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Research on demagnetization characteristics of eddy current brake under impact load

JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS 2025年 621卷

作者： Liu, Tiantian Li, Lei Wang, Liqun Peng, Peng Wang, Zongfan Yang, Guolai Nanjing Univ Sci & Technol Sch Mech Engn Nanjing 210094 Peoples R China

In this paper, eddy current brake are applied to artillery, and three layouts of it on large-caliber artillery are introduced. A demagnetization model for neodymium iron boron (NdFeB) permanent magnets under impact was proposed based on experimental data and its numerical calculation model is established by joint simulation. A surrogate model for the impact demagnetization model was trained using a Radial Basis Function (RBF) neural network and combined with a particle swarm optimization algorithm to identify the key parameters of the permanent magnet impact demagnetization model. Based on the dynamics of artillery firing, numerical calculation models for electromagnetic forces were developed for different artillery structures, and the electromagnetic forces generated by each structure were calculated. Fine discrete modeling was conducted on the three types of artillery structures, and Abaqus software was utilized to quantitatively calculate the impact demagnetization for each structure. The demagnetization behavior of eddy current brakes under different configurations is analyzed and compared and the reliability of three structural designs is verified. It proposes the addition of a protective cover to Structure II to reduce the area of irreversible demagnetization and validates the feasibility of this approach.

关键词： Eddy current brake Impact demagnetization RBF neural network pso algorithm Finite element

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Allocation of reactive power for parallel hybrid filter based on accurate equalization of DSTATCOM maximum lead and lag currents in network voltage variation

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ELECTRICAL ENGINEERING 2025年 1-12页

作者： Golafshani, Amin Rahimnezhad Changizian, Mahmudreza Shoulaie, Abbas Iran Univ Sci & Technol IUST Dept Elect Engn Heidarkhani St Tehran 16844 Iran Univ Isfahan Dept Railway Engn & Transportat Planning Esfahan Iran

This paper presents a 0.7-MW high-current variable-voltage inductive load that is connected by a 12-pulse thyristor rectifier to the distribution system. In order to compensate at the point of common coupling over the load current range, a parallel hybrid filter (PHF) is used comprising two single-tuned passive filters for 11th and 13th harmonic and a second-order high-pass passive filter for 23th harmonic and DSTATCOM. According to the load reactive power variation, the DSTATCOM is used only to improve the displacement power factor (DPF) while passive filters are incapable of keeping DPF in acceptable values (greater than 0.98). Because of the distribution system voltage variation, it is assumed that voltage varies +/- 5% of the network line voltage. A new comprehensive method is presented for the PHF design with simple equations based on accurate equalization of DSTATCOM maximum lead and lag currents (minimum rating and cost) in the fixed and variable network voltage. This equalization not only reduces the rating of DSTATCOM, but also the total power of passive filters. A network current TDD optimization is according to the pso algorithm carried out with modeling of the system (presenting system equations) and using network harmonics current constraints in pso loops which puts all network current harmonics in acceptable amounts. What's more, harnessing pso algorithm considerably reduces network current TDD in comparison with previous studies. MATLAB simulation results comprising DSTATCOM current and reactive power, network current TDD and harmonics, and other simulation results are presented to verify the better reactive power and harmonic performance of proposed method compared with other method.

关键词： DSTATCOM Parallel hybrid filter Reactive power compensation Current TDD pso algorithm Current constraint

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A numerical optimization scheme for solving systems of fractional-order differential equations

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INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 2025年

作者： Zhou, Fengying Zhang, Jiakun Jiangxi Sci & Technol Normal Univ Sch Math Sci Nanchang 330036 Jiangxi Peoples R China

A numerical optimization scheme is developed by combining particle swarm optimization (pso) algorithm to solve systems of fractional-order differential equations. Firstly, scale-3 fractional Euler wavelets are constructed using orthogonal Euler polynomials. Subsequently, the convergence analysis of scale-3 fractional Euler wavelets expansion is studied and error estimation is acquired through generalized fractional-order Taylor expansion. Following this, the fractional integral formulas in the sense of Riemann-Liouville fractional integral for scale-3 fractional Euler wavelets are derived. Based on these formulas, together with the collocation method, a numerical technique is constructed by discretizing the system of fractional-order differential equations into a system of algebraic equations. Finally, several examples are provided and pso algorithm is employed to further optimize the numerical technique. The numerical results are analysed and compared with existing findings, which not only verify the feasibility and effectiveness of the proposed method but also illustrate that pso algorithm can enhance the numerical technique.

