Simscape Toolbox Research Articles

The Influence of Solar Irradiance and Temperature on The Pll-Synchronized Inverter Within Grid-Connected PV Systems

This study assesses the influence of solar irradiance and temperature on αβPLL synchronized inverters by investigating their intricate relationship within grid-connected PV systems. The intermittent nature of the DC side of these systems can significantly impact their performance. However, the extent of this impact remains uncertain when employing the stationary reference frame PLL (αβPLL) algorithm for synchronization with the utility grid. Employing simulation in MATLAB 2020a and a Model Based Design approach in the Simscape toolbox of SIMULINK, we conducted this investigation through two test scenarios: one with constant solar irradiance and varying temperature, and the other with varying solar irradiance and constant temperature. Our results indicate that fluctuations in solar irradiance and temperature have minimal effects on the output parameters of grid-connected PV systems when synchronized with the stationary reference frame PLL (αβPLL) algorithm. This conclusion is supported by the total harmonic distortion values, which all fall within the specified limits of IEEE Standard 929- 2000. These findings underscore the potential of αßPLL synchronization as a promising technique, capable of effectively synchronizing grid inverters even in the presence of DC input distortion. This proficiency in grid integration holds promise for enhancing the integration of renewable energy sources into the grid, thereby bolstering power availability for household distribution.

PEM fuel cell and supercapacitor hybrid power system for four in-wheel switched reluctance motors drive EV using geographic information system

In recent years, Electric Vehicles (EVs) powered by a Proton Exchange Membrane Fuel Cell (PEMFC) which has high energy density and efficiency have become an attractive solution for the automotive industry. However, since the power density of the PEMFC is not high enough for different road conditions such as accelerating and going uphill, a supercapacitor (SC) is preferred as the auxiliary energy source for high power density in EVs. Thus, in this paper, a hybrid power system consisting of the Fuel Cell (FC) and SC for a Four-Wheel Drive Electric Vehicle (4WDEV) is proposed. Since energy requirement of the EV depends on the travel route, an effective Energy Management System can be designed by using a Geographic Information System (GIS). According to the road trajectory, the power requirement of the EV is estimated and thus, energy consumption is reduced. The proposed system is validated by using the Matlab Simscape Toolbox.

Comprehensive modeling of ventilation systems for Nearly Zero Energy Buildings

In the present work, a lumped-parameter model of a multifunctional ventilation unit for residential applications was developed in the Simulink environment, also relying on the Simscape toolbox with Moist Air and Two-Phase fluid libraries. A simple, yet effective method to analyze and optimize the efficiency of the combined HVAC – air distribution system is proposed. To investigate the impact of boundary conditions on system performance, a parametric study of different installation conditions was also carried out, including outdoor air and indoor air temperature, humidity, static pressure, filter fouling, pressure drop in the intake and distribution ducts. The model highlights a strong decrease in the useful cooling/heating heat flow rate produced by the system as the installation and maintenance conditions become more challenging.

AI Algorithm Based Green Hydrogen Static Compensator for Harmonic Mitigation, Power Balancing, and Power Factor Correction in Nano-Grids

Nano-grids are emerging as a vital solution for sustainable energy distribution, particularly in integrating intermittent renewable energy sources. In this context, this research paper aims to address the challenges faced in Nano-grids through the innovative use of a Green Hydrogen Static Compensator (GHSC). The purpose of this study is to overcome issues related to harmonic pollution, power factor correction, and real power balancing within the Nano-grid system. The method employed involves a two-fold approach. Firstly, a modified instantaneous p-q algorithm is proposed to enhance the effectiveness of GHSC. Secondly, artificial intelligence (AI) algorithms, including deep neural networks, random forest, and XGBoost, are utilized to further refine the system's accuracy. These AI algorithms were trained using the modified p-q method, and the simulation of GHSC was performed using SimScape Toolbox in MATLAB-Simulink. The results of the study clearly demonstrate that the proposed GHSC approach, combined with the AI algorithms, outperforms traditional methods in terms of effectiveness in mitigating harmonic pollution and correcting power factors. However, it is noted that the current implementation lacks flexibility for real-time self-learning. In conclusion, the paper underscores the novelty and potential of the GHSC in conjunction with AI algorithms, while also pointing out areas for future research. Specifically, future efforts may focus on developing an automatic weight updating deep neural network that responds to real-time feedback of THD, power factor, and frequency, enhancing the system's adaptability and efficiency.

