Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Operation of Smart Buildings with Stochastic Connection of Electric Vehicles

One of the key domains in smart cities is smart energy in which smart grid is a main focus. In recent years, with the development of smart grid, controllable air conditioning load participating in demand response projects and the application of renewable energy sources have drawn wide research interests. The integration of photovoltaic (PV) system and electric vehicles into the micro grid has also brought vitality to the stable operation of smart grids. In this paper, a novel control scheme is proposed to optimize the scheduling of building micro grid that integrate controllable air conditioner loads, PV panels and electric vehicles. The optimal operation problem is modeled and further converted into a mixed integer linear programming (MILP) problem whose objective function is minimizing the electricity cost of the building. The stochastic characteristics of electric vehicles are also considered in this paper to better model electric vehicle behaviors. Simulations are conducted on an office building micro grid and the simulation results verify the feasibility of proposed control strategy.
A State-of-the-Art Strategy to Implement Nonlinear Model Predictive Controller with Non-Quadratic Piecewise Discontinuous Cost Index for Ocean Wave Energy Systems

This article presents a novel method to real-time implementation of the Non-Linear Model Predictive Controller (NLMPC) to maximize the energy produced by a Wave Energy Converter (WEC) when the cost index is a non-quadratic piecewise discontinuous functional of some design variables. The presented technique applies to a broader category of nonlinear systems, which require the real-time optimization solution with nonstandard cost functional. The ACADO toolkit is used to implement the proposed NLMPC in MATLAB/Simulink using pseudo-quadratization and weight-scheduling techniques. The proposed strategy features code generation and deployment on real-time target machines. The simulation and experiments confirm the success of the proposed strategy.
Sensitivity Analysis Based NVH Performance Evaluation in Permanent Magnet Synchronous Machines using Lumped Unit Force Response

Noise, vibration, and harshness (NVH) in electric machines are mainly of electromagnetic and structural origin. This research focuses on isolating the structural and electromagnetic impacts on NVH performance, in a fractional slot concentrated winding (FSCW) permanent magnet synchronous machine (PMSM), brought by variation of different design parameters. A modification to the unit force response method is proposed for easier implementation in this work and is termed as lumped unit force response method. The modified method is experimentally verified before subsequent application for sensitivity analysis of various design parameters on NVH performance of a 12-slot/10-pole (12s10p) surface mounted PMSM. Separation of electromagnetic and structural impacts of different design parameters aids decision making during NVH performance optimization. Taguchi orthogonal array based mean and variance analysis are used during the sensitivity analysis in this work.
Power Oscillation Control of Grid-Feeding Converter Considering Next Generation Grid Code During Asymmetrical Faults

Grid-feeding converters are required to maintain the operation capability and support the grid voltage during asymmetrical faults. This paper considers these two demands and proposes an active power oscillation control strategy of grid-feeding converters. By setting a flexible reference current expression with four control parameters, power allocations are mathematically derived to achieve different objectives. Thus, the asymmetrical current is injected to meet the next generation grid code and reduce the voltage unbalance factor (VUF) at the point of common coupling (PCC). The proposed strategy can also attenuate the active power oscillation and take full advantage of the converter capacity, which is implemented in two phase stationary frame without phase-locked loop. Experimental results verify the correctness of the proposed control strategy.
Integrated Isolated OBC for EVs with 6-phase Traction Motor Drives

This work deals with a new topology of on-board integrated battery charger intended for road electric vehicles equipped with a 6-phase traction motor drive. The proposed OBC topology deeply integrates the battery charger within the e-drive powertrain, thus reducing cost and volume of the charger respect to non-integrated solutions. Moreover, galvanic insulation is provided, differently from all fully integrated charger in the literature. Finally, the charger has embedded PFC capability, so the AC grid current is absorbed at unitary power factor and low THD. Extensive simulation results show the feasibility of the proposed solution.
A Novel Simulation Model for Common-Mode Inductors Based on Permeance-Capacitance Analogy

This paper proposes a novel simulation model for common-mode inductors. The proposed model is able to capture the frequency dependency of complex permeability and leakage inductance based on an electric circuit with a gyrator. Electric components such as winding stray capacitance are modeled separately. The proposed model can simultaneously analyze filter inductor impedance with respect to differential-mode and common-mode.
FSA: A Fine-Grained Systolic Accelerator for Sparse CNNs

