Performance Of Filter Research Articles

Efficient capture of particulate matter with composite air filters comprising bamboo-derived nanofiber and base paper

Particulate-matter (PM) air filters comprising chemically synthesized polymers and petroleum-based materials are not environmentally sustainable because they do not biodegrade, causing secondary environmental pollution. To overcome this problem, we synthesized and analyzed the PM-capturing performance of composite sandwich-structured air filters containing bamboo-derived lignocellulose nanofibers and lignocellulose base paper. Bamboo pulp was produced through an organosolv process, and lignocellulose nanofibers and lignocellulose base paper were manufactured via electrospinning and paper processes, respectively. The manufacturing process was not only optimized via a rheological analysis of the precursor solution with different mixed solvent composition (6:4, 5:5, and 4:6 of 1-ethyl-3-methylimidazolium acetate:dimethylformamide) and different lignocellulose weight percent (3.3, 4.0, and 4.6 wt%), but also via nanofiber characterization, including electrospinnability, diameter distribution, and basis weight. The base paper condition was optimized based on analyses of the air permeability, PM filtration efficiency, and strength according to the paper thickness of 0.38 ± 0.05 and 0.10 ± 0.05 mm. As the lignocellulose nanofibers and base paper effectively captured particles smaller and larger than 2.5 μm, respectively, the structure of their composite sandwich-structured air filter was optimized to improve its PM-capturing performance. The study results provide new insights into the manufacturing of highly efficient PM air filters suitable for practical applications with diverse PM size distributions.

Geometrical Optimization of Closed-End Cylindrical Air Filter Using CFD Simulation

This research aims to evaluate the effect of porous filter configuration on flow characteristics within filter using CFD simulation. This simulation model was chosen for comprehensive analysis that considers different variables affecting the filter performances. Dynamics of the flow and pressure drop under different flow conditions and filter geometry were studied. The Euler-Lagrangian approach was used to model multiphase flow, and the standard K-ε model was used for turbulence characterisation. Particle size distribution was characterized using Rosin-Rammler distribution. The initial status of these properties was obtained by previous experimental references and their evolution over time was simulated at the cell level of the model using User-Defined Functions (UDF). The main conclusions of the study are: i) The pressure drop increased with flow rate and thickness of the filter but decreased with increasing filter length and diameter. ii) There is no significant change in velocity ratio with the distance from the filter inlet at the filter centre line except the first 5% from the inlet and last 5% close to the end. iii) it was identified that higher radial velocity ratios imply a less particle deposition within the filter media. The results also shows that the particle loading on 290 mm filter is 50% - 60% lower than the other filters but evenly distributed across the filter. However, the pressure drop decreased with the filter length. 55mm filter that has the highest radial velocity ratio performs poorly in particle trapping.

Optimizing virus filtration for continuous processing using serial filtration at high area ratio.

Compared to batch operation, continuous bioprocessing can offer numerous advantages, including increased productivity, improved process control, reduced footprint, and increased flexibility. However, integration of traditional batch operations into a connected process can be challenging. In contrast to batch operations run at constant pressure or high flux, virus filtration in continuous processes may be operated at very low flux. This change in operating conditions may reduce the viral retention performance of the filter which has inhibited adoption of truly continuous virus filtration. To overcome this limitation, a novel approach is described that utilizes serial virus filtration, with a high area ratio between first to second stage filters, to achieve virus retention targets. In this study, virus filters were operated continuously (except for planned process interruptions) for 200 h in a serial configuration at a first to second stage filter area ratio of 13:1 and at a first stage flux of 5 L/m2/h. While the minute virus of mice (MVM) retention performance of the first stage filter was about 4 log reduction value (LRV), there was no virus detected in the second stage filtrate, translating to an MVM LRV across the filtration train of ≥6.7. The second stage filter was the dominant flow resistance at the start of the run but, as it was protected from foulants by the first stage filter, it suffered minimal fouling and the life of the filter train was controlled by the first stage. A theoretical case study projected that continuous virus filtration using serial configuration at high area ratio would have about 30% longer filter changeout time, 14% higher productivity, and virus retention nearly sixLRV greater than single stage operation. The findings of this research are expected to provide valuable insights into optimizing virus filtration in continuous bioprocessing.

Low-cost, reliable, and highly efficient removal of COD and total nitrogen from sewage using a sponge-filled trickling filter.