A Lumped-Parameter Model of a Smart Ventilation unit for nearly Zero Energy Buildings

In the present work, a simple model of a ventilation unit used for residential purposes is proposed, which was developed by means of MATLAB Simulink and the Simscape toolbox, also including the Moist Air and Two-Phase fluid libraries. This study falls in the realm of air conditioning in nearly Zero Energy Buildings. The model presented here is focused mostly on the aeraulic system. A parametric analysis of various installation conditions was conducted to assess and enhance the combined heat pump and the air distribution system performance, under various operating conditions. Therefore, the overall approach included several parameters, such as outdoor and indoor air temperature, humidity, static pressure, pressure drop in the intake and the distribution ducts, and filter fouling. The model serves as a predictive tool to evaluate the effectiveness of the whole system, in both design and off-design conditions; notably, critical conditions are emphasized, which are associated to severe fouling conditions, making the use of an additional fan ineffective.

Design and simulation of a TTRH-EV supervisory controller for a proton SAGA 1.3

This paper presents modeling and control design steps towards the vehicle hybridization process. The objectives are: a) to model a retrofitted proton SAGA, which is a through-the-road HEV; and b) to design and implement a supervisory control unit for this vehicle. The electric powertrain components required for conversion are sized using the ADVISOR software package. Physical models of both powertrains were modeled using the MATLAB Simscape toolbox and validated for their fidelity. A supervisory controller design and implementation for retrofitted TTRH-EV SAGA is based on the BSFC map and OOL of the engine. The control objective is to restrict engine operation within its optimum window. The controller was implemented using the MATLAB Stateflow toolbox. The complete model of the retrofitted TTRH-EV SAGA, together with the supervisory controller, was tested using standard drive cycles, and the results are presented.

Thermal-Electric Modeling: A New Approach for Evaluating the Impact of Conservation Voltage Reduction on Cooling Equipment

It has been suggested in the literature that by reducing the incoming voltage at a distribution feeder head or at the supply side of buildings, significant electricity savings can be achieved. This technique is called Conservation Voltage Reduction (CVR). Data-based analysis with and without CVR is primarily used to support such assertions, which does not explain the physics behind reduction in energy consumption with CVR. This paper presents a new approach for evaluating the impact of CVR on cooling equipment. In this approach, a thermal-electric model of the cooling process is developed in MATLAB’s SIMSCAPE toolbox that can be used to explain the physics behind energy reduction with CVR. This model includes an accurate model of a compressor coupled to an induction motor whose supply voltage can be varied to simulate CVR. Simulations performed using this model show that the Coefficient of Performance (COP) of cooling equipment improves with a reduction in supply voltage. However, the energy lost in the motor windings may nullify the impact of the improvement in the COP and render the CVR programs ineffective if the range of speed change is small over the allowable voltage change. The simulation results show an increase in energy consumption of 4% at 90% rated voltage compared to the energy consumed at the rated voltage. However, if variable frequency drives-based cooling equipment is appropriately controlled, it is possible to reduce their net energy consumption using CVR. Simulations performed keeping the ratio of the supply voltage and the frequency constant showed a reduction in energy consumption of 2.5% at 90% rated voltage compared to the energy consumed at the rated voltage. Thermal-electric modeling of building cooling equipment is, therefore, vital to accurately evaluating the benefits of CVR as smart, power electronics-based end-use equipment is globally adopted.

Cooling performance of thermal management system for lithium-ion batteries using two types of cold plate: Experiment and MATLAB/Simulink-Simscape simulation

The thermal management system for lithium-ion batteries (LIBs) was investigated to improve the operating performance of LIBs. Experiments with two battery packs that integrate two different types of cold plates, Type I and Type II, were conducted to compare the cooling efficiencies of the battery thermal management system (BTMS). The interior heat generation of the battery modules was analyzed. Because of safety concerns, the battery pack in the experiment was replaced by heaters. A comparative experiment with a cell and heater was conducted under the same parameter conditions to compare the heating properties. The MATLAB/Simulink - Simscape toolbox (version R2020b) was used to simulate the thermal characteristics of a cylindrical cell and a battery pack. The thermal resistance was analyzed to investigate the cooling efficiency of the cold plates. As the results, the heater produced 10% higher temperature than the Li-ion cell under same conditions. In Type I, the thermal resistance decreased with an increase in the C-rates, whereas in Type II, it remained constant at 0.001. The simulation results were verified accurately through comparison with experimental results. Both experimental and simulation results show cold plate Type II has outstanding cooling performance than Type I.

