Miracle-dz/UniFAR-FTUs huggingface dataset:
Switching Modeling of Power Devices Turn-Off in a SiC Mosfets-based Inverter Leg

The aim of this paper is to provide an analytical model of the power devices turn-off in a Silicon Carbide (SiC) MOSFETs-based inverter leg. In the proposed modeling approach, different methods have been evaluated to characterize the transconductance profiles, which playa key role in the switching behavior of the power devices. The proposed modeling method represents a good compromise between computational efforts and accuracy. The last has been evaluated by comparing simulation results with experimental tests, under different operating conditions.
Thermal Laser Seperation with Deep Scribe for Silicon Wafer Dicing

TLS-Dicing (Thermal Laser Separation) is a unique technology for separating wafers into single chips in semiconductor back end processing. TLS-Dicing uses thermally induced mechanical stress to separate brittle semiconductor materials, like silicon (Si) and silicon carbide (SiC) wafers. TLS is a two-step TLS-Dicing method consisting of scribing and cleaving. The scribing is used to create a starting point of the second step – the cleaving step. A continuous wave laser in combination with water spray cooling generates a thermal distribution. This leads to a mechanical stress capable to guide one defined crack along the dicing street which leads to the separation of the material. This work investigates a new scribing method – the Deep Scribe – in detail. While using Deep Scribe a pulsed laser beam of near infrared wavelength is focused with an objective into the silicon. This generates a line of subsurface material modification. By using this scribe technique no particles occur at the surface. Additionally, straightness and the bending strength of separated silicon chips can be improved in comparison with state of the art dicing technologies. In this presentation, we will discuss the latest developments in Deep Scribe TLS with focus on the physical effects of the interaction between laser beam and material, as well the requirements for generation of a Deep Scribe. We will investigate the influence of adjusting parameters such as focus position, duration of laser pulse and laser power, on position and size of the modified area. We will also study the effects of thermal laser separation with Deep Scribe on bending strength of diced chips, a crucial parameter for wafer thinning applications. For comparison, similar wafers were cut with current state-of-the-art mechanical blade dicing.
Probabilistic Prediction of Regional Wind Power Based on Spatiotemporal Quantile Regression

Different from power prediction for a single wind farm, the regional wind power prediction is to predict the total power of multiple wind farms located in the same region. Normally, abundant information on spatiotemporal correlations and nonlinearity is implicated in regional wind farms, and thus selecting the most representative explanatory variables becomes one of the most crucial issues to construct an effective regional wind power prediction model. This paper proposes a spatiotemporal quantile regression (SQR) algorithm to perform short-term nonparametric probabilistic prediction of regional wind power, incorporating the advantages of the hybrid neural network (HNN) and quantile regression (QR). In the approach, the high dimensional input data are reorganized into a feature graph that is ready for feature extraction by the HNN. And the advantages of HNN can therefore be utilized to extract the representative features and construct nonlinear regression models. Meanwhile, by following the QR rules, the model can obtain quantiles and perform probabilistic prediction. By properly addressing the explanatory variable selection issue, the approach provides a specific solution for regional wind generation probabilistic prediction with huge input information. Test results on a region with 10 wind farms demonstrate the effectiveness of the proposed approach.
Pulse Width Modulation-Based Common-Mode Noise Source Characterization of Three-Phase Two-Level Split-Source Inverter

Several undesirable impacts of electromagnetic interference (EMI) have been reported in various applications including not only motor drives but also transformerless photovoltaic (PV) power systems and other applications. These impacts are predominantly due to the converter’s noise source voltage that may lead to higher motor bearing currents and inevitably lead to premature damage. In addition to serious leakage currents in non-isolated grid connected PV systems. In this context, this paper presents the analysis and characterization of the noise source spectra of the commonmode (CM) voltage for a single-stage split-source inverter (SSI) topology incorporating three pulse width modulation (PWM) strategies. The mathematical modeling of the investigated modulation techniques is identified, and the induced noise source voltage is examined. Moreover, the resultant noise source spectra are compared, and the main findings are demonstrated. A MATLAB/Simulink model is used to verify the analysis. It is shown that a significant reduction in the noise source spectra can be attained by applying the proposed modulation strategy especially in the high frequency range, which mainly due to the reduced number of transitions in the noise source voltage profile.
An Improved Modulation Strategy for Single-Phase Quasi-Single-Stage AC-DC Converter

An improved triple-phase-shift modulation for single-phase quasi-single-stage (Q1S) AC-DC converter is proposed to eliminate the circulating current and realize the current decouple, thus eliminating the grid side current distortion. The relationship between three phase shifts and desired transfer average current is further determined by introducing the constraint of minimum current stress. All of the theoretical analysis and the proposed ITPS modulation are validated in detail in the experimental way.
Low-Threshold 4/5 Octave-Spanning Mid-Infrared Frequency Comb in a LiNbO$_3$ Microresonator

