Co-simulation Technique Research Articles

Temperature uncertainty modelling with proxy structural data as geostatistical constraints for well siting: an example applied to Granite Springs Valley, NV, USA

Utilizing existing temperature and structural geology information around Granite Springs Valley, Nevada, we build 3D stochastic temperature models with the aims of evaluating the 3D uncertainty of temperature and choosing between candidate exploration well locations. The data used to support the modelling are measured temperatures and structural proxies from 3D geologic modelling (distance to fault, distance to fault intersections and terminations, Coulomb stress change and dilation tendency), the latter considered ‘secondary’ data. Two stochastic geostatistical techniques are explored for incorporating the structural proxies: cosimulation and local varying mean. With both the cosimulation and local varying mean methods, many equally-likely temperature models (i.e. realizations) are produced, from which temperature probability profiles are calculated at candidate well locations. To aid in choosing between the candidate locations, two quantities summarize the temperature probabilities: V prior and entropy. V prior quantifies the likelihood for economic temperatures at each candidate location, whereas entropy identifies where new information has the most potential to reduce uncertainty. In general, the cosimulation realizations have smoother spatial structure, and extrapolate high temperatures at candidate locations that are located along the direction of the longest spatial correlation, which are down dip from existing temperature logs. The smooth realizations result in tight temperature probability profiles that are easier to interpret, but they have unrealistic temperature reversals in some locations because of the dipping ellipsoid shape created and that the cosimulation technique does not enforce a conductive geothermal gradient as a baseline (i.e. linearly increasing temperature with depth). The local varying mean results produce realizations with more realistic geothermal gradients, with temperatures increasing downward since a depth-temperature relationship is included. However, because they have much noisier spatial nature compared to cosimulation, it is harder to interpret the temperature probability profiles. The different local varying mean results allow the geologist to determine which proxy (e.g. dilation v. distance to fault termination) should be used given the specific geothermal system. In general, V prior from local varying mean results identify locations that are close to high values for the structural proxies: areas with higher probabilities for higher temperatures. The entropy results identify where uncertainty is greatest and therefore new drilling information could be most useful. Though these techniques provide useful information, even when applied to areas of sparse data, our comparison of these two techniques demonstrates the need for new geothermal geostatistics techniques that combine the advantages of these two methods and that are tailored to the spatial uncertainty issues inherent in geothermal exploration.

Vibration Reduction of Robot End Effector Based on Co-simulation Method

Hydraulic cylinder replacement robot as a new type of engineering machinery has been increasingly used, but its end effector encounters vibrations in the process of clamping the object, so the accuracy of disassembling and assembling the cylinder will be reduced, thus reducing the replacement efficiency and affecting the user’s experience. To address this problem, virtual prototyping technology is used to study the cylinder disassembly process under real working conditions. We use the 3D modeling software Solidworks to construct a model of the cylinder replacement robot. After that, kinematic analysis of the model is carried out, then a dynamics model is built in multi-body dynamics simulation software ADAMS to simulate the process of the robot grasping the object, as a consequence, the trajectory of the end effector is calculated. A controlled dynamic model is established with Simulink and Adams by using the co-simulation technique, and optimization is carried out by using the model. Results show that the optimized control parameter can effectively reduce the end effector vibration and improve the stability and accuracy of the work.

Modeling and Simulating Wind Energy Generation Systems by Means of Co-Simulation Techniques

This paper presents the development of a wind energy conversion system co-simulation based on the Functional Mock-up Interface standard aiming at contributing to the development of co-simulation of large electrical power systems by means of open-source and standardized computational tools. Co-simulation enables the computational burden of a monolithic simulation to be shared among several processing units, significantly reducing processing time. Through the Functional Mock-up Interface standard, developed models are encapsulated into Functional Mock-up Unit, providing an extra means for the protection of intellectual property, a very appealing feature for end users, both in industry and academia. To achieve the decoupling of the subsystems, the Bergeron ideal transmission line model will be used, with travel time equal to the simulation time-step. The computational performance and effectiveness of the proposed co-simulation technique was evaluated with a wind power plant with 50 wind turbines. The system digital models were developed into Modelica language, while co-simulation was implemented in Python.