Sparsity, as an intrinsic property of convolutional neural networks (CNNs), has been widely employed for hardware acceleration, and many customized accelerators tailored for sparse weights or activations have been proposed in these years. However, the irregular sparse patterns introduced by both weights and activations are much more challenging for efficient computation. For example, due to the issues of access contention, workload imbalance, and tile fragmentation, the state-of-the-art sparse accelerator SCNN fails to fully leverage the benefits of sparsity, leading to nonoptimal results for both speedup and energy efficiency. In this article, we propose an efficient sparse CNN accelerator for both weights and activations, namely fine-grained systolic accelerator (FSA), which jointly optimizes both hardware dataflow and software partitioning and scheduling strategy. Specifically, to deal with the access contentions problem, we present a fine-grained systolic dataflow, in which the activations move rhythmically along the horizontal processing element array while the weights are fed into the array in a fine-grained order. We then propose a hybrid network partitioning strategy that sets different partitioning strategies for different layers to balance the workload and alleviate the fragmentation problem caused by both sparse weights and activations. Finally, we present a scheduling search strategy to find the optimized schedules for neural networks, which can further improve energy efficiency. Extensive evaluations show that the proposed FSA consistently outperforms SCNN over AlexNet, VGGNet, GoogLeNet, and ResNet with an average speedup of $1.74\times $ and up to $13.86\times $ energy efficiency.
Online Health Monitoring and Aging Prognostics for SiC Power Converters

The 650 V and 1200 V SiC MOSFETs have gained significant market acceptance in the recent years, mainly, due to the promise of higher power conversion efficiency and power density. However, the lack of field-proven long-term reliability data of SiC MOSFETs is still a major concern, particularly in applications where the devices are exposed to harsh thermal and electrical cycles. This paper discusses a methodology to monitor health status of SiC MOSFETs to enable aging prognostics and remaining useful life estimation. The methodology is based on measurements of ohmic resistance between source and drain terminals. In order to desensitize the method from the well-known temperature dependency of the Rdson; it is proposed to measure the resistance of the MOSFET’s body-diode. It will be shown that body-diode presents a much lower dependency to changes in temperature. The measurements can be obtained in real-time, without interrupting the converter normal operation, a highly appreciated feature in next generation of power electronics converters. By proper management of failure precursor data, it will be possible to forecast converter failures so that necessary actions can be taken before a catastrophic failure occurs. The methodology is applicable for SiC MOSFETs of any voltage class from 650 V to 15 kV.
A Dual Stator/Rotor PM and Winding Flux Modulated PM Machine

In this paper, an ultra-high torque density flux modulated permanent magnet machine (FMPM) topology is elaborately constructed. Its main structural features are that both stator and rotor parts consist of PMs and armature windings, so that a single air gap and simple structure is kept. Meanwhile, the rotor space is fully utilized. What’s more, both the PMs can interact with both the windings, and produce four torque components, and the output torque on the shaft is the superposition of these four torque components. Consequently, extremely high torque is expected. This paper firstly introduces the topology and the main inverter circuit of the machine. Then taking the proposed machine as an example, the basic operation principle and slot/pole combination equation are illustrated. Finally, the electromagnetic performance including flux density, back electromotive force (EMF), torque quality and power factor are analyzed by FEA and the fault tolerance of a set of windings fault is verified.
Study on DC-Voltage Rising of Blocked Port in High-Frequency-Link Converters

High-frequency-link converters (HFLC) are the core part of multi-port power electric transformers. Some of the ports might be blocked during standby while other ports are kept running. Sometimes the blocked ports show significant rises of their dc voltages, which potentially makes these ports be unblocked unsafely and even triggers overvoltage protections. The mechanism of dc voltage rising is studied based on dual active bridges. The transient process excited by the running port is divided into three successive stages and the equivalent circuits and equations are established. The analyses reveal that junction capacitors, dc-link capacitors and leakage inductors play main roles in these transients. To avoid the voltage rising, dual phase-shifting modulation method is adopted, taking the place of single phase-shifting method, to keep power from being injected into the blocked ports during their standby. Simulations are carried out to validate the analyses and the proposed solution.
Isolated DC/DC Multimode Converter with Energy Storage Integration for Charging Stations

Battery storage integration in fast charging station is becoming more popular to achieve higher charging rates with peak-demand shaping. The proposed architecture allows the integration of battery storage in fast charging stations. This architecture consists of an isolated multimode three-port converter (MM3P-SAB), based on single active bridge. Compared to conventional Triple Active Bridge (TAB) architecture, the hybrid solution, with one unidirectional port, leads to cost reduction and higher robustness. Additionally, the topology provides high-efficiency over the whole battery charging profile. Different operation modes are analyzed and a prototype is validated experimentally.
Semi-Supervised Multi-Label Learning for Classification of Wafer Bin Maps With Mixed-Type Defect Patterns

