Hybrid Multilevel Converters with Internal Cascaded/Paralleled Structures for MV Electric Aircraft Applications

Using on-board medium voltage (MV) dc distribution system has been a megatrend for next-generation electric aircraft systems due to its ability to enable a significant system mass reduction. In addition, it makes electric propulsion more feasible using MV power electronic converters. To develop high-performance high-density MV power converters, the emerging silicon carbide (SiC) devices are more attractive than their silicon (Si) counterparts, since the fast switch frequency brought by the SiC can effectively reduce the volume and weight of the filter components and thus increase the converter power density. From the converter topology perspective, with the MV dc distribution, the state-of-the-art two-level converters are no longer suitable for next-generation electric aircraft system due to the excessive dv/dt and high voltage stress across the power devices.To address these issues while still maintaining cost-effectiveness, this work demonstrates a megawatt-scale MV seven-level (7-L) Si/SiC hybrid converter prototype implemented by active-neutral-point-clamped (ANPC) converter and H-bridges which is called ANPC-H converter in this work, and a MV five-level (5-L) Si/SiC hybrid ANPC converter prototype, which are hybrid multilevel converters with internal cascaded and paralleled structures, respectively. Using multilevel circuit topology, the voltage stress across the devices and converter output voltage dv/dt are reduced. The tradeoff between the system cost and efficiency was addressed by the adoption of the Si/SiC hybrid configuration with optimized modulation strategies. Comprehensive design and evaluation of the full-scale prototypes are elaborated, including the low-inductance busbar designs, power converter architecture optimization and system integration. To control the 7-L Si/SiC hybrid ANPC-H converter prototype, a low computational burden space-vector-modulation (SVM) with common-mode voltage reduction feature is proposed to fully exploit the benefits of 7-L Si/SiC hybrid ANPC-H converter. To further reduce the converter losses and simplify control algorithm, an active hybrid modulation is proposed in this work by applying low frequency modulation in Si cells and high frequency modulation in SiC cells, thus the control framework is simplified from the 7-L SVM to a three-level SVM. To control the 5-L Si/SiC hybrid ANPC converter prototype to overall loss minimization, the low frequency modulation and high frequency modulation are also adopted for Si cells and SiC cells respectively in 5-L Si/SiC hybrid ANPC converter prototype. Compared to the SVM-based hybrid modulation in 7-L ANPC-H converter, the hybrid modulation for 5-L hybrid ANPC adopts a simpler carrier-phase-shifted pulse width modulation for its inner-paralleled high frequency SiC cells, which extensively suppresses harmonics caused by high frequency switching. With the proposed modulation strategies, extensive simulation and experimental results are provided to evaluate the performance of each power stage and the full converter assembly in both the steady-state operation and variable frequency operations of the demonstrated hybrid converters

Hybrid Multilevel Converters with Internal Cascaded/Paralleled Structures for MV Electric Aircraft Applications

Using on-board medium voltage (MV) dc distribution system has been a megatrend for next-generation electric aircraft systems due to its ability to enable a significant system mass reduction. In addition, it makes electric propulsion more feasible using MV power electronic converters. To develop high-performance high-density MV power converters, the emerging silicon carbide (SiC) devices are more attractive than their silicon (Si) counterparts, since the fast switch frequency brought by the SiC can effectively reduce the volume and weight of the filter components and thus increase the converter power density. From the converter topology perspective, with the MV dc distribution, the state-of-the-art two-level converters are no longer suitable for next-generation electric aircraft system due to the excessive dv/dt and high voltage stress across the power devices.To address these issues while still maintaining cost-effectiveness, this work demonstrates a megawatt-scale MV seven-level (7-L) Si/SiC hybrid converter prototype implemented by active-neutral-point-clamped (ANPC) converter and H-bridges which is called ANPC-H converter in this work, and a MV five-level (5-L) Si/SiC hybrid ANPC converter prototype, which are hybrid multilevel converters with internal cascaded and paralleled structures, respectively. Using multilevel circuit topology, the voltage stress across the devices and converter output voltage dv/dt are reduced. The tradeoff between the system cost and efficiency was addressed by the adoption of the Si/SiC hybrid configuration with optimized modulation strategies. Comprehensive design and evaluation of the full-scale prototypes are elaborated, including the low-inductance busbar designs, power converter architecture optimization and system integration. To control the 7-L Si/SiC hybrid ANPC-H converter prototype, a low computational burden space-vector-modulation (SVM) with common-mode voltage reduction feature is proposed to fully exploit the benefits of 7-L Si/SiC hybrid ANPC-H converter. To further reduce the converter losses and simplify control algorithm, an active hybrid modulation is proposed in this work by applying low frequency modulation in Si cells and high frequency modulation in SiC cells, thus the control framework is simplified from the 7-L SVM to a three-level SVM. To control the 5-L Si/SiC hybrid ANPC converter prototype to overall loss minimization, the low frequency modulation and high frequency modulation are also adopted for Si cells and SiC cells respectively in 5-L Si/SiC hybrid ANPC converter prototype. Compared to the SVM-based hybrid modulation in 7-L ANPC-H converter, the hybrid modulation for 5-L hybrid ANPC adopts a simpler carrier-phase-shifted pulse width modulation for its inner-paralleled high frequency SiC cells, which extensively suppresses harmonics caused by high frequency switching. With the proposed modulation strategies, extensive simulation and experimental results are provided to evaluate the performance of each power stage and the full converter assembly in both the steady-state operation and variable frequency operations of the demonstrated hybrid converters