Digital twins of multiple energy networks based on real-time simulation using holomorphic embedding method, Part I: Mechanism-driven modeling

Digital twins can provide system operators with a new way to design, operate, and maintain highly-interconnected multiple energy networks (MEN) by integrating interdisciplinary models using the co-simulation technique and implementing faster-than-real-time simulation enabled by powerful modern computing facilities. This series of papers presents digital twins of MEN capable of real-time simulation facilitated by the holomorphic embedding method. As Part I of this series of papers, mechanism-driven modeling is concentrated to guarantee that high-resolution solutions are computationally accessible. A holomorphic embedding-based model (HEM) for MEN is proposed, which uses time-dependent holomorphic functions to depict the time-varying dynamics of gas and heat flows. A convergence radius model (CRM) is proposed to obtain the essential convergence information of HEM, thereby improving its computational performance to match the real-time requirement. Finally, the effectiveness of the proposed method is validated in a medium-sized study case. The results show that the proposed method offers a significant computational benefit with competent precision when compared to standard differential methods, laying the groundwork for the realization of MEN’s digital twins.

Cosimulation of Integrated Organic Photovoltaic Glazing Systems Based on Functional Mock-Up Unit

This study presents an approach to simulating building-integrated photovoltaic glazing systems composed of semitransparent organic photovoltaic (ST-OPV) elements. The approach consists of a mathematical cosimulation model based on the energy balance of complex glazing systems, considering heat transfer as conduction, mixed convection, and radiation effects. The cosimulation method is based on a functional mock-up unit (FMU) developed in Python and the building simulation program Domus. This work aims at presenting a cosimulation technique that can be easily applied to building energy simulation tools for the assessment of photovoltaic energy generation in glazing systems. The cosimulation glazing model was verified according to ANSI/ASHRAE Standard 140-2011, and the zone temperature was kept within with a root medium square error (RMSE) of 1.45 °C. The simulated building with an ST-OPV system showed promising results and could be applied to near-zero energy buildings since each 6-m2 glazing has a power generation of around 77 W, equivalent to 9% of available solar resource.

Numerical investigations on high-speed turbo-compressor rotor systems with air ring bearings: Nonlinear vibration behavior and optimization

Regarding aerodynamic bearings, mainly two basic types can be distinguished: air bearings with a rigid housing and air foil bearings with an elastic supporting structure. Here, a modified bearing concept -- called air ring bearing -- is investigated, which may be considered as a further development of rigid air bearings or as a combination of the two basic bearing types. The idea of air ring bearings is to insert a ring-shaped bearing bushing between the shaft and the foil structure. Alternatively, a visco-elastic supporting structure (e.g., an elastomer) can be applied to connect the bushing ring with the housing. In the first case, external dissipation is mainly generated by dry friction. In the latter case, viscous damping is used to provide external dissipation. Due to the external friction/damping generated by the ring mounting structure, rotor systems with air ring bearings can be operated above the linear threshold speed of instability so that stable self-excited vibrations with moderate amplitudes can be achieved in the complete speed range. Here, a detailed transient co-simulation model for rotor systems with air ring bearings is presented. The rotor is represented by a multibody model. The air films of the two bearings are represented by two nonlinear time-dependent finite element systems. The multibody model and the two finite element subsystems are solved simultaneously by means of an explicit sequential co-simulation technique. Due to the strong nonlinearities, the system shows interesting vibration and bifurcation effects, which are investigated in detail with the help of run-up simulations.

The impact of urban vegetation morphology on urban building energy consumption during summer and winter seasons in Nanjing, China

Studies have shown that urban vegetation can be an effective strategy for reducing energy consumption in urban buildings by regulating the microclimate and shading solar radiation on building surfaces. However, an understanding of the potential energy savings of vegetation morphological planning at the urban scale is still lacking, particularly regarding the quantitative correlation between urban vegetation morphology and its impact on urban building energy use. The morphology of the metropolitan area in Nanjing, a typical hot summer/cold winter city in eastern China, was statistically analyzed, and 40 urban building-vegetation morphological prototypes were extracted. Using the proposed co-simulation technique for urban microclimate and urban building energy, the summer and winter building energy consumption of the prototypes were simulated. A quantitative analysis was conducted on the relationship between urban vegetation morphology indexes and building energy consumption. The results indicate that strategically planned urban vegetation morphology can significantly reduce urban building energy consumption. In the summer, vegetation close to the geometric center of the site, uniformly distributed and highly mixed with buildings, can significantly reduce the building energy consumption; in the winter, the opposite is true. The presented findings provide designers and planners with strategies for incorporating urban vegetation morphology design into the construction of energy efficient cities.