Mid-infrared (MIR) optical frequency combs (OFCs) are ideal light sources for precision metrology and can find extensive applications, especially in molecular spectroscopy and gas detection. Here the generation of mode-locked MIR frequency comb in a LiNbO<inline-formula><tex-math notation="LaTeX">$_3$</tex-math></inline-formula> microring through optimized slot-waveguide design is proposed. Such microcomb can span over four-fifths of an octave (ranging from <inline-formula><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula>2810 nm to <inline-formula><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula>4630 nm) with pump power as low as 50 mW, which can be applied to the 2<italic>f</italic>-3<italic>f</italic> self-referencing for fully stabilization and helpful to monolithic integration of the whole system. Further investigations on complex dynamical processes for the microcomb generation suggest that the intracavity soliton drifting caused by the third-order dispersion could be compensated by the self-steepening effect as introducing an additional drift through proper dispersion tailoring. This work could facilitate the low-threshold broadband MIR frequency comb generation technique, as well as provide a way to realize more delicate control of soliton microcombs in both temporal and spectral domain.
An Enhanced Multi-frequency Small-Signal Model for a High-Bandwidth PCM Buck Converter

An enhanced multi-frequency small-signal model (E-MFSSM) is proposed to analyze the frequency domain characteristics of high-bandwidth peak current mode (PCM) buck converters. For such systems, the small-signal averaged model (SSAM) fails due to three major factors (i) the sampling-hold effect produced by the PCM control (ii) the considerable sideband components that exist in the pulse width modulation (PWM), and (iii) the large modulation waveform ripple due to the high bandwidth. Several modified small-signal models have been proposed by considering factor (i) or (ii). Compared with these models, our E-MFSSM incorporates all three factors to make further improvement in accuracy. In this study, factors (i) and (iii) are modeled by describing function. By considering the dominant sideband component, factor (ii) is added to obtain this extremely accurate model. Simulations and experiments are presented as verifications.
Fast and Ultra-Fast Charging for Battery Electric Vehicles – A Review

This paper intends to establish an overall up-to-date review on Fast Charging methods for Battery Electric Vehicles (BEV). This study starts from basic concepts involving single battery cell charging, current and future charging standards. Then, some popular power converter topologies employed for this application are introduced, and finally a summary of the industrial solutions available on the market are presented, as well as the ongoing projects related to the extreme fast charging (XFC) network expansion. Practical insights, considering the current BEV scenario, are employed to get a better understanding of this topic. Special attention is given to the modular design approach, analyzing its advantages and some of the factors that influence the number and size of modules that conform a fast charger solution
Big data-empowered system for automatic trouble ticket generation in IoT networks

One of the major concerns for a mobile network operator is the customer trouble ticket (TT) management, as it is directly related to the customers’ satisfaction about the provided quality of service. This issue becomes specially relevant when the number of end devices being served by the cellular network increases dramatically. Such is the case of communications under the Internet of Things (IoT) paradigm. In this case, a traditional approach for TT management appears as insufficient and novel mechanisms for TT management need to be devised. This work proposes a big data-empowered framework for automatic TT generation, showing its capability to deal with such amount of data. Results in a live network providing IoT communication show that the proposed framework was able to identify the network anomalies that were identified following a traditional approach as well as many others that remained hidden under that approach.
Sugar Cane Grading from Photos Using Convolutional Neural Networks

Sugar manufacturing companies need up-to-date information about sugar cane condition in order to forecast sugar yield. However, the wide spatial distribution of cane fields in Thailand makes exhaustive surveys of sugar cane condition impractical. In this paper, we report on initial efforts to apply convolutional neural networks (CNN) to classify sugar cane condition based on ground level photographs of sugar cane fields at different stages of the growing season. Our long term goal is to create a system where farmers can submit mobile phone photos of their fields that will be evaluated for cane quality using a machine learning (ML) model. Results suggest that this approach has promise, but that we need a larger set of exemplars to create a model that can provide classification performance accurate enough for operational use.
New online estimation algorithm of lateral tire-road coefficients based on Inertial Navigation System

For the sake of simplicity, control laws for autonomous vehicle mainly use linear tire models, but this modeling is only valid for small slip angles. Hence, to keep this hypothesis valid, tire’s behavior has to lie within the limits of handling, i.e. there is a threshold the slip angle cannot surpass. This paper develops a new estimator for the cornering stiffness and maximum lateral friction coefficients. These parameters provide important information on the ground conditions and are beneficial for improving the stability of the vehicle. The algorithm is based on estimated lateral tire forces and on a 3 zones adaptive algorithm, including a Dugoff theoretical tire model. It will allow to set up a model not only for the linear part but for the whole range of slip angles, providing the trend of the tire behavior at each time and informing about the future evolution of lateral forces. The advantage of the algorithm is that no measurement of lateral tire forces is needed and few parameters are required such as yaw rate, longitudinal and lateral velocities obtained through an effective Inertial Navigation System, wheel rotational speeds and steering angles. Simulations conducted on realistic dynamical situation validate the algorithm efficiency.
A Fault Precaution Model based on Fault Sequential Patterns for Metro Overhead Contact System

