A Novel Multiple DBC-staked units Package to Parallel More Chips for SiC Power Module

Silicon carbide(SiC) power modules play an essential role in the electric vehicle drive system. To improve their performance, reduce their size, and increase production efficiency, this paper proposes a multiple staked direct bonded copper(DBC) unit based power module packaging method to parallel more chips. This method utilizes mutual inductance cancellation effect to reduce parasitic inductance. Because the conduction area in the new package is doubled, the overall area of power module can be reduced. Entire power module is divided into smaller units to enhance manufacture yield, and improve design freedom. This paper provides a detailed design, analysis and fabrication procedure for the proposed package structure. Additionally, this paper offers several feasible solutions for the connection between power terminals and DBC untis. With the structure, 18dies were paralleled for each phase-leg in a econodual size power module. Both simulation and double pulse test results demonstrate that, compared to conventional layouts, the proposed package method has 74.8% smaller parasitic inductance and 34.9% lower footprint.

Young's double slit interference with vortex source

The fast and convenient demultiplex of optical vortex(OV) mode is crucial for its further application. We propose a novel approach that combines classic Young's doublet with an OV source to effectively identify the OV mode through the analysis of interference patterns. The interference patterns of the OV source incident on the double slits can be perfectly illustrated by using both the classical double-slit interference method and the Huygens–Fresnel principle. The interference fringes will twist along the negative or positive direction of x axis when topological charge(TC)l>0 or l<0, and the degree of the movement varies with the TC, allowing for a quantitative display of the OV characteristics through the interference patterns. Additionally, we deduce analytically that the zeroth-order interference fringe has a linear relationship with the TC and the vertical position. These findings highlight the ability to identify the OV mode by analyzing the interference patterns produced by Young's doublet.

Analysis of the Effect of Temperature and Relative Humidity on the Reliability of a Photovoltaic Module

Photovoltaic energy occupies a significant place in the renewable energy market, with photovoltaic (PV) modules playing a vital role in converting solar energy into electricity. However, their effectiveness is likely to be affected by variations in environmental conditions, including temperature and relative humidity. The study examines the impact of these major climatic factors on the reliability of PV modules, aiming to provide crucial information for optimizing and managing these systems under varying conditions. Inspired by Weibull’s law to model the lifespan of components, we proposed a mathematical model integrating a correction factor linked to temperature and relative humidity. Using this approach, simulations in Matlab Simulink reveal that increasing temperature and relative humidity have an adverse impact on the reliability and lifespan of PV modules, with a more pronounced impact on temperature. The results highlight the importance of considering these environmental parameters in the management and optimization of photovoltaic systems to ensure their long-term efficiency.

A High Resolution Convolutional Neural Network with Squeeze and Excitation Module for Automatic Modulation Classification

Automatic modulation classification(AMC) technology is one of the cutting-edge technologies in cognitive radio communications. AMC based on deep learning has recently attracted much attention due to its superior performances in classification accuracy and robustness. In this paper, we propose a novel, high resolution and multi-scale feature fusion convolutional neural network model with a squeeze-excitation block, referred to as HRSENet,to classify different kinds of modulation signals.The proposed model establishes a parallel computing mechanism of multi-resolution feature maps through the multi-layer convolution operation, which effectively reduces the information loss caused by downsampling convolution. Moreover, through dense skipconnecting at the same resolution and up-sampling or down-sampling connection at different resolutions, the low resolution representation of the deep feature maps and the high resolution representation of the shallow feature maps are simultaneously extracted and fully integrated, which is benificial to mine signal multilevel features. Finally, the feature squeeze and excitation module embedded in the decoder is used to adjust the response weights between channels, further improving classification accuracy of proposed model.The proposed HRSENet significantly outperforms existing methods in terms of classification accuracy on the public dataset “Over the Air” in signal-to-noise(SNR) ranging from-2dB to 20dB. The classification accuracy in the proposed model achieves 85.36% and97.30% at 4dB and 10dB, respectively, with the improvement by 9.71% and 5.82% compared to LWNet.Furthermore, the model also has a moderate computation complexity compared with several state-of-the-art methods.