Vibration reduction of monopile-supported offshore wind turbines based on finite element structural analysis and active control

A finite element (FE) structural analysis based on a commercial software is combined with an observer-based active control to study the real-time performance of an Active Tuned Mass Damper (ATMD) in reducing the fore-aft vibration of a monopile-supported offshore wind turbine (OWT). Firstly, a reduced order MDOF model was established and used to design a Linear Quadratic Regulator. Secondly, the controller was combined with an observer to minimize the required number of sensors. Thirdly, co-simulations between the high-fidelity FE software and the optimized controller were performed. The aim was to test the robustness of the MDOF model-based controller in terms of OWT vibration reduction when the ATMD is used within a structural FE commercial software. The optimized controller applied to the FE mechanical model of the OWT proved to be efficient, the RMS reduction ratio of the tower top displacement being around 60%. Given the increasing size and capacity of OWTs, the proposed co-simulation technique combining a large deformation structural analysis based on a FE commercial software with an optimized observer-based active control can serve as a tool for the final design stage of the next-generation dynamically-sensitive OWT structures to accurately capture their dynamic responses in the presence of ATMDs.

PIL Implementation of Feedback Linearisation-SVM Control of 3-Phase Multifunctional Grid-Tied Solar PV Integrated UPQC

In this paper, an implementation of a feedback linearisation-based on SVM control of a multifunctional unified power quality conditioner (UPQC) combined with a photovoltaic generator (PVG) using STM32F429I-DISC DSP board has been presented. Further, The PVG-UPQC is acting as a universal conditioner for power quality enhancement and renewable energy integration simultaneously with harmonics reduction in both grid voltage and current. Furthermore, the system can also compensate reactive power in presence of nonlinear loads. The presented system is made up of a shunt active power filter which acts as a current harmonics compensator in addition to a series filter that compensates voltage harmonics and fluctuations such as voltage sag/swell. In order to enhancing the PVG-UPQC performances, a nonlinear feedback linearisation control technique combined with SVM controller is applied. The performance of the suggested control scheme is validated by extensive PIL co-simulation technique. The obtained results prove the high performances and reliability of the presented system in the case of nonlinear load variations as well as eliminating voltage and current harmonics. These results accomplish the superiority and effectiveness of those obtained by a compared to a conventional PI controller.

A novel hybrid GWO–PSO-based maximum power point tracking for photovoltaic systems operating under partial shading conditions

One of the major challenges in photovoltaic (PV) systems is extracting the maximum power from the PV array, especially when they operate under partial shading conditions (PSCs). To address this challenge, this paper introduces a novel hybrid maximum power point tracking (MPPT) method based on grey wolf optimization and particle swarm optimization (GWO–PSO) techniques. The developed MPPT technique not only avoids the common disadvantages of conventional MPPT techniques (such as perturb and observe (P&O) and incremental conductance) but also provides a simple and robust MPPT scheme to effectively handle partial shading in PV systems, since it requires only two control parameters, and its convergence to the global maximum power point (GMPP) is independent of the search process's initial conditions. The feasibility and effectiveness of the hybrid GWO–PSO-based MPPT method are verified via a co-simulation technique that combines MATLAB/SIMULINK and PSIM software environments, while comparing its performance against GWO, PSO and P&O based MPPT methods. The simulation results carried out under dynamic environmental conditions have shown the satisfactory effectiveness of the hybrid MPPT method in terms of tracking accuracy, convergence speed to GMPP and efficiency, compared to other methods.

Hybrid model for exhaust systems in vehicle thermal management simulations

AbstractUsing Vehicle Thermal Management (VTM) simulations to predict the thermal load experienced by components is a popular method within the automotive industry. The VTM simulation approach is fast becoming equivalent to conducting thermal load tests with prototypes for vehicles powered by internal combustion engines. This is especially true in the early development phase of the vehicle. The accuracy of the VTM simulations plays a pivotal role at them being accepted as an eventual replacement for physical testing. The correct prediction of thermal loads in VTM simulations depends on a multitude of different parameters, but the modelling of the exhaust system plays a central role in it. This is because the exhaust gas, and with it the exhaust system, is the primary source of heat in a vehicle powered by an internal combustion engine. The developed approach not only needs to be accurate but also modular enough to allow for different exhaust configurations to be tested. It also needs to be capable of integration into any VTM simulation workflow while maintaining an industrially acceptable turnaround time. This paper explores a new methodology to achieve these requirements. A 1D/3D hybrid approach to exhaust system modelling is presented. In this, the components that have an enthalpy change of the exhaust gas, such as the turbocharger, have been modelled as 1D and simple components such as pipes have been modelled in 3D. This has the advantage of combining the speed of 1D simulations with the spatial accuracy of 3D simulations. The method uses a unique three-code co-simulation technique for full vehicle VTM simulations. The coupling is between a 3D CFD software, a 1D simulation tool, and a Finite Element based thermal solver. The methodology was validated against experimental data for multiple loadcases. The results show good agreement with experiment within acceptable tolerances.