Achieving accurate fault precaution of metro overhead contact system (OCS) is of great significance for the reliability of metro system. However, the current metro maintenance strategies generally adopt the idea of condition monitoring and fault maintenance, which cannot achieve real preventive maintenance. In this paper, we propose a fault precaution model for metro OCS which mines fault sequential patterns from historical fault data. As a case study, we analyzed the historical fault data of a city in south China and formed a fault relational network out of it. At last, detailed process of precaution suggestions generation is given based on the analysis results.
Four-Port Bidirectional Dual Active Bridge Converter for EVs Fast Charging

This paper presents the modeling of the isolated multiport bidirectional dual active bridge DC-DC Converter to be used in fast charging applications. The proposed topology uses four different full-bridge sections: the first full-bridge is able to manage the PV source, the second full-bridge is connected to a stationary storage system and can operate as either a source or a load, the remaining two full-bridges are able to manage the charging of the battery units up to two vehicles. All ports are connected through a high-frequency multi-winding transformer which allows to create a magnetic node. The analytical model of the four-port bidirectional dual active bridge DC-DC (4P-DAB) Converter is addressed in order to investigate the system behavior and to obtain the control law to manage the power flows between the ports. Switching model of a 100 kVA 4P-DAB Converter has been created in MATLAB/Simulink to validate the analytical model. The modes of operation of the proposed topology is then validated through the Hardware-In-the-Loop (HIL) test bench.
Development of a Co-Simulation Framework for Systematic Generation of Scenarios for Testing and Validation of Automated Driving Systems*

Due to the sheer infinite number of test scenarios for test and validation of automated driving, stand-alone on-road testing of these systems is not reasonable, calling for the development of X-in-the-loop test methods. Recent advances in simulation methods are often based on simulation techniques where test scenarios are built considering stochastic traffic or deterministic predefined manoeuvres. To ensure realism, numerical robustness and usability of the test scenarios for both approaches, increasing effort must be invested in modelling the driving environment as well as vehicle and traffic dynamics. Especially traffic models are rarely realistically modelled in most current scenario generation and testing techniques. The goal of the present paper is to introduce a co-simulation framework for automated scenario generation with calibrated traffic flow models using measured data from an official test road in Austria and modelled in PTV Vissim. Combined with the Multi-Body-System vehicle development software IPG CarMaker, the presented co-simulation framework provides an approach for generation of realistic scenarios. This approach is demonstrated for a Highway Chauffeur function and allows future systematic testing.
The Growing Application Field of Laser Debonding: From Advanced Packaging to Future Nanoelectronics

Thin substrate handling has become one of the cornerstone technologies that enabled the development of 3D stacked ICs over the past years. Temporary wafer bonding has continuously improved and reached the maturity level required by volume manufacturing of first-generation devices. Yet the need remains for further development and performance increases. Indeed, the continuous push for denser interconnects has brought new requirements for a through-silicon-via technology on one side but also pushed temporary adhesive and carrier technology into the space of wafer reconstruction and fan-out WLP. On the opposite side of the semiconductor spectrum, at the early steps of the front-end-of-line processing, transistor scaling becomes more and more challenging, including demanding the integration of higher numbers of novel materials. To further increase the options of materials, a growing number of exploratory devices are considering using a layer transfer approach. The advances in temporary bonding and debonding technology is bringing the packaging and nanoscale world together.
Suppression of Quantization-Induced Limit Cycles in Digitally Controlled DC-DC Converters by Dyadic Digital Pulse Width Modulation

Quantization-induced limit cycle oscillations (LCOs) in digitally controlled DC-DC converters are addressed in this paper. The novel Dyadic Digital PWM (DDPWM) is proposed to increase the effective pulse-width-modulator (PWM) resolution, as required for LCO-free operation, at low cost, without sacrificing DC accuracy and with no detrimental effects on the ripple voltage. Experimental results on a synchronous buck validate the approach highlighting effective LCOs suppression and DC accuracy enhancement at 5x reduced output voltage ripple compared to thermometric dithering for the same resolution increase.
Multilevel-Boost-Converter-Neutral-Point-Clamped-Inverter Photovoltaic System with MPPT Based on Fibonacci Search

