs,such as YOLOv6n(11.9),YOLOv8n(8.7),YOLOv7t(13.2)and YOLOv5s(16.0).The mAPs that are 4.4%,3%,3.5%,and 1.7%greater than those of these algorithms show that the improved algorithm achieves higher accuracy in target detection tasks under similar computational resource overhead.On the other hand,compared with other algorithms such as YOLOv8l(91.1%),YOLOv6l(89.5%),YOLOv7(90.8%),and YOLOv3(90.1%),the improved algorithm needs only 5.5%,2.3%,8.6%,and 2.3%,respectively,of the GFLOPs.The improved algorithm has shown significant advancements in balancing accuracy and computational efficiency,making it promising for practical use in resource-limited scenarios.

Application of Electrical Automation Technology in Power System

With the continuous development and progress of science and technology in China, automation technology has occupied an important position in many fields while its application in power system is increasingly widespread. Therefore, the application of electrical automation technology in power system is of great significance for power supply stability and work efficiency. In this paper, the author analyzes the application of electric automation technology in power system and makes contributions to the sustainable and stable development of power enterprises.

Comparative Study of the Types of Photovoltaic Panels Used in Solar Pumping Systems in Dry Tropical Zones: Case of Adamawa Region in Cameroon

In the dry tropical zone where access to water is increasingly difficult for populations, solar pumping units are increasingly installed to provide water to population. In the local market, there are essentially two types of solar panels, namely monocrystalline and polycrystalline. However, the part of the local market is more dominated by the polycrystalline panel. In this work, comparative studies are carried out in order to characterize the two types of solar panels with regard to local constraints. Tests were carried out over the course of the sun to establish the performance of each type. The panels used have the same electrical characteristics and are connected to loads with same characteristics. Under the set operating conditions, the monocrystalline panel presents more performance than the polycrystalline panel. Although the local market is dominated by the polycrystalline panel, dust deposition tests on the surface of the panels show that the performance of the polycrystalline panel is more affected compared to the performance of the monocrystalline panel.

6-DOF MOTION AND CENTER OF ROTATION ESTIMATION BASED ON STEREO VISION

A new motion model and estimation algorithm is proposed to compute the general rigid motion object＇s 6-DOF motion parameters and center of rotation based on stereo vision. The object＇s 6-DOF motion model is designed from the rigid object＇s motion character under the two defined reference frames. According to the rigid object＇s motion model and motion dynamics knowledge, the corresponding motion algorithm to compute the 6-DOF motion parameters is worked out. By the rigid object pure rotation motion model and space sphere geometry knowledge, the center of rotation may be calculated after eliminating the translation motion out of the 6-DOF motion. The motion equations are educed based on the motion model and the closed-form solutions are figured out. To heighten the motion estimation algorithm＇s robust, RANSAC algorithm is applied to delete the outliers. Simulation and real experiments are conducted and the experiment results are analyzed. The results prove the motion model＇s correction and algorithm＇s validity.

ANALYSIS OF CIRCUIT TOLERANCE BASED ON RANDOM SET THEORY

Monte Carlo Analysis has been an accepted method for circuit tolerance analysis, but the heavy computational complexity has always prevented its applications. Based on random set theory, this paper presents a simple and flexible tolerance analysis method to estimate circuit yield. It is the alternative to Monte Carlo analysis, but reduces the number of calculations dramatically.

P-Indeterminate Vector Similarity Measures of Orthopair Neutrosophic Number Sets and Their Decision-MakingMethod with Indeterminate Degrees

In the complexity and indeterminacy of decision making(DM)environments,orthopair neutrosophic number set(ONNS)presented by Ye et al.can be described by the truth and falsity indeterminacy degrees.Then,ONNS demonstrates its advantages in the indeterminate information expression,aggregations,and DM problems with some indeterminate ranges.However,the existing research lacks some similarity measures between ONNSs.They are indispensable mathematical tools and play a crucial role in DM,pattern recognition,and clustering analysis.Thus,it is necessary to propose some similaritymeasures betweenONNSs to supplement the gap.To solve the issue,this study firstly proposes the p-indeterminate cosine measure,p-indeterminate Dice measure,p-indeterminate Jaccard measure of ONNSs(i.e.,the three parameterized indeterminate vector similarity measures of ONNSs)in vector space.Then,a DMmethod based on the parameterized indeterminate vector similarity measures of ONNSs is developed to solve indeterminate multiple attribute DM problems by choosing different indeterminate degrees of the parameter p,such as the small indeterminate degree(p=0)or the moderate indeterminate degree(p=0.5)or the big indeterminate degree(p=1).Lastly,an actual DM example on choosing a suitable logistics supplier is provided to demonstrate the flexibility and practicability of the developed DM approach in indeterminate DM problems.By comparison with existing relative DM methods,the superiority of this study is that the established DMapproach indicates its flexibility and suitability depending on decision makers’indeterminate degrees(decision risks)in ONNS setting.

