Simulation Study of Two Torque Optimization Methods for Direct Torque‐Controlled Induction Motors

The simplicity and excellent dynamic performance of Direct Torque Control (DTC) make Induction Motor (IM) drives attractive for many applications that require precise torque control. The traditional version of DTC uses hysteresis controllers. Unfortunately, the nature of these controllers prevents the optimization of the inverter voltage vectors inside the flux hysteresis band. The inverter voltage vector optimization can produce fast torque response of the IM drive. This research proposes two torque optimization methods for IM systems utilizing DTC. Analysis and Matlab simulations for the proposed optimization methods prove that the torque and, consequently, the speed responses, are greatly improved. The performances of the drive system controlled by the proposed optimization methods and the traditional DTC are compared. Conversely, the effects of the parameters on the proposed optimization methods are introduced. The proposed methods greatly improve the torque and speed dynamic performances against the traditional DTC technique. However, one of the proposed optimization methods is more sensitive to IM parameter variations than the other

Active Cell Balancing Control Method for Series-Connected Lithium-Ion Battery

Power conveyance potentiality for series and parallel allied battery-packages are constrained by the wickedest cell of the string. Every cell contains marginally dissimilar capability and terminal voltage because of industrialized acceptances and functional situations. During charging or discharging progression, the charge status of the cell strings become imbalanced and incline to loss equalization. Therefore, the enthusiasm of this paper is to design an active charge balancing system for Lithium-ion battery pack with the help of online state of charge (SOC) estimation technique. A Battery Management System (BMS) is modeled by means of controlling the SOC of the cells to upsurge the efficacy of rechargeable batteries. The capacity of each cell is calculated by dint of SOC function estimated as a result of Backpropagation Neural Network (BPNN) algorithm through four switched DC/DC Buck-Boost converter. The simulation results confirm that the designed BMS can synchronize the cell equalization via curtailing the SOC estimation error (RMSE 1.20%) productively

Power sharing analysis of a new modified multi-input interleaved boost converter based on H-Bridge cells

In this paper, a new modified multi-input boost converter is proposed using H-bridge cells as building blocks and uncoupled inductors in parallel using interleaved technique as ripple reduction method. The objectives of this paper are to design a high ripple reduction and a high-performance multi-input boost converter. Different operating modes and the switch realization of the new converter are obtained. The modes of operation based on the status of the four switches. The proposed multi-input boost converter is composed of two inputs source that accommodated with some extra semiconductors, inductances and diodes to form the interleaving technique as proposed method. The proposed concept has been investigated through simulation using the MATLAB/Simulink environment. The simulation results confirm the validity of the proposed method, which can be seen as a promising new topology that ensure multi-input converter suitable for renewable energy application

Development and Modelling of Three Phase Inverter for Harmonic Improvement using Sinusoidal Pulse Width Modulation (SPWM) Control Technique

This paper describes the design of a 400 V, three-phase voltage source inverter system using Sinusoidal Pulse Width Modulation (SPWM) control technique. Pulse Width Modulation (PWM) is an internal control technique for inverters. The Sinusoidal Pulse Width Modulation (SPWM) technique is the type of PWM used in this work. The aim is to reduce the harmonic produced by the inverter. Current standards require that total harmonic distortion (THD) be minimal. A three-phase SPWM signal is implemented in order to create an output voltage which is closer to a true sine wave and reduce harmonics. The development and model were implemented using MATLAB Simulink soft-ware and hardware parameters. The addition of a low pass filter circuit aids the achievement of smoother sine waveforms and a reduced THD value of 0.17%. The proposed concept has been validated through experimentally on a laboratory prototype by using DSP TMS320F28335 real-time digital control. The experimental outcomes emphasize the authenticity of the suggested technique in reducing harmonics, which can be promising to power quality improvement

Recent Progress and Future Trends on State of Charge Estimation Methods to Improve Battery-Storage Efficiency : A Review

Battery storage systems are subject to frequent charging/discharging cycles which reduce the operational life of the battery and reduce system reliability on the long run. As such, several Battery Management Systems (BMS) have been developed to maintain system reliability and extend the battery's operative life. Accurate estimation of the battery State of Charge (SOC) is a key challenge in the BMS due to its non-linear characteristics. This paper presents a comprehensive review on the most recent classifications and mathematical models of the SOC estimation. Future trends of the SOC estimation methods are also presented