Offline adaptation of co-simulation time steps by leveraging past co-simulation runs in multi-level mechatronic systems

Modeling and simulation of mechatronic systems require a multi-disciplinary approach as several physical domains interact with each other. Due to this heterogeneity, each domain can benefit from a dedicated time integration strategy as well as modeling formalism to control the error in simulation and reduce computational overhead. Current multi-rate adaptive time-stepping approaches disregard the system dynamics knowledge obtained in previous simulations and adapt the time steps at run-time as a black-box model. Although current multi-rate adaptive time-stepping approaches do not exploit the time scale of the physics of each domain, this information can be exploited in co-simulations by having a predefined multi-rate time integration approach in design space exploration and parameter identification applications, which involve repeated simulations with similar dynamics. In this study, an offline adaptive co-simulation technique is introduced. The proposed method adapts the communication and time integration time steps before the simulation using the estimated error data from past co-simulation runs. The offline adaptive co-simulations performed faster against the run-time adaptive co-simulations for comparable accuracy levels in 1D and multi-level mechatronic systems with changing loading and initial conditions.

Multiscale co-simulation of deep brain stimulation with brain networks in neurodegenerative disorders

Deep brain stimulation (DBS) has been used successfully as symptomatic treatment in several neurodegenerative disorders, including Parkinson’s disease (PD). However, the mechanisms of its activity inside the brain network are unclear. Many virtual DBS models investigate the dynamics of a subnetwork surrounding the basal ganglia (BG) as a spiking network has been attracting a growing body of research in neuroscience. Connectomic data, on the other hand, show that DBS has a wide range of impacts on many distinct cortical and subcortical sites. Notably, the nonlinear reaction–diffusion multiscale mathematical models demonstrate the effectiveness of capturing crucial disease characteristics and are used to simulate large-scale brain activity. The BG and associated nuclei comprise many subcortical cell groups in the brain, and their couplings commonly revealed MRI-based assessments of the strength of anatomical connections. We have developed a hybrid modeling formalism and a unique co-simulation technique that allows us to compute electrodiffusive ion dynamics for the cortex–BG–thalamus (BGTH) brain network model within a large-scale brain connectome. We collect data from the Human Connectome Project (HCP) and propose a closed-loop DBS approach based on the brain network model. Moreover, we select regions in the parameter space that reflect the healthy and Parkinsonian states as well as the impact of DBS on the subthalamic nucleus (STN) and globus pallidus internus (GPi) neurons. We predicted that if we apply the DBS to the system described by the temporal model, the brain maintains a healthy state until 0.05ms for STN neurons and 0.035ms for GPi neurons. A local regulatory mechanism known as feedback inhibition control (FIC) points to the existence of underlying network dynamics in the white matter of connected brain regions. The model showed unanticipated effects that in the presence of diffusion, the human brain maintained a healthy state for a long time after the DBS had been applied to STN and GPi neurons. This research helps us better understand the changes in brain activity caused by DBS and enhances this clinical therapy, thus shedding new light on the importance of DBS mechanisms in BGTH brain network models of neurodegenerative disorders.

The impact of the spatio-temporal morphology of urban green infrastructure on urban building energy consumption: A case study in the hot-summer-cold-winter climate

Studies have confirmed that urban green infrastructure (UGI) profoundly impacts urban building energy consumption by regulating urban microclimate, providing shading to buildings, and other mechanisms. This impact is largely dependent on the morphology of UGI. Although this conclusion is widely accepted there lacks a systematic approach to quantify the impact and thus the knowledge regarding its magnitude. This paper discusses the influencing mechanisms of UGI on urban building energy consumption. The city of Nanjing, a Chinese city in the hot-summer-cold-winter climate, is morphologically analyzed to extract prototypes of UGI forms. These prototypes are simulated for their microclimate and urban building energy consumptions using a co-simulation technique, which links ENVI-met to EnergyPlus. The simulation results are statistically analyzed to quantify the impact of UGI morphology on urban building energy consumption. The energy consumption of different morphological groups in summer and winter is compared to determine the impact of UGI morphological features on urban building energy.