关键词： Scale-3 fractional Euler wavelets system of fractional-order differential equations pso algorithm collocation method numerical solution

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Design and Verification of a Novel Synchronous Force-Increasing Disk Electro-Mechanical Brake Actuator for Pure Electric Trucks

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INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY 2025年 1-18页

作者： Zhang, Zhenwen Yang, Kun Nie, Mengwen Ma, Chao Tan, Di Huang, Zhuangzhuang Shandong Univ Technol Sch Transportat & Vehicle Engn Zibo 255000 Peoples R China Weichai Power Co Ltd Weifang 261043 Peoples R China Shandong Gold Phoenix Co Ltd Leling 253600 Peoples R China

Electro-mechanical brake (EMB) has the characteristics of rapid braking response and precise adjustment for braking torque, it can provide an ideal brake actuator for the uncoupled regenerative braking system of new energy vehicles and active braking system of autonomous driving. Considering the synchronous requirements for braking force variation on both sides of the brake disk and the actuator's volume for pure electric trucks, a novel scheme of the synchronous force-increasing disk EMB (SFD-EMB) actuator is proposed. The relationship between the force-increasing ratio, push displacement and size parameters of the bidirectional eccentric wheel is analyzed. Meanwhile, considering the requirements for compensating the maximum wear of brake linings and the smooth operation, an optimization based on the particle swarm optimization (pso) algorithm is studied. The structural strength for the key components is verified based on the statics analysis. Furthermore, the braking response speed and tracking performance of braking torque for the SFD-EMB actuator is verified by performance testing platform. The results show that the braking response and the torque adjustment performance of the SFD-EMB actuator can meet the requirements of GB12676-2014, and the braking response time can be reduced by 68.8% compared with the specified time.

关键词： Electro-mechanical brake actuator Synchronous force-increasing Bidirectional eccentric wheel pso algorithm Structural analysis Performance verification

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RESEARCH ON HOT SPOT TEMPERATURE INVERSION METHOD OF OIL-IMMERSED TRANSFORMER BASED ON MULTI-PHYSICAL FIELD COUPLING OF MAGNETIC-THERMAL-FLUID

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THERMAL SCIENCE 2025年第1A期29卷 199-213页

作者： Gu, Lingyun Yuan, Fating Zhang, Naiyue Bai, Xuefeng Zhang, Xin Gao, Wenpeng Wu, Yan Bai, Zhixin China Elect Power Res Inst Beijing Key Lab Distribut Transformer Energy Savin Beijing Peoples R China China Three Gorges Univ Coll Elect Engn & New Energy Yichang Peoples R China China Three Gorges Univ Hubei Prov Engn Technol Res Ctr Power Transmission Yichang Peoples R China

The hot spot temperature is an important factor affecting the operation state and insulation life of oil-immersed transformer. It is of great value to carry out multiphysical field coupling simulation research on magnetic-fluid-thermal field of oilimmersed transformer and accurately calculate and predict the hot spot temperature of transformer for transformer service life evaluation. In this paper, the oil immersed transformer is taken as the research object, and five characteristic parameters of the hysteresis model are obtained by using pso algorithm according to the experimental magnetic characteristics data of the core material and the classical Jiles-Atherton (J-A) hysteresis model, A 3-D simulation model of magnetic-fluid-thermal field is established based on the electrical and structural parameters of the oil-immersed transformer. Combined with the magnetic characteristics of the core material, the thermal field and the surrounding fluid distribution of the transformer core and winding are obtained by two-way coupling method. On this basis, in order to accurately reflect the correlation between the hot spot temperature of the transformer winding and the temperature of the oil tank wall, the selection position of the characteristic temperature point of the transformer tank wall is determined by streamline analysis method, and the hot spot temperature of the oil-immersed transformer is retrieved by support vector machine method. The results show that the prediction accuracy of the hot spot temperature reaches 0.998, and the inversion method has a high enough accuracy. It provides theoretical basis and technical support for real-time monitoring of hot spot temperature in oil-immersed transformer windings.