A review on the cooling of energy conversion and storage systems using thermoelectric modules

Exploitation of sustainable energy sources requires the use of unique conversion and storage systems,such as solar panels,batteries,fuel cells,and electronic equipment.Thermal load management of these energy conversion and storage systems is one of their challenges and concerns.In this article,the thermal management of these systems using thermoelectric modules is reviewed.The results show that by choosing the right option to remove heat from the hot side of the thermoelectric modules,it will be a suitable local cooling,and the thermoelectric modules increase the power and lifespan of the system by reducing the spot temperature.Thermoelectric modules were effective in reducing panel temperature.They increase the time to reach a temperature above 50℃ in batteries by 3 to 4 times.Also,in their integration with fuel cells,they increase the power density of the fuel cell.

Review of Thermal Design of SiC Power Module for Motor Drive in Electrical Vehicle Application

In the current vehicle electric propulsion systems,the thermal design of power modules heavily relies on empirical knowledge,making it challenging to effectively optimize irregularly arranged Pinfin structures,thereby limiting their performance.This paper aims to review the underlying mechanisms of how irregularly arranged Pinfins influence the thermal characteristics of power modules and introduce collaborative thermal design with DC bus capacitor and motor.Literature considers chip size,placement,coolant flow direction with the goal of reducing thermal resistance of power modules,minimizing chip junction temperature differentials,and optimizing Pinfin layouts.In the first step,algorithms should efficiently generating numerous unique irregular Pinfin layouts to enhance optimization quality.The second step is to efficiently evaluate Pinfin layouts.Simulation accuracy and speed should be ensured to improve computational efficiency.Finally,to improve overall heat dissipation effectiveness,papers establish models for capacitors,motors,to aid collaborative Pinfin optimization.These research outcomes will provide essential support for future developments in high power density motor drive for vehicles.

Engineering vascularized organotypic tissues via module assembly

Adequate vascularization is a critical determinant for the successful construction and clinical implementation of complex organotypic tissue models. Currently, low cell and vessel density and insufficient vascular maturation make vascularized organotypic tissue construction difficult,greatly limiting its use in tissue engineering and regenerative medicine. To address these limitations, recent studies have adopted pre-vascularized microtissue assembly for the rapid generation of functional tissue analogs with dense vascular networks and high cell density. In this article, we summarize the development of module assembly-based vascularized organotypic tissue construction and its application in tissue repair and regeneration, organ-scale tissue biomanufacturing, as well as advanced tissue modeling.

A Hybrid Integrated and Low-Cost Multi-Chip Broadband Doherty Power Amplifier Module for 5G Massive MIMO Application

In this paper,a hybrid integrated broadband Doherty power amplifier(DPA)based on a multi-chip module(MCM),whose active devices are fabricated using the gallium nitride(GaN)process and whose passive circuits are fabricated using the gallium arsenide(GaAs)integrated passive device(IPD)process,is proposed for 5G massive multiple-input multiple-output(MIMO)application.An inverted DPA structure with a low-Q output network is proposed to achieve better bandwidth performance,and a single-driver architecture is adopted for a chip with high gain and small area.The proposed DPA has a bandwidth of 4.4-5.0 GHz that can achieve a saturation of more than 45.0 dBm.The gain compression from 37 dBm to saturation power is less than 4 dB,and the average power-added efficiency(PAE)is 36.3%with an 8.5 dB peak-to-average power ratio(PAPR)in 4.5-5.0 GHz.The measured adjacent channel power ratio(ACPR)is better than50 dBc after digital predistortion(DPD),exhibiting satisfactory linearity.

Research on the LA-UMamba Model for Asymmetric Modules with Added Auxiliary Information

Deep learning techniques are revolutionizing the developmentof medical image segmentation.With the advancement of Transformer models,especially ViT and Swin-Transformer,which enhances the remote-dependent modeling capability of the model through the self-attention mechanism,better segmentation performance can be achieve.Moreover,the high computational cost of Transformer has motivated researchers to explore more efficient models,such as the Mamba model based on state-space modeling(SSM),and for the field of medical segmentation,reducing the number of model parameters is also necessary.In this study,a novel asymmetric model called LA-UMamba was proposed,which integrates visual Mamba module to efficiently capture complex visual features and remote dependencies.The classical design of U-Net was adopted in the upsampling phase to help reduce the number of references and recover more details.To mitigate the information loss problem,an auxiliary U-Net downsampling layer was designed to focus on sizing without extracting features,thus enhancing the protection of input information while maintaining the efficiency of the model.The experiments were conducted on the ACDC MRI cardiac segmentation dataset,and the results showed that the proposed LA-UMamba achieves proved performance compared to the baseline model in several evaluation metrics,such as IoU,Accuracy,Precision,HD and ASD,which improved that the model is successful in optimizing the detail processing and reducing the complexity of the model,providing a new perspective for further optimization of medical image segmentation techniques.