Switch Fault Detection and Localization for T-Type Converter

Over the past decade, multilevel converters have received considerable interest in medium voltage applications. A large number of active switches in a multilevel converter increases the probability of switch failure and decreases the reliability of the system. An open switch fault can lead to a malfunction of the whole system and should be diagnosed as soon as possible. In this paper, an open-switch fault diagnosis method for a five-level H-Bridge T-type converter is presented. The proposed fault detection method and the fault localization algorithm are based on the switching patterns and the converter output voltage level observation. This approach is capable to detect and localize an open circuit fault for all switches. First, it is validated by simulations in Matlab Simulink and Simscape toolbox environments. Experimental results are also presented and discussed to validate the simulation results.

A novel approach to design of a power factor correction and total harmonic distortion reduction-based BLDC motor drive

This study describes a novel approach to design of a power factor correction (PFC) and total harmonic distortion (THD) reduction-based brushless DC (BLDC) motor drive. The drive was designed to obtain a reduced THD for PFC. The basic design of the BLDC motor drive contains an AC voltage source as input for a diode bridge rectifier. The output DC voltage is filtered out to reduce ripples. The smooth DC output voltage is supplied to the modified Zeta converter. The output voltage of the modified Zeta converter is controlled by using pulse width modulation (PWM). The modified Zeta converter is utilized in discontinuous inductor current mode (DICM) for better power factor. This controlled DC voltage is supplied to the voltage source inverter (VSI) as input. The VSI is designed to convert input DC into a suitable AC voltage source. The output voltage of the VSI depends upon switching patterns applied to power transistors generated by space vector PWM. Additionally, the output of the VSI is supplied to the BLDC motor for speed control. The main purpose of this paper is to simulate and assess BLDC motor function via the MATLAB/Simulink environment, using SimPowerSystems and the Simscape toolbox, with the goals of improved power factor, lower THD, and better speed control. The PFC modified Zeta converter topology produced the best power factor, currently 0.981, which is better than other topologies, with a THD of only 9.81%, the lowest of all three topologies, which demonstrates the significance of the proposed model.

Enhancing low voltage ride through capability of grid connected DFIG based WECS using WCA-PSO tuned STATCOM controller

This paper investigates the utilization of a STATCOM to enhance the LVRT capability of a 9 MW DFIG based Wind Power Plant (WPP) during grid faults. The STATCOM under investigation is tuned using the Water Cycle Algorithm (WCA), Particle Swarm Optimization (PSO) and a hybrid algorithm of both WCA and PSO. Simulations are carried out in MATLAB programming software, using SimScape toolbox. Performance analysis is done by investigating the ability of the test system to ride through voltage sags on the grid side, with incorporation of the STATCOM tuned using WCA, PSO and further with the hybrid WCA-PSO algorithm. To confirm effectiveness of the proposed algorithm, simulation results for the three scenarios are compared. Results show that LVRT capability of the Danish power system was met for L-G faults. However, without a STATCOM, the WPP could not ride through LLL-G faults. When STATCOM was incorporated, LVRT capability requirements were met. Voltage fluctuations reduce from 17% to 3%, without STATCOM and with WCA-PSO tuned model, respectively, during L-G faults. During LLL-G faults, voltage magnitude fluctuates from 60% to 25%, without STATCOM and with WCA-PSO tuned model respectively. WCA-PSO tuned STATCOM also resulted in the least voltage, active and reactive power overshoots.

Assessment of Electrical Power Generation of Wave Energy Converters With Wave-to-Wire Modeling

Direct-drive wave energy converter (WEC) and buoy control algorithms have shown great potential for renewable wave energy extraction in ideal conditions. However the actual power take-off (PTO) impacts are barely considered in the WEC design. This paper highlights the demands of designing the WEC wave-to-wire control from a global point of view by studying the actual PTO impacts. A permanent magnet linear electrical machine (LEM) PTO unit is simulated and controlled to fulfill the WEC buoy control requirements. Several state of the art control algorithms, which include singular-arc (SA) control, shape-based (SB) control, model predictive control (MPC), and proportional-derivative (PD) control, are applied to maximize the wave energy production (mechanical energy). Multiple types of electrical PTOs, including ideal PTO, unlimited PTO and limited PTO, are all implemented to evaluate WEC wave-to-wire performances. Further, the PTO copper loss model and the PTO actual efficiency maps are introduced and studied to improve the electrical PTO operation efficiency. To further assess the control schemes in various wave conditions, one-year PacWave ground-truth data is applied as well. Numerical simulations are conducted using MATLAB/Simulink and the Simscape toolbox. The electrical PTO unit is composed of a LEM, an ideal inverter, and an ideal energy storage system. The results show that the actual PTO will impact the constrained controls (MPC and SB) less comapring to unconstrained controls (SA and PD). Although SB can produce the maximum energy with the limited PTOs, it is not robust for all wave conditions. At the end of the paper, the possible solutions for improving the WEC wave-to-wire performances are also provided.