After wafer fabrication, individual chips on the wafer are checked for defects by using multiple electrical tests. The test results can be represented by binary values for all individual chips, which form a spatial map called a wafer bin map (WBM). Different defect patterns in WBMs are related to different causes of process faults. Thus, it is important to classify WBMs according to their defect patterns to identify the root causes of process faults and correct the problems. Recently, with the increase in wafer size, the semiconductor manufacturing process has become more complicated and the probability of having mixed-type defect patterns in WBMs has increased. Previous studies for the classification of mixed-type defect patterns have mainly used labeled WBM data, although a much larger quantity of unlabeled data are often available in practice. To utilize both labeled and unlabeled data to achieve better classification performance, this study proposes the use of a semi-supervised deep convolutional generative model. In particular, we formulate the problem of classifying mixed-type defect patterns as a problem of multi-label classification and adopt multiple latent class variables, each for a distinct single pattern. As an inherent advantage of a generative model, we can also use the proposed model to generate new WBM data.
WinDConv: A Fused Datapath CNN Accelerator for Power-Efficient Edge Devices

Diverse applications of Deep convolution neural networks (CNNs), such as image classification, semantic segmentation, video recognition, etc., in smart systems require high-throughput acceleration for real-time performance. Such CNNs when realized on edge devices of the Internet of Things, a power/energy-efficient compute platform is required, which can meet the limited power/energy budget of the devices. In this regard, an end-to-end power-optimized acceleration for the compute-intensive CNNs is proposed in this work. The proposed architecture, termed WinDConv, introduces a scheme to support both regular and energy-efficient Winograd convolutions on the same architecture through a fused datapath. Furthermore, using a thoroughly investigated data sparsity enhancement, the data reuse scheme, and a suitable memory hierarchy for power efficiency, the proposed architecture is able to exhibit a practical average power efficiency of at least 12.35 tera operations per second per Watt, which is at least <inline-formula> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> higher than the generic <inline-formula> <tex-math notation="LaTeX">$z$ </tex-math></inline-formula>-first storage baseline architecture with over <inline-formula> <tex-math notation="LaTeX">$3\times $ </tex-math></inline-formula> higher energy efficiency. The proposed architecture also demonstrates the applicability of the proposed schemes in commonly occurring variants of the convolution operation.
A Five-Level Flying-DC-Source Multilevel Inverter with Self-Regulated Voltages and Boosting Capability

In this paper, a novel single-phase five-level inverter is proposed. It is composed of eight switches and one flying-dc-source. Compared with the conventional active-neutral-point-clamped five-level inverter, the proposed structure has the same number of active devices and it does not require any sensor or balancing circuits to control the split dc-link capacitors. Thereby, the proposed converter reduces the cost and the complexity of the control system. Additionally, the proposed inverter has the capability of boosting the input voltage by a factor of two, which means it allows a reduction of 50 % in the DC-link voltage requirement and it does not require an intermediate DC-boosting stage for applications such as, photovoltaic panels and full-cells systems, characterized by a low and unregulated input voltage. Experimental results have been performed in order to validate the theoretical analysis of the proposed system.
Influence of Airgap Length on Performance of High Power PM-Assisted Syn-Rel Machines

In recent years, synchronous reluctance (Syn-Rel) machines are research hotspots in variable speed motor drives due to their robust rotor structure and wide constant power speed range (CPSR). More practically, when kVA limitation is considered, embedded permanent magnets (PMs) have been widely adopted in Syn-Rel rotors to further increase power density as well as power factor. In this paper, the authors have investigated the potential of PM-assisted Syn-Rel machine to be the next generation electrical propulsion motor topology for automotive application, with special attention put on a key geometric parameter, i.e., airgap length. In MTPA region, the influence of airgap length on different torque components has been analyzed in detail based on the frozen permeability method. In field weakening region, the variation trend of several key performance such as peak power, iron loss and torque ripple have been investigated along with airgap length. It is found that with specifically high level of electric and magnetic loading, there exists optimal value of airgap length to achieve high power density based on specific cooling and kVA limitation. Numerical FEA and experimental tests are associated to validate the conclusions.
Method of Expanding Operating Range for Three-phase Series-end Winding Motor Drive