Band offsets and electronic properties of the Ga_(2)O_(3)/FTO heterojunction via transfer of free-standing Ga_(2)O_(3) onto FTO/glass

The determination of band offsets is crucial in the optimization of Ga_(2)O_(3)-based devices,since the band alignment types could determine the operations of devices due to the restriction of carrier transport across the heterogeneous interfaces.In this work,the band offsets of the Ga_(2)O_(3)/FTO heterojunction are studied using x-ray photoelectron spectroscopy(XPS)based on Kraut’s method,which suggests a staggered type-II alignment with a conduction band offset(DEC)of 1.66 eV and a valence band offset(DEV)of2.41 eV.Furthermore,the electronic properties of the Ga_(2)O_(3)/FTO heterostructure are also measured,both in the dark and under ultraviolet(UV)illuminated conditions(254 nm UV light).Overall,this work can provide meaningful guidance for the design and construction of oxide hetero-structured devices based on wide-bandgap semiconducting Ga_(2)O_(3).

Power Quality Issues Concerning Photovoltaic Generation and Electrical Vehicle Loads in Distribution Grids

The high utilization level of renewable generation including residential photovoltaic (PV) systems together with the uncontrolled charging of electric vehicles (EVs) can have a significant impact on load characteristics in distribution networks. Harmonic content of PV generation, EV charging loads, and their influence on power quality indicators in residential distribution networks are discussed in this paper. For investigating likely power quality scenarios, PV generation and EV charging measurement results including current harmonic amplitude and phase angle values are used and compared with present load characteristics. Different modelling scenarios are analysed and a simplified model of harmonics in PVs and EVs is offered. The results of the study show moderate additional harmonic distortion in residential load current and voltage distortion at the substation’s busbar when PV generation and EV loading are added. The scenarios presented in this paper can be further used for modelling the actual harmonic loads of the PVs and EVs in distribution networks.

Revealing the role of electrode potential micro-environments in single Mn atoms for carbon dioxide and oxygen electrolysis

Elucidation the relationship between electrode potentials and heterogeneous electrocatalytic reactions has attracted widespread attention.Herein we construct the well-defined Mn single-atom(MnSA)catalyst with four N-coordination through a simple thermal pyrolysis preparation method to investigate the electrode potential micro-environments effect on carbon dioxide reduction reactions(CO_(2)RR)and oxygen reduction reactions(ORR).MnSA catalysts generate higher CO production Faradaic efficiency of exceeding 90%at-0.9 V for CO_(2)RR and higher H_(2)O_(2)yield from 0.1 to 0.6 V with excellent ORR activity.Density functional theory(DFT)calculations based on constant potential models were performed to study the mechanism of MnSA on CO_(2)RR.The thermodynamic energy barrier of CO_(2)RR is lowest at-0.9 V vs.reversible hydrogen electrode(RHE).Similar DFT calculations on the H_(2)O_(2)yield of ORR showed that the H_(2)O_(2)yield at 0.2 V was higher.This study provides a reasonable explanation for the role of electrode potential micro-environments.

Characteristic Model-based Discrete-time Sliding Mode Control for Spacecraft with Variable Tilt of Flexible Structures

In this paper, the finite-time attitude tracking control problem for the spacecrafts with variable tilt of flexible appendages in the conditions of exogenous disturbances and inertia uncertainties is addressed. First the characteristic modeling method is applied to the problem of the spacecraft modeling. Second, a novel adaptive sliding mode surface is designed based on the characteristic model. Furthermore, a discrete-time sliding mode control (DTSMC) law, which makes the tracking error converge into a predefined bound in finite time, is proposed by employing the parameters of characteristic model associated with the sliding mode surface to provide better performances, robustness, faster response, and higher control precision. The designed DTSMC includes the adaptive control architecture and is chattering-free. Finally, digital simulations of a sun synchronous orbit satellite (SSOS) are presented to illustrate effectiveness of the control strategies as well as to verify the practical feasibility of the rapid maneuver mission. © 2014 Chinese Association of Automation.

Digitalization of mine operations:Scenarios to benefit in real-time truck dispatching

One of the key factors in a profitable open-pit mine is the efficiency of the waste disposal system. Using GPS-technology, the truck-dispatching decisions can be made in real-time but the chosen strategy has a crucial role. Therefore, finding the optimal dispatching strategy for truck-shovel operations is extremely important. Dispatching strategies have been reported in the literature, but the comparison of these strategies is still missing. This paper illustrates the differences between the strategies by conducting a stochastic simulation study based on the data gathered from an actual mine. The findings underline the importance of the global vision in dispatching decisions.