Efficient and Stable Inverted Perovskite Solar Modules Enabled by Solid-Liquid Two-Step Film Formation

A considerable efficiency gap exists between large-area perovskite solar modules and small-area perovskite solar cells.The control of forming uniform and large-area film and perovskite crystallization is still the main obstacle restricting the efficiency of PSMs.In this work,we adopted a solid-liquid two-step film formation technique,which involved the evaporation of a lead iodide film and blade coating of an organic ammonium halide solution to prepare perovskite films.This method possesses the advantages of integrating vapor deposition and solution methods,which could apply to substrates with different roughness and avoid using toxic solvents to achieve a more uniform,large-area perovskite film.Furthermore,modification of the NiO_(x)/perovskite buried interface and introduction of Urea additives were utilized to reduce interface recombination and regulate perovskite crystallization.As a result,a large-area perovskite film possessing larger grains,fewer pinholes,and reduced defects could be achieved.The inverted PSM with an active area of 61.56 cm^(2)(10×10 cm^(2)substrate)achieved a champion power conversion efficiency of 20.56%and significantly improved stability.This method suggests an innovative approach to resolving the uniformity issue associated with large-area film fabrication.

Analysis of thermal management and anti-mechanical abuse of multi-functional battery modules based on magneto-sensitive shear thickening fluid

Electric vehicles(EVs)have garnered significant attention as a vital driver of economic growth and environmental sustainability.Nevertheless,ensuring the safety of high-energy batteries is now a top priority that cannot be overlooked during large-scale applications.This paper proposes an innovative active protection and cooling integrated battery module using smart materials,magneto-sensitive shear thickening fluid(MSTF),which is specifically designed to address safety threats posed by lithium-ion batteries(LIBs)exposed to harsh mechanical and environmental conditions.The theoretical framework introduces a novel approach for harnessing the smoothed-particle hydrodynamics(SPH)methodology that incorporates the intricate interplay of non-Newtonian fluid behavior,capturing the fluid-structure coupling inherent to the MSTF.This approach is further advanced by adopting an enhanced Herschel-Bulkley(H-B)model to encapsulate the intricate rheology of the MSTF under the influence of the magnetorheological effect(MRE)and shear thickening(ST)behavior.Numerical simulation results show that in the case of cooling,the MSTF is an effective cooling medium for rapidly reducing the temperature.In terms of mechanical abuse,the MSTF solidifies through actively applying the magnetic field during mechanical compression and impact within the battery module,resulting in 66%and 61.7%reductions in the maximum stress within the battery jellyroll,and 31.1%and 23%reductions in the reaction force,respectively.This mechanism effectively lowers the risk of short-circuit failure.The groundbreaking concepts unveiled in this paper for active protection battery modules are anticipated to be a valuable technological breakthrough in the areas of EV safety and lightweight/integrated design.

Analysis for Effects of Temperature Rise of PV Modules upon Driving Distance of Vehicle Integrated Photovoltaic Electric Vehicles

The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO2 emissions from the transport sector to realize a decarbonized society. Although long-distance driving of VIPV-EV without electricity charging is expected in sunny regions, driving distance of VIPV-EV is affected by climate conditions such as solar irradiation and temperature rise of PV modules. In this paper, detailed analytical results for effects of climate conditions such as solar irradiation and temperature rise of PV modules upon driving distance of the VIPV-EV were presented by using test data for Toyota Prius and Nissan Van demonstration cars installed with high-efficiency InGaP/GaAs/InGaAs 3-junction solar cell modules with a module efficiency of more than 30%. The temperature rise of some PV modules studied in this study was shown to be expressed by some coefficients related to solar irradiation, wind speed and radiative cooling. The potential of VIPV-EV to be deployed in 10 major cities was also analyzed. Although sunshine cities such as Phoenix show the high reduction ratio of driving range with 17% due to temperature rise of VIPV modules, populous cities such as Tokyo show low reduction ratio of 9%. It was also shown in this paper that the difference between the driving distance of VIPV-EV driving in the morning and the afternoon is due to PV modules’ radiative cooling. In addition, the importance of heat dissipation of PV modules and the development of high-efficiency PV modules with better temperature coefficients was suggested in order to expand driving range of VIPV-EV. The effects of air-conditioner usage and partial shading in addition to the effects of temperature rise of VIPV modules were suggested as the other power losses of VIPV-EV.