Development of low-cost and reliable reactors demanding minimal supervision is a need-of-the-hour for sewage treatment in rural areas. This study explores the performance of a multi-stage sponge-filled trickling filter (SPTF) for sewage treatment, employing polyethylene (PE) and polyurethane (PU) media. Chemical oxygen demand (COD) and nitrogen transformation were evaluated at hydraulic loading rates (HLRs) ranging from 2 to 6 m/d using synthetic sewage as influent. At influent COD of ∼350 mg/L, PU-SPTF and PE-SPTF achieved a COD removal of 97% across all HLRs with most of the removal occurring in the first segments. Operation of PE-SPTF at an HLR of 6 m/d caused substantial wash-out of biomass, while PU-SPTF retained biomass and achieved effluent COD < 10 mg/L even at HLR of 8-10 m/d. The maximum Total Nitrogen removal by PE-SPTF and PU-SPTF reactors was 93.56 ± 1.36 and 92.24 ± 0.66%, respectively, at an HLR of 6 m/d. Simultaneous removal of ammonia and nitrate was observed at all the HLRs in the first segment of both SPTFs indicating ANAMMOX activity. COD removal data, media depth, and HLRs were fitted (R2 > 0.99) to a first-order kinetic relationship. For a comparable COD removal, CO2 emission by PU-SPTF was 3.5% of that of an activated sludge system.

Deep trapped bipolar heterocharges enable electret nanofibrous membranes for high-efficiency PM0.3 filtration

Recently frequent global pandemic outbreak triggers the demand of high-efficiency aerosol filtration materials. Most of traditional electret air filters can hardly achieve high efficiency (>99.99 %) due to limited charge density and inappropriate charge distribution. The influence mechanism of nanofibers bipolar heterocharge configuration on electrostatic capture of airborne particles is still confusing. Herein, a novel strategy to create high-efficiency air filters based on electret nanofibrous membranes with deep trapped heterocharge is reported. Space charges and dipole charges with opposite polarity are formed in electrospun membranes composed of different polymers under in-situ charge injection and electric poling during electrospinning. Nanoscale spatial surface potential mapping on individual nanofiber characterized by Kelvin probe force microscopy demonstrates bipolar heterocharge distribution. Numerical simulation shows that fiber heterocharge distribution endows the electret membrane with greater electrostatic field intensity gradient, resulting in stronger electrostatic force between nanofibers and airborne particles. With bipolar heterocharge configuration and bimodal fiber diameter distribution, the nanofibrous membranes exhibit high-efficiency low-resistance filtration property against 0.3 μm NaCl particles (99.994 %, 97.4 Pa) at 5.3 cm s−1. Furthermore, benefiting from charges with deep trap energy of 1.12 eV, the membranes still maintain 99.972 % filtration efficiency after 40 h exposure in 95 % relatively humidity. The prepared membranes brings new insight in the design of high-efficiency and long-term stability air filtration materials for public health precaution. This study not only reveals influence mechanism of nanofibers heterocharge distribution on electrostatic attraction, but also provides useful guidance for fiber charge configuration design to improve aerosol filtration performance of electret filters.

Numerical analysis of an all-fiber plasmonic polarization filter using dual elliptical gold thin layers deposited photonic crystal fiber

In order to solve the problems of high performance and small size incompatibility, as well as limited bandwidth, of traditional polarization filters in optical communication systems, this work presents an all-fiber polarization filter using dual elliptical gold layer deposited photonic crystal fiber by the finite element tool. The gold layers are plated on the inside of the two elliptical holes to create surface plasmon resonance effect, which cause the signal intensity in x-polarized direction to be much greater than that in y-polarized direction. The simulation results illustrate that when hole-to-hole pitch Λ is 2.0 μm, cladding hole diameter d 1 is 2.0 μm, two inner-holes’ diameter d 2 is 0.3 μm, spacing between two inner-holes d s is 0.755 μm, the major axis length of elliptical holes a is 2.0 μm, the minor axis length of elliptical holes b is 0.97 μm, the gold thin layer t is 100 nm, the proposed PCF filter exhibits good filtering performance at the communication wavelength of 1.55 μm, where the confinement loss in x- and y-polarized direction are 303.91 dB cm−1 and 0.06 dB cm−1, respectively. The crosstalk and operating bandwidth improve with the increment of device’s length, the 800 μm-long PCF filter possesses the maximum crosstalk of −211.14 dB and the bandwidth of 600 nm. Finally, the experimental scheme is also discussed. We believe that this photonic filter can play a significant role in optical communication, optical sensing, spectral analysis, and other related fields.