Determining anomalies in a semilinear elliptic equation by a minimal number of measurements

We are concerned with the inverse boundary problem of determining anomalies associated with a semilinear elliptic equation of the form $-\Delta u+a(\mathbf x, u)=0$, where $a(\mathbf x, u)$ is a general nonlinear term that belongs to a H\"older class. It is assumed that the inhomogeneity of $f(\mathbf x, u)$ is contained in a bounded domain $D$ in the sense that outside $D$, $a(\mathbf x, u)=\lambda u$ with $\lambda\in\mathbb{C}$. We establish novel unique identifiability results in several general scenarios of practical interest. These include determining the support of the inclusion (i.e. $D$) independent of its content (i.e. $a(\mathbf{x}, u)$ in $D$) by a single boundary measurement; and determining both $D$ and $a(\mathbf{x}, u)|_D$ by $M$ boundary measurements, where $M\in\mathbb{N}$ signifies the number of unknown coefficients in $a(\mathbf x, u)$. The mathematical argument is based on microlocally characterising the singularities in the solution $u$ induced by the geometric singularities of $D$, and does not rely on any linearisation technique

Feature Selection Inspired Classifier Ensemble Reduction

Classifier ensembles constitute one of the main research directions in machine learning and data mining. The use of multiple classifiers generally allows better predictive performance than that achievable with a single model. Several approaches exist in the literature that provide means to construct and aggregate such ensembles. However, these ensemble systems contain redundant members that, if removed, may further increase group diversity and produce better results. Smaller ensembles also relax the memory and storage requirements, reducing system's run-time overhead while improving overall efficiency. This paper extends the ideas developed for feature selection problems to support classifier ensemble reduction, by transforming ensemble predictions into training samples, and treating classifiers as features. Also, the global heuristic harmony search is used to select a reduced subset of such artificial features, while attempting to maximize the feature subset evaluation. The resulting technique is systematically evaluated using high dimensional and large sized benchmark datasets, showing a superior classification performance against both original, unreduced ensembles, and randomly formed subsets. ? 2013 IEEE

2-Chloro-N′-(2-hy­droxy-3,5-diiodo­benzyl­idene)benzohydrazide

In the title compound, C14H9ClI2N2O2, the dihedral angle between the benzene rings is 65.9 (2)° and an intra­molecular O—H⋯N hydrogen bond generates an S(6) ring. The mol­ecule has an E conformation about the C=N bond. In the crystal, mol­ecules are linked into C(4) chains propagating in [001] by N—H⋯O hydrogen bonds

Hybrid Active PWM Strategy with Dual-Mode Modulation Waves of Three-Level T-type Converter for Aircraft Turboelectric Propulsion Systems

Turboelectric propulsion is emerging as an enabling technology for the future aviation industry, aiming to reduce its carbon footprint. To provide electrified thrust for aircraft, the converter-fed motor drive system is a promising solution for the energy conversion between an onboard dc distribution bus and a high-speed electric machine. However, the neutral-point potential fluctuation and even drifting can be an outstanding issue when employing three-level neutral-point-clamped (3L-NPC) topologies, which puts the converter output performance and the lifespan of capacitors at risk. To address these problems, in this paper, a new hybrid active pulse-width-modulation (PWM) strategy is proposed for the studied airborne electric propulsion systems. With the versatile dual-mode modulation signals, not only can the proposed PWM algorithm keep capacitor voltages balanced at the entire range of operating points but also switching losses can be lowered with the help of discontinuous pulse trains during the cruise. Moreover, the computational burden rendered by a short switching cycle is reduced by the sextant coordinate-based analytical derivation. The effectiveness of the presented modulation technique are validated through simulation results from a Simulink/PLECS model and experimental results obtained from a 200 kVA silicon-carbide (SiC) based T-type 3L-NPC prototype with a variable output fundamental frequency

Anomaly Detection and Explanation Discovery on Event Streams

International audienceAs enterprise information systems are collecting event streams from various sources, the ability of a system to automatically detect anomalous events and further provide human readable explanations is of paramount importance. In this position paper, we argue for the need of a new type of data stream analytics that can address anomaly detection and explanation discovery in a single, integrated system, which not only offers increased business intelligence, but also opens up opportunities for improved solutions. In particular , we propose a two-pass approach to building such a system, highlight the challenges, and offer initial directions for solutions

Spark-based Cloud Data Analytics using Multi-Objective Optimization

International audienceData analytics in the cloud has become an integral part of enterprise businesses. Big data analytics systems, however, still lack the ability to take user performance goals and budgetary constraints for a task, collectively referred to as task objectives, and automatically configure an analytic job to achieve these objectives. This paper presents a data analytics optimizer that can automatically determine a cluster configuration with a suitable number of cores as well as other system parameters that best meet the task objectives. At a core of our work is a principled multi-objective optimization (MOO) approach that computes a Pareto optimal set of job configurations to reveal tradeoffs between different user objectives, recommends a new job configuration that best explores such tradeoffs, and employs novel optimizations to enable such recommendations within a few seconds. We present efficient incremental algorithms based on the notion of a Progressive Frontier for realizing our MOO approach and implement them into a Spark-based prototype. Detailed experiments using benchmark workloads show that our MOO techniques provide a 2-50x speedup over existing MOO methods, while offering good coverage of the Pareto frontier. When compared to Ottertune, a state-of-the-art performance tuning system, our approach recommends configurations that yield 26%-49% reduction of running time of the TPCx-BB benchmark while adapting to different application preferences on multiple objectives