This paper proposed a method of expanding operating range for three-phase series-end winding motor drive. Compared with open-end winding motor drive, the series-end winding topology can achieve the same DC voltage utilization with reduced power devices, which balance the performance and cost. However, when compared to traditional AC machine with half-bridge topology, it will increase the current stress of the intermediate leg, thereby limiting the torque capability at low speed. By proposing a new three-phase series-end winding topology for torque capability at low speed and a switching method of two series-end winding topology, the operating range is extended, and the drive power loss at low speed is also reduced. In addition, the zero crossing of phase current is used to achieve seamless switching without affecting the average output torque. Simulation and experimental results verify the advantages of topology and switching methods.
Integrated Planar Transformer Design of 3-kW Auxiliary Power Module for Electric Vehicles

This paper presents a planar transformer design of a 3-kW 250 kHz SiC-based Auxiliary Power Module (APM) with 3.6 kW/L power density for electric vehicle (xEV) application. The transformer design is optimized based on the trade-off between footprint and magnetic loss using the proposed figure-of-merit (FoM) based optimization. In order to increase the ZVS range of the converter, an additional leakage inductance is implemented using the proposed magnetic integration technique. A comparison between non-integrated and integrated magnetic cores using finite element analysis (FEA) is presented. Results show that the integrated structure can reduce the core loss up to 35% and footprint around 15 % compared to the non-integrated. Experimental results show that all the switches can achieves ZVS under the entire load condition.
Modeling of the Temperature Dependence of Soft Magnetic Materials

This paper focuses on the modeling of the temperature dependence of soft magnetic materials. In order to describe the influence of the temperature on the magnetic and energetic properties and deriving consequences for electrical machine application, a simplified but effective model is presented. In this research activity, the influence of a changing material temperature is quantified by measurements that are performed on ring samples. For this, different material grades are investigated. The proposed approach to model the temperature behavior of soft magnetic materials is presented and validated by measurement results. This simplified approach to account for changes in magnetic permeability and iron losses due to changing material temperature is particularly relevant when the model is implemented in a numerical simulation tool. A comparison between model and measurement results of the investigated ring samples is presented and discussed.
How Agile Software Development Affect Software Reusability (Study Case: New Student Admissions Portal in East Java Province)

Software quality has a very important role in the software development process. Several attributes can be used to measure the quality of software. In this study, the attribute chosen was reusability. The main objective of this research is to understand how the Agile method affects application’s reusability. The object research is New Student Admissions Portal (PPDB) in East Java Province. The modules chosen in this study are system modules that support student ranking and registration. Experiments are conducted by reviewing and analyzing its features manually. The research conducted shows that form 6 modules analyzed, there are 2 modules have medium reusability and 4 modules have high reusability.
Comparison of Lithium-Ion Battery Pack Models Based on Test Data from Idaho and Argonne National Laboratories

This paper first reviews lithium-ion (Li-ion) battery models for battery-electric vehicle (BEV) simulation. Electrical equivalent-circuit (EEC) models are then derived using BEV test data from Idaho National Laboratories (INL). Four existing battery models, MATLAB, Tremblay, Log-Linear-Exponential and Polynomial, are compared to the INL test data. A modified-Trembley is introduced to improve the basic Tremblay model. It is shown that the steady-state performance can enable a virtual fuel gauge for a BEV simulator to be constructed. The dynamic performance of the Li-ion battery pack models for BEV applications are then tested with two separate internal impedance circuits in the EEC models and validated utilizing the Argonne National Laboratories (ANL) dynamometer data. A further contribution of this paper is to contrast and validate EEC battery pack models under high power BEV operating conditions.
Dynamic Performance Improvement of Singlephase DC-AC Converter with Non-linear Digital Predictive Control

Single-phase voltage source inverter (VSI) still suffers a long settling time, and significant voltage overshoot/undershoot under the sudden output current change such as the impact load application. This paper first built the system differential equation to model and analyzed this comprehensive large signal dynamic process. And then presents a hardware-efficient digital control algorithm, as the improved capacitor charge balance control (CBC), forces the inductor current and capacitor voltage reach the target value by accurately tracking the predicted optimal trajectory during the transient process. A linear PI regulator is also employed under the steady-state. For the given main circuit parameters and detected load step change, the detailed mathematical derivation and design procedure are provided to guide the implementation. Finally, simulation and experimental results verify single-phase VSI attain the significant settling time reduction and minimized voltage variations. Fast load adjustment can be achieved without the consideration of control bandwidth limitation, like the conventional linear regulator under wide load range operation.