This paper deals with a system composed by a photovoltaic array feeding a Neutral-Point-Clamped inverter by a dc-dc multilevel boost converter. The system is able to adequately operate under partial shading condition. A current control allows for the boost converter to operate at high frequency while the Maximum Power Point Tracking (MPPT) with the help of Fibonacci search. System operation is explained as well as its model, control and PWM strategy. Simulation and experimental results validate the theoretical studies.
Controller Design for V2X Application Under Unreliable Feedback Channel

In this paper, an LMI-based algorithm for designing the log-quantized controller to stabilize Markovian jump linear systems (MJLS) is introduced, along with related lemmas on system stability. An explanation of how the algorithm could be applied to the design of mode-dependent controller for the system with stochastic packet loss is given. Meanwhile, the state-space function is rearranged and the discrete linear feedback system with delay is modeled as an augmentation model. Then, the LMI-based method is expanded to the system with stochastic delay, solving switched control inputs for various delays and quantization densities. Simulation tests on connected vehicle cooperative adaptive cruise control (CACC) are carried out to verify the feasibility of designing a switched controller for connected vehicles under unreliable communication channel with the proposed method.
Large-scale Detection of Privacy Leaks for BAT Browsers Extensions in China

Although browser extensions bring users a better experience, it creates a hidden danger of privacy leakage. A common privacy leakage detection method is realized through detecting private data transmission. However, only the unintended transmission is considered to be a privacy leak. Therefore, the real challenge is to determine whether or not the transmission is user intended. In order to address this problem, we check the rationality of private data transmission by establishing a privacy model based on classification for extensions to confirm the scope of private data that can be uploaded and domains that can be sent to. Furthermore, we present BEDS (Browser Extension Detection System), a Chromium based extension dynamic detection system. BEDS first builds a privacy model for each extension and then records the extension's network logs and browser API logs when accessing specified pages. Finally, BEDS determines whether there exists a privacy leak according to the strict privacy leakage judgment rules. We test our implementation in large scale on extensions in browsers developed by China's three major Internet companies and complete 15 months of continuous tracking. After examining a total of 14,487 extensions, 1,897 privacy leaks are identified, all results have been inspected by manual and the accuracy of BEDS is over 97%. A number of domains that illegally collect private user data are discovered and tracked. Our results show that about 47,000 Chinese IPs upload private information to suspicious servers every day.
Dynamic Cooperative Automated Lane-Change Maneuver Based on Minimum Safety Spacing Model*

Cooperative lane-change has received considerable attention since the rapid development of vehicle-to-vehicle communication and intelligent transportation system. In this paper a dynamic cooperative lane-change maneuver is proposed, aiming to maintain safety both on the early stage of lane-change maneuver and during the lane-change process. The variable states of surrounding vehicles are taken into consideration. To fit this condition, an improved minimum safety spacing (MSS) model is established, which can calculate safe distance between every two vehicles for each time point during the lane-change process. Based on the calculation results of MSS model, a dynamic lane-change trajectory planning and re-planning method is proposed to obtain safe trajectories and avoid collisions. To verify the validity of the maneuver, some typical lane change scenarios as well as the influence of communication are simulated. The results indicate that the proposed maneuver can achieve efficient and safe cooperative lane-change behavior under complicated conditions when there is no speed limit on the surrounding vehicles.
Hybrid A*-based Curvature Continuous Path Planning in Complex Dynamic Environments

With the progress of autonomous driving technology in recent years, motion planning has been an issue in the navigation of self-driving cars. To achieve an optimal path that meets the requirements of both smoothness and safety, vehicle kinematics and dynamics constraints should be considered. This paper proposes a novel motion planning method based on Hybrid A* for real-time and curvature-contentious path planning with local post smoothing in complex dynamic environments: (1)our method introduces parametric clothoid curves precomputed offline as basic motion primitives for rapid online planning; (2)the path obtained using our method is G2-continuous (i.e., curvature continuous) and does not have a considerable effect on the search time consumption, while also considering possible collisions and motion constraints of nonholonomic car-like vehicles; (3) the node re-expansion issue of conventional Hybrid A* is discussed and resolved by the proposed quintic spine-based local smoothing approach for complete path continuity. Hence, post smoothing and collision checking for the overall resulting path. Simulation and on-road tests have been performed to evaluate the efficiency of the proposed method. The method can be widely implemented in numerous complex scenarios.
Multi-cell Multi-port Bidirectional Flyback based on GaN devices

This paper proposes the novel Multi-cell Multi-port Bidirectional Flyback (M2BF), which is suitable for applications with high-controllability requirement. Moreover, control strategy of the proposed converter and design considerations are analyzed, identifying the most differential characteristics. The main advantage of M2BF is the possibility of configuring the number of connected cells according to the specifications of the system. Besides, an independent control of each cell is proposed with a bidirectional power flow. The assembled experimental prototype is also presented, in order to validate the proposed concept.