Modular Multi Research Articles

Performance of Modular Multilevel Converter in Electric Vehicles Charging Station

The awareness of air pollution is the main reason for the development of Electric Vehicles. Hence, the many number of Electric vehicle connected to grid produce power quality problem in conversion of AC-DC. In this paper, to avoid this drawback, the MATLAB/SIMULINK model of Modular Multi Level Converter is implemented in charging station. MMC not only provide bidirectional flow but also improve power quality. The converter works on boost mode and buck mode. In G2V, the boost mode is for charging the battery of electric vehicle and buck mode is discharging the battery. For, the G2V, the buck mode reduces the voltage to charge the battery with current or voltage constant which is about the state of the charge of the battery. The out of the battery is pure dc with mmc which replace the filter also. It increases the life of the battery. The model of the MMC-based charger for electric vehicle was created in MATLAB/Simulink, and simulation results shows the output power of the MMC and circulation current is controlled.

模块化多关节绳驱动并联机器人设计

模块化多关节绳驱动并联机器人设计

Switching Characterization and Power Loss Optimization for Modular Multiactive Bridge Converter Under Common Phase Shift Control

In modular multi active bridge (MMAB) converters which are inherently coupled among dc ports, single phase-shift (SPS) control has been widely adopted due to its simplicity in implementation and neglect of coupling characteristics in control algorithms. However, under SPS control, the converter may have unfavorable system efficiency performance, especially when voltage conversion ratios of ports mismatch. To improve the efficiency, this paper proposes a common phase-shift (CPS) control method for a generalized MMAB or multi active bridge converter. A comprehensive operation analysis of MMAB converters under CPS control with switching characterization of power semiconductors has been carried out. Besides, an overall power loss model is derived, with main electrical components and their power-loss behaviors taken into consideration. Moreover, an optimal strategy aimed at power loss optimization is proposed to improve the efficiency of the converter. Finally, a four-port experimental MMAB converter prototype has been constructed. The experimental results and tested efficiency curves have verified the feasibility and effectiveness of the proposed CPS control.

ZVS Soft Switching Operation Region Analysis of Modular Multi Active Bridge Converter Under Single Phase Shift Control

Modular multi active bridge (MMAB) converter can provide multiple dc ports using modular H-bridge. When voltage conversion ratios of each port are not equally balanced, zero-voltage-switching (ZVS) turn-on of power semiconductors in the MMAB converter cannot be secured under single phase shift (SPS) control, increasing power loss and leading to lower efficiency. To estimate the efficiency of the converter in various conditions, ZVS operation region of MMAB converters under SPS is comprehensively derived based on steady-state time domain with superposition theorem. Voltage conversion ratios are taken as main variables for ZVS region analysis and influences of them are comprehensively analyzed. Full ZVS regions and constrained ZVS regions are obtained by ZVS discriminants. Simulation and experimental results for a three-port MMAB prototype are given to verify the theoretical analysis of ZVS operation region.

Modular Multi-Source Prediction of Drug Side-Effects With DruGNN.

Drug Side-Effects (DSEs) have a high impact on public health, care system costs, and drug discovery processes. Predicting the probability of side-effects, before their occurrence, is fundamental to reduce this impact, in particular on drug discovery. Candidate molecules could be screened before undergoing clinical trials, reducing the costs in time, money, and health of the participants. Drug side-effects are triggered by complex biological processes involving many different entities, from drug structures to protein-protein interactions. To predict their occurrence, it is necessary to integrate data from heterogeneous sources. In this work, such heterogeneous data is integrated into a graph dataset, expressively representing the relational information between different entities, such as drug molecules and genes. The relational nature of the dataset represents an important novelty for drug side-effect predictors. Graph Neural Networks (GNNs) are exploited to predict DSEs on our dataset with very promising results. GNNs are deep learning models that can process graph-structured data, with minimal information loss, and have been applied on a wide variety of biological tasks. Our experimental results confirm the advantage of using relationships between data entities, suggesting interesting future developments in this scope. The experimentation also shows the importance of specific subsets of data in determining associations between drugs and side-effects.

Efficient hardware realization and high radix implementation of modular multi exponential techniques for public key cryptography

Modular multi exponentiation (MME) is a critical operation in most of the public-key cryptosystems and verification functions. Two novel algorithms: HRMME and SFWHRMME, are proposed to evaluate the MME efficiently. The evaluation process of the proposed algorithm has an inbuilt confusion mechanism, which increases the security level. The side-channel attacks and timing attacks are counteracted by algorithmic means instead of using only hardware measures. The high-radix implementation is efficiently reducing the required number of clock cycles. The performance of the proposed algorithms is analyzed in terms of power, throughput and energy. The experimental results show that the proposed techniques HRMME and SFWHRMME increase the throughput in the order of 23.55% and 23.67%, respectively and consume less power in the order of 21.78% and 21.88%. Xilinx Vivado 21.2 on Virtex-7 evaluation boards and ICARUS Verilog simulation & synthesis tools are used for FPGA for hardware realization. The hardware compatibility of proposed algorithms has also been checked using Cadence for ASIC.