Voltage Tracking of a DC-DC Flyback Converter Using Neural Network Control

This paper proposes a neural network control voltage tracking scheme of a DC-DC Flyback converter. In this technique, a back propagation learning algorithm is employed. The controller is designed to improve performance of the Flyback converter during transient and steady state operations. Furthermore, to investigate the effectiveness of the proposed controller, some operations such as starting-up and reference voltage variations are verified. The numerical simulation results show that the proposed controller has a better performance compare to the conventional PI-Controller method

Active Charge Balancing Strategy Using the State of Charge Estimation Technique for a PV-Battery Hybrid System

: Charging a group of series-connected batteries of a PV-battery hybrid system exhibits an imbalance issue. Such imbalance has severe consequences on the battery activation function and the maintenance cost of the entire system. Therefore, this paper proposes an active battery balancing technique for a PV-battery integrated system to improve its performance and lifespan. Battery state of charge (SOC) estimation based on the backpropagation neural network (BPNN) technique is utilized to check the charge condition of the storage system. The developed battery management system (BMS) receives the SOC estimation of the individual batteries and issues control signal to the DC/DC Buck-boost converter to balance the charge status of the connected group of batteries. Simulation and experimental results using MATLAB-ATMega2560 interfacing system reveal the effectiveness of the proposed approac

Designing a control system based on SOC estimation of BMS for PV-Solar system

One of the major challenges forbattery energy stowage system is to design a supervisory controller whichcan yield high energy concentration, reducedself-discharge rate and prolong the battery lifetime. A regulatory PV-Battery Management System (BMS) based State of Charge (SOC) estimation is presented in this paper that optimally addresses the issues. The proposed control algorithm estimates SOC by Backpropagation Neural Network (BPNN) scheme and utilizesthe Maximum Power PointTracking(MPPT)schemeof the solar panels to take decision for charging, discharging or islanding mode of the Lead-Acid battery bank. A case study(SOC estimation) is demonstrated as well to depictthe efficiency(Error 0.082%) of the proposed modelusing real time data. The numerical simulation structured through real-time information concedes that the projected control mechanismis robust and accomplishes several objectives of integratedPV-BMS for instance avoiding overcharging and deep discharging manner under different solar radiation

Voltage Tracking of a Multi-Input Interleaved Buck-Boost DC-DC Converter Using Artificial Neural Network Control

This paper proposes an artificial neural network (ANN) voltage tracking of multi-input interleaved buck-boost DC-DC converter. A back-propagation algorithm topology is implemented in this paper. The control unit is implemented to ameliorate the performance of the proposed multi-input converter during transient dynamic response and steady-state operation mode. The neural network controller unit design, which is adaptive against output voltage command tracking and reference voltage variations is proposed. The proposed design has been verified through the MATLAB software. The simulation outcomes emphasized the validity and reliability of the proposed neural network technique, which would be a promising an efficient control method that ensures multi-input converter suitable for electric vehicle and renewable energy application system

Sizing of a Hybrid Photovoltaic-Hydrokinetic Turbine Renewable Energy System in East Malaysia

The difficulties faced in the extension of conventional grid electricity to remote locations elicit increased application of renewable energy (RE) sources in such locations. In locations that are in proximity to rivers or streams, microhydro hybrid RE systems (HRES) are employed. Similarly, hybrid photovoltaic (PV) /battery configurations exist. Unfortunately, micro-hydro turbines require a minimum height/head and expensive civil works during installation. Hydrokinetic turbines (HKTs) eliminate the height/head requirement and greatly reduce necessary civil work by generating electricity using the kinetic energy of water flow in a river or stream. This study used a software, Hybrid Optimization of Multiple Energy Resources (HOMER), to simulate and obtain the optimal size and configuration of a hybrid PV/HKT/Battery storage system for Kampung Git in East Malaysia. Techno-economic comparison of the system is done with a PV/Battery and a standalone diesel generator (DG) system. The levelized cost of energy (LCOE) and the total net present cost (NPC) are the primary indices used for comparison purposes. The optimal configuration from simulations has 89.9 kWp of PV, two 3.5 kW HKTs and 132 kWh of battery storage. Also, economic results obtained indicate that the LCOE of 1.21 RM/kWh and NPC of RM 1,431,000 for the PV-HKT-battery configuration bested those for the PV-battery and standalone DG systems by 165 % and 27 % respectively. This optimal configuration is more environmentally friendly and highlights the role of the HKT in reducing battery usage and wear in addition to achieving lower LCOE and NPC values