Study on Image Recognition Algorithm for Residual Snow and Ice on Photovoltaic Modules

The accumulation of snow and ice on PV modules can have a detrimental impact on power generation,leading to reduced efficiency for prolonged periods.Thus,it becomes imperative to develop an intelligent system capable of accurately assessing the extent of snow and ice coverage on PV modules.To address this issue,the article proposes an innovative ice and snow recognition algorithm that effectively segments the ice and snow areas within the collected images.Furthermore,the algorithm incorporates an analysis of the morphological characteristics of ice and snow coverage on PV modules,allowing for the establishment of a residual ice and snow recognition process.This process utilizes both the external ellipse method and the pixel statistical method to refine the identification process.The effectiveness of the proposed algorithm is validated through extensive testing with isolated and continuous snow area pictures.The results demonstrate the algorithm’s accuracy and reliability in identifying and quantifying residual snow and ice on PV modules.In conclusion,this research presents a valuable method for accurately detecting and quantifying snow and ice coverage on PV modules.This breakthrough is of utmost significance for PV power plants,as it enables predictions of power generation efficiency and facilitates efficient PV maintenance during the challenging winter conditions characterized by snow and ice.By proactively managing snow and ice coverage,PV power plants can optimize energy production and minimize downtime,ensuring a sustainable and reliable renewable energy supply.

Heat dissipation enhancement method for finned heat sink for AGV motor driver's IGBT module

With the widespread use of high-power and highly integrated insulated gate bipolar transistor(IGBT),their cooling methods have become challenging.This paper proposes a liquid cooling scheme for heavy-duty automated guided vehicle(AGV)motor driver in port environment,and improves heat dissipation by analyzing and optimizing the core component of finned heat sink.Firstly,the temperature distribution of the initial scheme is studied by using Fluent software,and the heat transfer characteristics of the finned heat sink are obtained through numerical analysis.Secondly,an orthogonal test is designed and combined with the response surface methodology to optimize the structural parameters of the finned heat sink,resulting in a 14.57%increase in the heat dissipation effect.Finally,the effectiveness of heat dissipation enhancement is verified.This work provides valuable insights into improving the heat dissipation of IGBT modules and heat sinks,and provides guidance for their future applications.

Unsupervised multi-modal image translation based on the squeeze-and-excitation mechanism and feature attention module

The unsupervised multi-modal image translation is an emerging domain of computer vision whose goal is to transform an image from the source domain into many diverse styles in the target domain.However,the multi-generator mechanism is employed among the advanced approaches available to model different domain mappings,which results in inefficient training of neural networks and pattern collapse,leading to inefficient generation of image diversity.To address this issue,this paper introduces a multi-modal unsupervised image translation framework that uses a generator to perform multi-modal image translation.Specifically,firstly,the domain code is introduced in this paper to explicitly control the different generation tasks.Secondly,this paper brings in the squeeze-and-excitation(SE)mechanism and feature attention(FA)module.Finally,the model integrates multiple optimization objectives to ensure efficient multi-modal translation.This paper performs qualitative and quantitative experiments on multiple non-paired benchmark image translation datasets while demonstrating the benefits of the proposed method over existing technologies.Overall,experimental results have shown that the proposed method is versatile and scalable.