Resilient cyber physical simulation for modified back-to-back converter with sliding mode control

This paper presents an approach on to the testing of cyber–physical controller-hardware in loop testing of modified back to back converter for three phase applications with sliding mode control. The proposed back-to-back converter is capable of feeding supply for two independent loads. The uncontrolled rectifier is utilised as front end converter and a modified back end converter is designed. The back converter has reduced semiconductor switches and rating of the DC link is reduced. The power electronics model is designed by using Multisim tool which is a pspice based electrical simulation software. The control terminals are interfaced with LabVIEW using co-simulation interface. The co-simulation technique involves controller on target control unit and the plant model in a real-time computer (Multisim). The DSP processor TMS320F2812 which has the control algorithm for controlling the plant model is connected with the NI Compact Date Acquisition (C-DAQ) module and is interfaced with LabVIEW, where the data acquisition takes place. The control strategy for back end control is based on integral sliding mode control. The performance analysis of the modified back-to-back converter is analysed with cyber physical hardware in loop and co-simulation framework.

Parametric Analysis of Gas Diffusion Layer on PEMFC Performance Using Design of Experiment Method

The water saturation in the gas diffusion electrodes of proton exchange membrane fuel cell (PEMFC) significantly impacts on the cell performance, but it is difficult to directly observe. The physical properties of gas diffusion electrodes, such as porosity and thermal conductivity, effects on the water saturation, but these physical properties are difficult to vary in the hardware-based experiment. Thus, the model-based engineering is significantly important to optimize the design in this area. A two-phase computational fluid dynamic (CFD) based model of PEMFC has been developed with Lattice Boltzmann Method (LBM) and validated [1, 2]. This multi-scale direct model can simulate the water saturation in the gas diffusion porous layers and predict the cell performance with co-simulation technique [3] as shown in the figure 1. The model is exercised through a rigorous design of experiment (DOE) to study the impact of the gas diffusion layers’ physical properties as well as operating conditions on the cell performance with the goal of enabling structural and operational optimization through model-based experiments. The L27 orthogonal array in the Taguchi Methods [4] was employed for the DOE. The physical properties (porosity of the gas diffusion layer (GDL) porosity, thermal conductivities of GDL and micro porous layer (MPL) and water contact angle of GDL) and operating conditions (operational temperature and current density) were allocated in the L27 array as the control factors. Since the high reproducibility is expected in the model-based experiments, the analysis of test-to-test variance was skipped. Table 1 shows a variance analysis among control factors at the current density of 1.5 A/cm2. The P-values of each control factor are very low except the water contact angle of GDL. Thus, the contact angle which represent the wettability of GDL can be insensitive for the cell performance. Figure 2 shows the results of an analysis of variance (ANOVA) study for the cell voltage as the output. Porosity and thermal conductivities of the GDL and the MPL exhibit different trend of sensitivities. It offers an opportunity to optimize them in the cell design.

Design of an FPGA-Based Fuzzy Feedback Controller for Closed-Loop FES in Knee Joint Model.

Functional electrical stimulation (FES) device has been widely used by spinal cord injury (SCI) patients in their rehab exercises to restore motor function to their paralysed muscles. The major challenge of muscle contraction induced by FES is early muscle fatigue due to the open-loop stimulation strategy. To reduce the early muscle fatigue phenomenon, a closed-loop FES system is proposed to track the angle of the limb’s movement and provide an accurate amount of charge according to the desired reference angle. Among the existing feedback controllers, fuzzy logic controller (FLC) has been found to exhibit good control performance in handling complex non-linear systems without developing any complex mathematical model. Recently, there has been considerable interest in the implementation of FLC in hardware embedded systems. Therefore, in this paper, a digital fuzzy feedback controller (FFC) embedded in a field-programmable gate array (FPGA) board was proposed. The digital FFC mainly consists of an analog-to-digital converter (ADC) Data Acquisition and FLC sub-modules. The FFC was designed to monitor and control the progress of knee extension movement by regulating the stimulus pulse width duration to meet the target angle. The knee is expected to extend to a maximum reference angle setting (70°, 40° or 30°) from its normal position of 0° once the stimulus charge is applied to the muscle by the FES device. Initially, the FLC was modelled using MATLAB Simulink. Then, the FLC was hardcoded into digital logic using hardware description language (HDL) Verilog codes. Thereafter, the performance of the digital FLC was tested with a knee extension model using the HDL co-simulation technique in MATLAB Simulink. Finally, for real-time verification, the designed digital FFC was downloaded to the Intel FPGA (DE2-115) board. The digital FFC utilized only 4% of the total FPGA (Cyclone IV E) logic elements (LEs) and required 238 µs to regulate stimulus pulse width data, including 3 µs for the FLC computation. The high processing speed of the digital FFC enables the stimulus pulse width duration to be updated every stimulation cycle. Furthermore, the implemented digital FFC has demonstrated good control performance in accurately controlling the stimulus pulse width duration to reach the desired reference angle with very small overshoot (1.4°) and steady-state error (0.4°). These promising results are very useful for a real-world closed-loop FES application.