关键词： hot spot temperature pso algorithm support vector machine oil-immersed transformer

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Bifurcation analysis of mixed traffic system with different car-following modes and distributed PID control strategy based on particle swarm optimizer

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CHAOS SOLITONS & FRACTALS 2025年 192卷

作者： Wang, Shu-Tong Zhu, Wen-Xing Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China

This paper is committed to capturing the dynamical behaviors of the mixed traffic flow which is composed of human-driven vehicle (HDV) and connected autonomous vehicle (CAV), and exploring targeted control strategies to alleviate traffic congestion. Firstly, a novel car-following model is proposed for mixed traffic flow, which considers different car-following modes and functional degradation. Secondly, the bifurcation and stability analysis of proposed model are conducted to explore the occurrence of bifurcation in mixed traffic flow under different market penetration rate (MPR) of CAV and car-following mode ratio (CFR) of mixed flow, and numerical simulation is used to validate the conclusions of theoretical analysis. Thirdly, a modified distributed PID controller is proposed to suppress the bifurcation, and the particle swarm optimization (pso) algorithm is used to optimize the control gains of the PID controller. The analysis results of controlled model verify the advantage of the controller, and the numerical simulation also confirms the conclusions. This paper can enrich the research on the characteristics of traffic flow, improve the theoretical basis of traffic control, and provide implications for traffic management.

关键词： Mixed traffic system Traffic dynamics Bifurcation analysis PID control pso algorithm

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Research on variable domain three-point energy management strategy and parameter adaptive optimization for range-extended electric vehicle

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2025年

作者： Liu, Hanwu Lei, Yulong Sun, Wencai Chang, Cheng Jiang, Wei Liu, Yuwei Jilin Univ Transportat Coll 5988 Renmin St Changchun 130022 Jilin Peoples R China Jilin Univ Automot Engn Coll Changchun Jilin Peoples R China Henan Inst Technol Sch Vehicle & Traff Engn Xinxiang Henan Peoples R China

This study proposes a variable domain three-point energy management strategy (VDT-PEMS) for range-extended electric vehicles (R-EEV), which focuses on achieving energy conservation, emission reduction, and battery life extension through the refinement of the auxiliary power unit (APU) variable operation domain and targeted parameter adaptive adjustment. The strategy divides the power interval into variable domain three-point and APU system operates at constant speed and variable torque to achieve effective tracking of the required power. And further designed an adaptive parameter optimization module, which adaptively adjusts the variable domain power coverage of the working area at various speeds based on fuzzy controller, enabling the APU system to more flexibly cope with complex and changing working conditions. And improving the adaptability and stability of the system by refining the variable operating range of APU and implementing targeted parameter adaptive adjustment, dynamic optimization of the working mode strategy has been achieved. Subsequently, the study aimed to solved the multi-objective optimization problem, VDT-PEMS was designed to combines offline optimization based on particle swarm optimization algorithm and online adaptive parameter optimization module. A series of simulated pareto solution sets were used for comparative analysis and initial parameter calibration. The results showed that the optimization results under a single objective cannot achieve the optimal comprehensive performance, and the proposed VDT-PEMS significantly improves fuel economy and reduces emissions. The effectiveness and feasibility of the proposed strategy were verified through bench testing. The discovery provides important theoretical basis for the management and maintenance of power batteries, which helps to better protect batteries and extend their service life in practical applications.

关键词： Range-extended electric vehicle variable domain energy management parameter adaptive optimization fuzzy control pso algorithm

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Research on the application of particle swarm optimization algorithm based on heterogeneous lithology analysis and drilling parameter correction to optimize the back propagation neural network rate of penetration prediction model

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PETROLEUM SCIENCE AND TECHNOLOGY 2025年

作者： Fang, Xinjie Hu, Zhongzhi Song, Wei Zhou, Yan Tan, Yuelong Sichuan Univ Sci & Engn Coll Mech Engn Yibin 644000 Peoples R China Jidong Oilfield Co Petrochina Co Ltd Tangshan Peoples R China CNPC Daqing Drilling Engn Co Daqing Peoples R China

Accurate prediction of the rate of penetration (ROP) is of great significance for efficient drilling. The traditional ROP prediction model mostly ignores the influence of formation, and takes the term estimated downhole weight on bit (TTEDWOB) as the real downhole weight on bit (WOB) input model, which has a large prediction error. In this study, we modified TTEDWOB, and then proposed a back propagation (BP) neural network ROP prediction model based on particle swarm optimization (pso) on the basis of formation classification. The results show that the error of ROP prediction model is reduced by 7.7% on average in different formation experiments after the correction of TTEDWOB;The prediction accuracy of the model after formation classification is increased by 9.5%;The model is applied to two wells in different blocks, and the average relative errors are 8.51% and 24.78% respectively. The difference between our work and the previous work is that we consider the correction of TTEDWOB and formation conditions. Our suggestion is that it is necessary for researchers to consider TTEDWOB correction and formation factors when establishing ROP prediction models, because doing so will help improve the prediction accuracy of the model.