A Novel Combined Control Strategy for a Two-Stage Parallel Full-Wave ZCS Quasi Resonant Boost Converter for PV-Based Battery Charging Systems with Maximum Power Point Tracking

This work deals with the design and validation of a combined control strategy to satisfy the requirements for both soft switching and Maximum Power Point Tracking (MPPT) for a Photo Voltaic based (PV-based) battery charging system. The proposed controller is employed for a two-stage parallel full-wave Zero Current Switching (ZCS) quasi resonant boost converter to obtain maximum voltage using Perturb and Observation (P&O) method. The controller utilizes frequency modulation to regulate the output voltage, considering any changes experienced due to the intermittent nature of the PV system. Operating principles of the tow-stage parallel boost converter are thoroughly analyzed, and Matlab Simscape toolbox and its real-time workshop capability is utilized to evaluate the performance of the proposed controller for a battery charging system.

A novel modelling and control strategy for a full-wave ZCS quasi-resonant boost converter for a PV-based battery charging system

In this paper, a novel modelling and control strategy is proposed for a DC-DC quasi-resonant boost converter utilised in a photovoltaic-based (PV-based) battery charging system. The MOSFET switch of the boost converter is operated at zero current using a resonant tank, providing soft-switching functionality, to reduce the switching losses experienced by conventional boost converters. The principles of operation of the utilised converter are analysed in detail and a characteristic function representing the model of quasi-resonant converter circuit is derived. This model is then used to design and implement a frequency control technique, which will maintain a constant DC voltage at the output stage of the converter to charge the battery. Simulation studies are conducted using MATLAB Simscape toolbox to evaluate the performance of the proposed controller. Simulation results validate the soft-switching functionality of the converter and its ability to reach and maintain the desired output voltage for charging a battery load in the presence of varying input voltage generated by a PV system with intermittent nature.

Parameter Estimation for Multibody System Dynamic Model of Delta Robot From Experimental Data

Abstract Delta robot is a type of parallel systems which has a complex nonlinear structure suitable to apply different mathematical algorithms. In recent years, researchers have been focused on the parameter estimation of a nonlinear mechanical system to compute optimal system parameters. However, few researchers tried to evolve the delta robots in such a system. In this contribution, we present a procedure for parameters estimation in multibody system model of the delta robot system. Firstly, the multibody model of the delta robot is formulated using Lagrange formulation. Then, the Matlab Simscape Toolbox is used to construct and verify the multibody model. Finally, a parameter estimation module is used to estimate optimal parameters by comparing the simulated model output with experimental measured data. The type of delta robot used in this study is D3S-800 and utilized for the multibody model validation. Detailed experimental results show that the modeled system is validated, which provides a reference for the dynamic optimal design of a delta robot system.

A novel modelling and control strategy for a full-wave ZCS quasi-resonant boost converter for a PV-based battery charging system

In this paper, a novel modelling and control strategy is proposed for a DC-DC quasi-resonant boost converter utilised in a photovoltaic-based (PV-based) battery charging system. The MOSFET switch of the boost converter is operated at zero current using a resonant tank, providing soft-switching functionality, to reduce the switching losses experienced by conventional boost converters. The principles of operation of the utilised converter are analysed in detail and a characteristic function representing the model of quasi-resonant converter circuit is derived. This model is then used to design and implement a frequency control technique, which will maintain a constant DC voltage at the output stage of the converter to charge the battery. Simulation studies are conducted using MATLAB Simscape toolbox to evaluate the performance of the proposed controller. Simulation results validate the soft-switching functionality of the converter and its ability to reach and maintain the desired output voltage for charging a battery load in the presence of varying input voltage generated by a PV system with intermittent nature.