基于改进LSTM的数码雷管模组印刷质量预测

由于数码雷管模组印刷过程中生产工艺复杂、强时序性等特点,其质量的精准预测已成为提高产品质量管理水平的关键。基于此提出一种改进长短期记忆(long short-term memory,LSTM)网络的数码雷管模组印刷质量预测模型。首先根据数码雷管模组印刷过程提炼机器运行参数、环境参数与检测参数作为印刷产品质量的原始特征,并对关键检测参数进行时序特征重构以增强特征表达能力;其次基于改进的LSTM网络建立数码雷管模组印刷特征提取框架,采用卷积神经网络提取空间特征避免LSTM挖掘高维印刷特征时隐含关系的不足,通过全局注意力机制自适应学习不同时刻印刷特征对印刷产品质量的贡献度,为LSTM提取的深层时序特征分配不同权值;最后以深层特征作为输入,通过全连接网络实现数码雷管模组印刷产品的质量预测。实验结果表明,相较于BP神经网络、门控循环单元网络、LSTM等预测方法,改进的LSTM网络有效提高了数码雷管模组印刷产品质量的预测精度。

自旋-轨道耦合作用下极化激元凝聚中的调制不稳定性

利用线性稳定性分析方法,对存在自旋-轨道耦合(SOS)作用的二维极化激元玻色-爱因斯坦凝聚(BEC)系统中的调制不稳定性(MI)进行了研究.分析了组分内部,组分之间以及SOC相互作用对系统调制不稳定性的影响.结果显示,当系统内部不存在SOC作用,组分之间的相互作用为0,组分内部存在排斥作用时,不会出现调制不稳定性,组分内部存在吸引作用时,会出现调制不稳定性,并且调制不稳定性区间长度随吸引作用的增强而增加;组分之间相互作用不为0时,组分之间的相互作用以平方形式出现,其正负不会对调制不稳定性产生实质性影响.存在SOC相互作用时,SOC相互作用会引起增益谱曲线的不规则振荡,破坏原来的调制不稳定性区间.

Quantitative Study on Module Biomass in Clonal Population of Puccinellia tenuiflora in Songnen Plain

[Objective]The research aimed to study the biomass structure of the functional modules of clonal population of Puccinellia tenuifora on Songnen Plain and its relationship with the functional modules quantitatively.[Method]Using the sample method of digging up the whole tiller tuft randomly at flowering stage,the relationships between the biomass of functional modules and turf size,biomass of different modules and the clone production,reproductive tillers of clones and the biomass of component modules of Puccinellia tenuifora clones on Songnen Plain were quantitatively analyzed.[Result]The biomass of sexual reproductive module,photosynthesis module and supporting module showed a linear increase with the increasing of turf size（P 〈0.05）,while the linear relationship between the biomass of vegetative reproductive module and turf size did not reach the significant level（P 〉0.05）.The restriction degree of turf size on the biomass of functional modules was supporting module sexual reproductive module photosynthesis module vegetative reproductive module.Biomass of reproductive tillers and vegetative tillers showed a linear increase as the biomass of total modules increased（P〈 0.05）,while the linear correlation between the biomass of tillering seedlings and biomass of total modules did not reach the significant level（P 〉0.05）.Biomass of stem,spike and leaf of reproductive plants showed a linear functional increase as reproductive tiller increased（P 〈0.05）,and the ratio of accumulation of biomass of stem,spike and leaf was 7：2：1.[Conclusion]The research laid the theoretical foundation for the further research on the ecology of clustered clone plants.

10Gb/s EML Module Based on Identical Epitaxial Layer Scheme

A 10Gb/s transmitter module containing an electroabsorption modulator monolithically integrated with a distributed feedback (DFB) semiconductor laser is fabricated using the identical epitaxial layer scheme.Gain-coupling mechanism is employed to improve the single mode yield of the DFB laser,while inductively coupled plasma dry etching technique is utilized to reduce the modulator capacitance.The integrated device exhibits a threshold current as low as 12mA and an extinction ratio over 15dB at -2V bias.The small signal modulation bandwidth is measured to be over 10GHz.The transmission experiment at 10Gb/s indicates a power penalty less than 1dB at a bit-error-rate of 10 -12 after transmission through 35km single mode fiber.

一种易于移植和使用的文件系统FatFs Module

介绍一种适用于单片机的嵌入式开源文件系统FatFs Module。相对于其他的开源FAT文件系统,它小巧、读/写速度快、功能强大、易于移植和使用,更适用于资源相对紧张的单片机。本文以AVR系列AT-mega128单片机为例,用FatFs Module的简化版Tiny-FatFs在SD卡上实现FAT文件系统,并给出必要的代码移植说明及其功能测试。