Comparison of Hand-Written RTL code against High-Level Synthesis for Blowfish and Tiny Encrpytion Algorithm (TEA)

Cryptography is the backbone of a secure and reliable communication system. Data security while transmission depends upon the strength of cryptographic algorithm. In this work, Tiny Encryption Algorithms (TEA) and Blowfish algorithms has been implemented using the High Level Synthesis (HLS) and hand-written Register Transfer Level (RTL) approaches in Xilinx Vivado HLS and Xilinx ISE. Comparative evaluation for both implementation approaches has shown that RTL approach is outperforming HLS approach in both algorithms for different parameters like throughput, frequency etc., due to flexibility of designing modules in RTL as compared to HLS approach

Nonlinear adaptive NeuroFuzzy feedback linearization based MPPT control schemes for photovoltaic system in microgrid.

Renewable energy resources connected to a single utility grid system require highly nonlinear control algorithms to maintain efficient operation concerning power output and stability under varying operating conditions. This research work presents a comparative analysis of different adaptive Feedback Linearization (FBL) embedded Full Recurrent Adaptive NeuroFuzzy (FRANF) control schemes for maximum power point tracking (MPPT) of PV subsystem tied to a smart microgrid hybrid power system (SMG-HPS). The proposed schemes are differentiated based on structure and mathematical functions used in FRANF embedded in the FBL model. The comparative analysis is carried out based on efficiency and performance indexes obtained using the power error between the reference and the tracked power for three cases; a) step change in solar irradiation and temperature, b) partial shading condition (PSC), and c) daily field data. The proposed schemes offer enhanced convergence compared to existing techniques in terms of complexity and stability. The overall performance of all the proposed schemes is evaluated by a spider chart of multivariate comparable parameters. Adaptive PID is used for the comparison of results produced by proposed control schemes. The performance of Mexican hat wavelet-based FRANF embedded FBL is superior to the other proposed schemes as well as to aPID based MPPT scheme. However, all proposed schemes produce better results as compared to conventional MPPT control in all cases. Matlab/Simulink is used to carry out the simulations

Consensus based SoC trajectory tracking control design for economic-dispatched distributed battery energy storage system.

The state-of-charge (SoC) of an energy storage system (ESS) should be kept in a certain safe range for ensuring its state-of-health (SoH) as well as higher efficiency. This procedure maximizes the power capacity of the ESSs all the times. Furthermore, economic load dispatch (ELD) is implemented to allocate power among various ESSs, with the aim of fully meeting the load demand and reducing the total operating cost. In this research article, a distributed multi-agent consensus based control algorithm is proposed for multiple battery energy storage systems (BESSs), operating in a microgrid (MG), for fulfilling several objectives, including: SoC trajectories tracking control, economic load dispatch, active and reactive power sharing control, and voltage and frequency regulation (using the leader-follower consensus approach). The proposed algorithm considers the hierarchical control structure of the BESSs and the frequency/voltage droop controllers with limited information exchange among the BESSs. It embodies both self and communication time-delays, and achieves its objectives along with offering plug-and-play capability and robustness against communication link failure. Matlab/Simulink platform is used to test and validate the performance of the proposed algorithm under load disturbances through extensive simulations carried out on a modified IEEE 57-bus system. A detailed comparative analysis of the proposed distributed control strategy is carried out with the distributed PI-based conventional control strategy for demonstrating its superior performance

Minimization of Torque Ripples in Multi-Stack Slotted Stator Axial-Flux Synchronous Machine by Modifying Magnet Shape

This paper presents a proposed model of a multi-stack slotted stator axial-flux type permanent magnet synchronous machine (AFPMSM) specifically for reducing torque ripple. The proposed AFPMSM model uses pentagon-shaped permanent magnets (PMs). It has a low value of cogging torque and torque ripples compared to the conventional model with a trapezoidal magnet shape. Additionally, it has increased internal generated voltage (Ef) as compared to the conventional model. To further enhance Ef phases and minimize cogging torque of the proposed model, the proposed AFPMSM model was optimized by varying different sides of PMs using a genetic algorithm (GA). A time-stepped three-dimensional (3D) finite element analysis (FEA) was performed for the comparative analysis of conventional, proposed, and optimized AFPMSM models. From this comparative performance analysis, it is observed that torque ripples and cogging torque of the optimized AFPMSM are significantly decreased, while output average torque is appreciably increased. Ef and output power are also enhanced

Minimization of Torque Ripples in Multi-Stack Slotted Stator Axial-Flux Synchronous Machine by Modifying Magnet Shape

This paper presents a proposed model of a multi-stack slotted stator axial-flux type permanent magnet synchronous machine (AFPMSM) specifically for reducing torque ripple. The proposed AFPMSM model uses pentagon-shaped permanent magnets (PMs). It has a low value of cogging torque and torque ripples compared to the conventional model with a trapezoidal magnet shape. Additionally, it has increased internal generated voltage (Ef) as compared to the conventional model. To further enhance Ef phases and minimize cogging torque of the proposed model, the proposed AFPMSM model was optimized by varying different sides of PMs using a genetic algorithm (GA). A time-stepped three-dimensional (3D) finite element analysis (FEA) was performed for the comparative analysis of conventional, proposed, and optimized AFPMSM models. From this comparative performance analysis, it is observed that torque ripples and cogging torque of the optimized AFPMSM are significantly decreased, while output average torque is appreciably increased. Ef and output power are also enhanced