A Deep Learning-based Model for Evaluating the Sustainability Performance of Accounting Firms

The harmonious and stable development of society is strongly related to the sustainable development of enterprises. In order to better face the challenges of environmental resources, sustainable development must be included in the development focus of accounting enterprises. The research proposes a performance evaluation model based on deep learning, improves RBMs model on the basis of deep belief network (DBN), improves the accuracy of the model through reverse fine-tuning technology, and effectively combines multiple restricted Boltzmann machines (RBMs) and Softmax classifiers to build a modular multi classification model to complete the sustainable development performance evaluation of accounting enterprises. The performance of RBM fine tuning classifier is higher than that of RBM expression and PCA (Principal Component Analysis) expression, which mainly shows the effectiveness and stability of feature extraction. The network output results of test samples are converted into prediction performance evaluation. The model is evaluated by average precision (AP), average recall (AR), and prediction accuracy. The AP, AR, and prediction accuracy of the proposed method are 86.95%, 89.74%, and 88.29% respectively, which are higher than Softmax classifiers, Back Propagation (BP) neural networks, and DBN based Softmax methods, It shows that this method is superior to other algorithms in the application of performance evaluation model for sustainable development of accounting enterprises, and it is feasible and effective, which is of great significance to the establishment of performance evaluation model for the accounting industry.

An efficient signed digit montgomery modular multiplication algorithm

In this paper, we present a novel radix-2 Montgomery modular multi+d its corresponding architecture for high speed and low ATP implementation. The proposed multiplier, which is based on the Signed Digit Adder(SDA), requires binary input and also generates a modular product in binary form. To speed up radix-2 Montgomery modular multiplication process, we first design a new Simplified SDA(SSDA), dedicated to multipliers based on Non-Adjacent-Form(NAF) methods, which can not only avoid the carry propagation at each addition operation of add-shift loop, but also reduce the addition rounds efficiently. Second, a detecting and skipping mechanism based on the proposed SSDA has been studied to bypass some unnecessary addition rounds which would further reduce the addition rounds. In addition, our proposed Montgomery modular multiplier uses only one-level SDA architecture, and this architecture is also used to both the operand pre-computation and the final format conversion, which lead to a low hardware cost and short critical path delay. At last, we compare the area, the critical path and the cycle number of the proposed multiplier with those of other multipliers based on CSAs and SDAs. Experimental results show that the proposed Montgomery modular multiplier can achieve higher speed(6.9%) and area–time product improvement(19.4%) when compared with previous designs.

Fuzzy based controller for a hybrid electric vehicle with MMC and SRM drive

In this article a novel fuzzy control based Hybrid Electric Vehicle (HEV) with Modular Multi Converter (MMC) fed Switched Reluctance Motor (SRM) is investigated. In this proposed approach MMC fed to the SRM motor with integration of Full Bridge (FB) converter. FB switching pattern operates with intelligent fuzzy control algorithm. The MMC inverter fed SRM drive HEV has been successfully simulated with MATLAB software package. The simulation results are proven that the harmonics are mitigated by employing proposed method. Performance characteristics of SRM motor such as, phase voltage, line voltage, speed, torque, rotor current, load torque is obtained, and these are compared with conventional methods i.e. current converter operated HEVs and solar (PV) integrated HEVs. It can be observed from the reported results that the proposed method is providing satisfactory output results.

Transmission Congestion& Voltage Profile Management using Modular Multi Level UPFC

Modular multi level convertor based UPFC (MMC-UPFC) has become one amongst the foremost rising convertor typologies for medium & high-powered applications. In the last years, outstanding researches are done concerning to Transmission congestion and voltage profile management victimization MMC-UPFC. Thus, standard construction convertor UPFC has been a major topic for each industrial applications and tutorial surveys. In this paper, an outline of the ability circuit analysis and operation principle of the standard construction of MMC-UPFC topology is mentioned. Totally different sub-module typologies are mentioned. Then, advantage sides of the MMC-UPFC which of application areas is reviewed. The proposed technique additional appropriate to avoids Transmission congestion & additionally for higher voltage profile management than previous ways, The proposed system used for MMC-UPFC better improvement of voltage profile and effective congestion relief also the entire function a promising answer for sensible applications, particularly once the quantity of sub-modules is fairly high. Simulation and experimental results verify the effectiveness of the proposed

Real-world operating strategy and sensitivity analysis of frequency containment reserve provision with battery energy storage systems in the german market