Dynamic simulation of a high-speed train with interconnected hydro-pneumatic secondary suspension

A secondary suspension configuration that integrates the Interconnected Hydro-Pneumatic Struts (IHPS) to the air spring system is proposed in this investigation for railway vehicles. Using the dynamic performance of IHPS, this suspension aims to provide smaller vertical supporting stiffness and larger anti-roll resistance compared to the traditional configuration, the air spring is connected to an emergency rubber spring in series with quite large stiffness. By replacing the rubber spring with IHPS, the proposed suspension configuration contributes to vibration absorption as well as anti-roll stiffness of the vehicle. The IHPS has two hydraulic cylinders installed in parallel to support the suspended mass. Each hydraulic cylinder has three oil chambers, and the oil chambers between the left and right struts are cross-connected through pipelines. Considering the oil compressibility and the vibration of liquid in the interconnected pipes, the mathematical model of IHPS is formulated and established in MATLAB. A multi-body dynamic railway vehicle model is built in SIMPACK, into which the IHPS is integrated through a co-simulation technique. Model validations on the IHPS are performed and its static and dynamic stiffness is examined. Numerical simulations show that the IHPS suspension reduces the vertical acceleration on the car body floor at a frequency between 1 and 3 Hz than the traditional air spring system with/without an anti-roll bar configuration. The vertical Sperling index of the vehicle using the IHPS suspension is smaller than that of the traditional suspensions, and it is more significant when the air spring deflates. However, the vertical acceleration with IHPS is larger than the traditional suspensions at 13∼55 Hz when the air spring deflates.

Numerical Fluid-Structure Interaction Analysis for a Flexible Marine Propeller Using Co-Simulation Method

Carbon fibre composite has exceptionally high strength, low density and corrosion resistance in the marine environment compared to conventional materials. These characteristics make it a favourable alternative material to be considered for manufacturing marine screw propellers. Despite these advantages, the flexibility of the material leads to a significant change in blade geometry due to loads acting on blades which alter hydrodynamic performance. A two-way coupled fluid-structure interaction analysis is required to accurately capture its hydrodynamic performance due to the reduced stiffness and material anisotropy. The present study focuses on numerical investigation for the hydro-elastic based performance analysis of a composite marine propeller in open water condition. The procedure involves the coupling of Reynolds-Averaged Navier-Stokes Equation based computational fluid dynamics solver with the finite element method solver using co-simulation technique. The open water characteristics, including thrust coefficient, torque coefficient and open water efficiency, are discussed as a function of advance ratio. This paper presents a comparison of the hydrodynamic performance and structural responses between a carbon fibre composite propeller and a conventional steel propeller which are geometrically identical. The results for the composite propeller show a significant improvement in hydrodynamic performance compared to the metallic propeller while remaining structurally safe throughout the tested range.

Performance Investigation of Digital Lowpass IIR Filter Based on Different Platforms

The work presented in this paper illuminates the design and simulation of a recursive or Infinite Impulse Response (IIR) filter. The proposed design algorithm employs the Genetic Algorithm to determine the filter coefficients to satisfy the required performance. The effectiveness of different platforms on filter design and performance has been studied in this paper. Three different platforms are considered to implement and verify the designed filter’s work through simulation. The first platform is the MATLAB/SIMULINK software package used to implement the Biquad form filter. This technique is the basis for the software implementation of the designed IIR filter. The HDL – Cosimulation technique is considered the second one; it inspired to take advantage of the existing tools in SIMULINK to convert the designed filter algorithm to the Very high-speed integrated circuit Hardware Description Language (VHDL) format. The System Generator is employed as the third technique, in which the designed filter is implemented as a hardware structure based on basic unit blocks provided by Xilinx System Generator. This technique facilitates the implementation of the designed filter in the FPGA target device. Simulation results show that the performance of the designed filter is remarkably reliable even with severe noise levels.