关键词： BP neural network machine learning pso algorithm ROP prediction WOB

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Investigating the effect of various types of components in optimal designing of a solar/wind/storage hybrid system

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JOURNAL OF ENERGY STORAGE 2025年 110卷

作者： Ghanbari, Kamyar Maleki, Akbar Ochbelagh, Dariush Rezaei Amirkabir Univ Technol Dept Energy Engn & Phys Tehran Iran Shahrood Univ Technol Fac Mech Engn Shahrood Iran

The growing global population and increasing scarcity of conventional fuels raise concerns about meeting power demand, particularly in remote areas with limited grid access. Hybrid renewable microgrids offer a reliable and cost-effective solution to this challenge. These systems typically integrate multiple components, each with varying models and technologies suited to specific conditions. Optimizing such systems and selecting appropriate technologies are critical for enhancing their performance and ensuring cost-effectiveness. This paper focuses on the optimal design, sizing, and technology selection for a hybrid renewable microgrid comprising batteries, wind turbines, and photovoltaic panels. To capture the impact of technology choices, three distinct models for each component were selected, resulting in 27 configurations optimized to identify the most suitable setup for the case study area. The Particle Swarm Optimization algorithm was employed to maximize system reliability, measured by LPSP, and economic performance, reflected in TAC. The optimization results were validated against the Genetic algorithm, a widely recognized method for optimizing similar systems, using statistical benchmark tests. The optimal configuration (PV3/WT3/B1) comprises polycrystalline photovoltaic panels, vertical-axis wind turbines, and lithium-ion batteries, achieving a TAC of $117,521 at 2 % unavailability. In contrast, the least efficient configuration (PV1/WT1/B3) includes thin-film photovoltaic panels, horizontal-axis wind turbines, and lead-acid batteries, with a TAC of $281,167 representing a 139.2 % increase, highlighting the importance of technology selection. A comprehensive sensitivity analysis was also conducted, examining key meteorological, economic, and social factors. This analysis identified the most influential parameters, validated the optimization results, and provided actionable insights for future system designs.

关键词： Hybrid solar/wind/storage system Various energy technologies pso algorithm GA algorithm Optimal sizing Optimal technology selection

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An energy-aware clustering approach based on Gini coefficient and Ipso applied for energy-constrained applications

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TELECOMMUNICATION SYSTEMS 2025年第2期88卷 1-16页

作者： Wan, Hang Gao, Jiaqi David, Michael Derigent, William Zhao, Haiyan Chang, Yufang Hubei Univ Technol Hubei Key Lab High Efficiency Utilizat Solar Energ Wuhan 430068 Peoples R China Univ Lorraine CRAN CNRS UMR 7039 F-54516 Vandoeuvre Les Nancy France

In recent years, wireless sensor networks are playing an increasingly pivotal role in the monitoring of energy-constrained environments. However, the limited power of nodes restricts the network's life cycle and service quality. In this paper, we propose an energy-aware dynamic reorganization clustering protocol based on the Gini coefficient and an improved particle swarm optimization algorithm (DGIpso). The concept of Gini coefficient is applied to address uneven clustering in this hierarchical method. An improved pso method is proposed for optimal cluster head selection, which considers residual energy, distance, and individual Gini coefficient factors. Additionally, a dynamic reorganization mechanism based on the Gini coefficient is introduced to enhance transmission performance over the network's lifespan. Experimental results demonstrate that the proposed DGIpso protocol significantly outperforms LEACH, R-LEACH, pso-C, pso-WZ, and C3HA in network lifetime, energy efficiency, data throughput, and communication stability across various network scales. By incorporating Gini coefficients and heuristic algorithms into dynamic reorganization, this approach effectively addresses uneven energy distribution in clustering protocols, providing innovative strategies for monitoring in resource-constrained applications.

关键词： WSN Energy efficiency Hierarchical clustering protocol Dynamic network reorganization pso algorithm Gini coefficient

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