Large-scale battery energy storage systems (BESS) have become increasingly interesting to provide ancillary services for the electricity grid. Especially the German frequency containment reserve (FCR) market which is organized by the German transmission system operators (TSO) is attractive for BESS. Because of its importance for the system stability, FCR has to be provided continuously with 100% availability. Due to the limited energy capacity of BESS, an operating strategy is required to enable continuous FCR provision. The German TSOs have defined several requirements that BESS have to comply with as well as degrees of freedom (DoF) to enable corrective measures such as selective recharging for an operating strategy. This paper presents a sensitivity analysis of different operational parameters based on an operating strategy developed within the M5BAT (Modular Multi_Megawatt Multi-Technology Medium-Voltage Battery Energy Storage System) project. Within this project the construction and operation of a 5MW hybrid BESS with five different battery technologies is realized. As this BESS will mainly be operated in the German FCR market, it is used as reference for this paper. The developed operating strategy considers the TSO’s FCR requirements and DoF and is fully applicable to the German FCR market. Within this paper it is explained how corrective measures have to be triggered in order to comply with the requirements. A model of the M5BAT BESS, which comprises various battery technologies and an energy management system (EMS) for load allocation among multiple battery strings, is introduced. Simulations of FCR operation with measured frequency data of the year 2014 are presented. The influence of the lead time and duration of corrective measures, the EMS and the FCR requirements on compliance with the FCR requirements, amount of corrective measures, resulting energy throughput, state-of-energy (SOE) distributions and cycle numbers are investigated. The results show a significant impact of all parameters. It is found that velocity and flexibility of corrective measures (e.g. recharging) and an efficient EMS are prerequisites for FCR operation with BESS under the applicable regulation. Additionally, the results indicate that the overall benefits of FCR provision with BESS could be improved with an adjustment of the requirements (30-min-criterion).

Application of modular multilevel converter for AGC in an interconnected power system

Abstract This article demonstrates the maiden application of a new Modular Multi level Converter based Series Compensation (MMCS) technique for multi area Automatic Generation Control (AGC) interconnected system. Primarily MMCS has been modeled in state space form and proposes an appropriate location in AGC to obtain the better dynamic responses in frequency, tie-line power and individual generating power; further to quench the oscillation for sudden changes in load. The system has been studied the operation of MMCS and investigated with Generation Rate Constraints (GRC) of reheat turbines used in system. Further, selection of suitable integral and proportional–integral controller gain has been investigated with Integral Square Error (ISE) technique and Particle Swarm Optimization (PSO) technique for step load perturbation (SLP) in area-1 with performance index as its objective function by making control parameters as variables. System with MMCS is compared with out MMCS and observed performance has been increased and results are explored.

Defined Variables for Modular Construction Multi Project Scheduling

The modular construction has several advantages such as high quality of product, safe work condition and short construction duration. So, it is adopted and utilized widely to product the house buildings. Meanwhile, the modular construction is composed of manufacturing modular units in factories and erecting it on the site. In this circumstance, the scheduling of modular construction should consider timeframe of manufacturing, transport and erection process with limited resources (e.g., modular units, transporter and workers). Also, this has a characteristic generated from the environmental condition of modular construction, which share resource pool such as the productivity of factory, storage for modular units and workers. So, the concept of multi project scheduling for modular construction should be also considered. The multi project scheduling of modular construction would manage the modular construction’s characteristics and diversity of projects, as a type of modular unit, quantities, and date for delivery. In this circumstance, this research preferentially performs to define variables of required resources from numerous literature reviews and expert interviews for multi project scheduling of modular construction. The authors regard that proposed variables are used for building a scheduling of multi project modular construction and suggest a framework for schedule optimization considering factory, shipping and erection process.

모듈라 곱셈의 충돌 입력에 기반한 부채널 공격 및 대응책

ABSTRACT The power analysis attack is a cryptanalytic technique to retri eve an user's secret key using the side-channel power leakage occurred during the execution of cryptographic algorithm embedd ed on a physical device. Especially, many power analysis attacks have targeted on an exponentiation algorithm which is c omposed of hundreds of squarings and multiplications and adopted in public key cryptosystem such as RSA. Recently, a new correlation power attack, which is tried when two modular multiplications have a same input, is proposed in order to reco ver secret key. In this paper, after reviewing the principle of side-channel attack based on input collisions in modular multip lications, we analyze the vulnerability of some exponentiation algorithms having regularity property. Furthermore, we present an improved exponentiation countermeasure to resist against the input collision-based CPA(Correlation Power Analysis) attack an d existing side channel attacks and compare its security with other countermeasures.Keywords: Power Analysis Attack, Exponentiation Algorithm, Modular Multi plication, Input Collision-based CPA

Rapid exploration of cost-performance tradeoffs using dominance effect during design of hardware accelerators

Modern Very Large Scale Integration (VLSI) designs require a tradeoff between cost efficiency and performance (circuit speed). Furthermore, the Design Space Exploration (DSE) of the cost-performance tradeoffs for the multi objective VLSI designs should also be fast and efficient in nature. This paper presents a novel accelerated DSE approach for the exploration of cost-performance tradeoffs of modular multi (trio parametric. viz. cost, execution time and power consumption) objective VLSI hardware accelerators using hierarchical criterion analysis. The selection of the final design point is made after the tradeoffs are explored using the proposed approach. Results of the proposed approach when applied to various benchmarks yielded significant acceleration in the exploration process compared to current existing approaches with multi parametric objective.

Simulation of Non-Isothermal Flow in a Modular Buss Kneader and Comparison with Experiment

Abstract Non-isothermal flow is simulated in a modular Buss Kneader including crosshead screw extruder. A method of calculating cycle averaged mean temperature rises for individual elements is discussed and results are presented. A method is then described for making calculations in a modular multi element Buss Kneader. Finally we compared the calculations with experiment.