Development of a three-bladed horizontal axis wind turbine with active control by using a programmable logic controller

For the increasing the physical efficiency, useful life and avoid accidents in wind turbines, it is very useful to implement a pitch control on the blades that help as an aerodynamic brake and orientation in the base to follow the wind direction. The main goal of this paper was to develop a digital controller on the wind turbine blades that allows to keep the constant angular velocity and monitor the orientation of the wind. A computer-aided design software was developed for allowing the aerodynamic analysis by using Solid Works® software based on a flow simulation tool. On the other hand, a MATLAB model was created employing Simulink tool and the Simscape toolbox with typical data from a 2MW wind turbine whereas the electrical and mechanical dynamics and control feedback were calculated having as input parameters the wind direction and speed. Consequently, a prototype was designed in 3D which was implemented to make the different tests. For lab experimentation, a fuzzy control algorithm was developed in structured control language and then implemented using the S7-1200 PLC. The trials with programmable logic controller and the fuzzy algorithm were satisfactory, which could be a basis for the optimization of the performance of a three-bladed horizontal axis wind turbine.

On the efficacy of charging a battery using a chaotic energy harvester

Introduction of stiffness nonlinearities to broaden the frequency bandwidth of vibratory energy harvesters has the adverse influence of complicating the response behavior of the harvester. As such, unlike linear energy harvesters, for which direct performance metrics can be easily developed, it is not always easy to develop metrics to assess the performance of nonlinear energy harvesters. One particular issue arises when the harvester operates in its chaotic regime resulting in an unpredictable response, under which the harvester’s performance is hard to assess. In this paper, we present a statistical technique to estimate the charging time of a battery being charged by a chaotic vibratory input. The proposed approach, which accounts for the presence of a rectifier circuit, a buck converter, and the dependence of the battery voltage on the state of charge, only requires the knowledge of the probability density function of the open-circuit voltage of the harvester. Using the proposed technique, it is also possible to obtain the optimal duty cycle of the buck converter. Results of the proposed methodology were compared to numerical data generated using MATLAB’s Simscape toolbox demonstrating excellent agreement. Not only does the proposed technique provide a valuable tool to assess performance of a chaotic energy harvester, but it can also be easily applied to other chaotic and random energy sources.

A comparative study of two simulation tools for the technical feasibility in terms of modeling district heating systems: An optimization case study

District heating dynamic models arise as an alternative approach to in-situ experimental investigations. The main advantage of dynamic modeling and simulation is the possibility to avoid technical and operational risks that might occur during in-situ experimental investigations (e.g. heat demand is not met, damages in the energy systems etc.). Within this study, the authors present two models for an existing district heating system in Cottbus, Germany. One model is developed using the tool EBSILON Professional, while the other one is developed using the Simscape toolbox for physical modeling in Matlab/Simulink. The models were experimentally validated against measured data from the considered district heating system. The results show that the Simscape model has a better fit and better response than the EBSILON model. Yet, some discrepancies were found between the measured and the simulated data and, therefore, the uncertainties of the models were addressed. A comparative study between both tools is presented. The EBSILON models permit only unidirectional flow, whereas the Simscape toolbox permits reverse flow. Nevertheless, the EBSILON model outperforms the Simscape model in computation time. In addition, this study presents an approach for dynamic thermo-hydraulic modeling of district heating networks. This approach is utilized to examine the role of district heating networks as heat storage as an optimization configuration. The numerical results show less start-ups for additional heat sources. Yet, higher heat losses from the network are observed due to the installation of unburied pipelines.

Comprehensive improvement of artificial fish swarm algorithm for global MPPT in PV system under partial shading conditions

Due to the non-linear characteristics I–V of the photovoltaic (PV) curve, the tracking of the maximum power point (MPP) under partial shading (PS) conditions can sometimes be a challenging task. This paper presents a modified artificial fish swarm algorithm (AFSA) for MPP tracking (MPPT) in PV modules under PS. In this algorithm, the AFSA optimized by particle swarm optimization (PSO) algorithm with extended memory (PSOEM-FSA) is improved by hybridizing it with adaptive visual and step, and the resulting algorithm is a comprehensive improvement on the AFSA (abbreviated as CIAFSA). Combining the searching capabilities of the PSOEM-FSA and the self-learning ability of adaptive visual and step for AFSA, CIAFSA is developed. To validate the effectiveness of this novel MPPT technique, the PV system along with the proposed MPPT algorithm is simulated using the Matlab/Simulink Simscape toolbox. Results show that the proposed approach is more effective in MPPT in PV systems under PS conditions when compared with other methods in searching precision.