Research on Reliability of Relaying Protection in Smart Substation

Research on reliability of relaying protection in smart substation not only has a positive effect on the rational configuration scheme of relaying protection in smart substation, but also can promote the stability and safety of the overall operation of power system. There are many reliability strategies for relaying protection in smart substation. In practice, the key points of relaying protection should be clarified. Based on the reality, the protection configuration should be strengthened;the voltage limited delay should be used for protection, and the protection configuration scheme of actual lines should be paid attention to, so as to improve the reliability of relaying protection in smart substation and promote the realization of stable and sustainable development of power system and smart substation.

Delay-dependent static output feedback control of nonlinear system

The static output feedback control problem for time-delay nonlinear system is studied based on T-S fuzzy bilinear model. The objective is to design a delay-dependent static output feed- back controller via the parallel distributed compensation （ PDC ） approach such that the closed-loop system is delay-dependent asymptotically stable. A sufficient condition for the existence of such a controller is derived via the linear matrix inequality （LMI） approach and the design problem of the fuzzy controller is formulated as an LMI problem. The simulation examples show the effectiveness of the proposed approach.

Acoustic wireless communication based on parameter modulation and complex Lorenz chaotic systems with complex parameters and parametric attractors

As the competition for marine resources is increasingly fierce,the security of underwater acoustic communication has attracted a great deal of attention.The information and location of the communicating platform can be leaked during the traditional underwater acoustic communication technology.According to the unique advantages of chaos communication,we put forward a novel communication scheme using complex parameter modulation and the complex Lorenz system.Firstly,we design a feedback controller and parameter update laws in a complex-variable form with rigorous mathematical proofs(while many previous references on the real-variable form were only special cases in which the imaginary part was zero),which can be realized in practical engineering;then we design a new communication scheme employing parameter modulation.The main parameter spaces of the complex Lorenz system are discussed,then they are adopted in our communication scheme.We also find that there exist parametric attractors in the complex Lorenz system.We make numerical simulations in two channels for digital signals and the simulations verify our conclusions.

Progress in Analysis of Key Technologies for Dynamic Wireless Charging of Electric Vehicles

At present, electric vehicles are very common means of transportation in our life. Contact charging is the main method of electric vehicles in China. With the continuous improvement of people’s awareness of environmental protection, wireless charging technology is also under constant development. Currently, there are more static wireless charging technologies, while dynamic charging mode is only a perfection and supplement to it, which is crucial to the promotion of electric vehicles and is able to make charging work faster and easier. China has been researching dynamic wireless charging technology, but it has been affected by many factors. Therefore, it is necessary for the relevant personnel to solve the existing obstacles according to the characteristics of dynamic wireless charging technology and apply dynamic wireless charging technology in an efficient manner.

Overview of Analysis on State Evaluation of Relaying Protection System

With the rapid development of the smart grid, it is necessary to do good corresponding work in relaying protection so as to meet the overall requirements of the smart grid better. So we must focus on the state division, risk analysis and fault diagnosis methods in the relaying protection system, in the basis of fully understanding the advantages and disadvantages of relaying protection system, and then improve the problems existing of relaying protection system at this stage according to the actual situation. This paper aims at the overview of analysis on state evaluation of relaying protection systems.

Intelligent Agent-Based Architecture for Demand Side Management Considering Space Heating and Electric Vehicle Load

Contraction of resilience on generation side due to the introduction of inflexible renewable energy sources is demanding more elasticity on consumption side. It requires more intelligent systems to be implemented to maintain power balance in the grid and to fulfill the consumer needs. This paper is concerned about the energy balance management of the system using intelligent agent-based architecture. The idea is to limit the peak power of each individual household for different defined time regions of the day according to power production during those time regions. Monte Carlo Simulation (MCS) has been employed to study the behavior of a particular number of households for maintaining the power balance based on proposed technique to limit the peak power for each household and even individual load level. Flexibility of two major loads i.e. heating load (heat storage tank) and electric vehicle load (battery) allows us to shift the peaks on demand side proportionally with the generation in real time. Different parameters related to heating and Electric Vehicle (EV) load e.g. State of Charge (SOC), storage capacities, charging power, daily usage, peak demand hours have been studied and a technique is proposed to mitigate the imbalance of power intelligently.

Impacts of Opinion Propagation on Social Balance

In social networks, opinions diffusion often leads to relationships evolution. Then changes of relationships result in the change of balance degree of social system. We simulate the opinion diffusion on Barabasi & Albert (BA) network and Watts & Strogatz (WS) network to study the effects of the two types of networks, dynamical parameters and structural parameters on the balance degree of system. We employ the spectral analysis to quantify the balance degree of system before and after opinion propagation. The result reveals that it is very similar effect of BA networks and WS networks on it. However, it is opposite effects between dynamical parameters and structural parameters. The balance degree of system is proportional to the two dynamical factors (P,Q) at initial state and always inversely proportional to the two structural factors (,Pne) at initial and convergence state.