Numerical simulation of an in-fiber broadband plasmonic polarization filter using photonic crystal fiber with dual elliptical gold layers

The demand for advanced and compact photonic filters is increasing in today's optical communication systems. This work introduces a new all-fiber broadband polarization filter using photonic crystal fiber with dual elliptical gold layers. The filtering performance is evaluated and analyzed by the finite element method. The simulation results demonstrate that the two elliptical gold layers can effectively induce a significant change in the energy of x-polarized light, leading to a great difference between the two polarized lights. By selecting reasonable structural parameters of the proposed PCF, the 1 mm-long in-fiber filter has a maximum extinction ratio of -108.90 dB, a low insertion loss of 0.64 dB around 1.31 µm and an ultra-broad bandwidth of 1020 nm, covering two common communication windows of 1.31 µm and 1.55 µm. Additionally, the filtering experimental scheme is discussed. This filter is expected to drive the advancement of optical integrated chips and all-optical communication networks.

Uncertainty quantification via localized gradients for deep learning-based medical image assessments

Objective. Deep learning models that aid in medical image assessment tasks must be both accurate and reliable to be deployed within clinical settings. While deep learning models have been shown to be highly accurate across a variety of tasks, measures that indicate the reliability of these models are less established. Increasingly, uncertainty quantification (UQ) methods are being introduced to inform users on the reliability of model outputs. However, most existing methods cannot be augmented to previously validated models because they are not post hoc, and they change a model’s output. In this work, we overcome these limitations by introducing a novel post hoc UQ method, termed Local Gradients UQ, and demonstrate its utility for deep learning-based metastatic disease delineation. Approach. This method leverages a trained model’s localized gradient space to assess sensitivities to trained model parameters. We compared the Local Gradients UQ method to non-gradient measures defined using model probability outputs. The performance of each uncertainty measure was assessed in four clinically relevant experiments: (1) response to artificially degraded image quality, (2) comparison between matched high- and low-quality clinical images, (3) false positive (FP) filtering, and (4) correspondence with physician-rated disease likelihood. Main results. (1) Response to artificially degraded image quality was enhanced by the Local Gradients UQ method, where the median percent difference between matching lesions in non-degraded and most degraded images was consistently higher for the Local Gradients uncertainty measure than the non-gradient uncertainty measures (e.g. 62.35% vs. 2.16% for additive Gaussian noise). (2) The Local Gradients UQ measure responded better to high- and low-quality clinical images (p < 0.05 vs p > 0.1 for both non-gradient uncertainty measures). (3) FP filtering performance was enhanced by the Local Gradients UQ method when compared to the non-gradient methods, increasing the area under the receiver operating characteristic curve (ROC AUC) by 20.1% and decreasing the false positive rate by 26%. (4) The Local Gradients UQ method also showed more favorable correspondence with physician-rated likelihood for malignant lesions by increasing ROC AUC for correspondence with physician-rated disease likelihood by 16.2%. Significance. In summary, this work introduces and validates a novel gradient-based UQ method for deep learning-based medical image assessments to enhance user trust when using deployed clinical models.

Comparative Analysis of the Impact of Protein on Virus Retention for Different Virus Removal Filters.

The performance of virus filters is often determined by the extent of protein fouling, which can affect both filtrate flux and virus retention. However, the mechanisms governing changes in virus retention in the presence of proteins are still not well understood. The objective of this work was to examine the effect of proteins on virus retention by both asymmetric (Viresolve® NFP and Viresolve® Pro) and relatively homogeneous (Ultipor® DV20 and PegasusTM SV4) virus filtration membranes. Experiments were performed with bacteriophage ϕX174 as a model parvovirus and human serum immunoglobulin G (hIgG) as a model protein. The virus retention in 1 g/L hIgG solutions was consistently less than that in a protein-free buffer solution by between 1 to 3 logs for the different virus filters. The virus retention profiles for the two homogeneous membranes were very similar, with the virus retention being highly correlated with the extent of flux decline. Membranes prefouled with hIgG and then challenged with phages also showed much lower virus retention, demonstrating the importance of membrane fouling; the one exception was the Viresolve® Pro membrane, which showed a similar virus retention for the prefouled and pristine membranes. Experiments in which the protein was filtered after the virus challenge demonstrated that hIgG can displace previously captured viruses from within a filter. The magnitude of these effects significantly varied for the different virus filters, likely due to differences in membrane morphology, pore size distribution, and chemistry, providing important insights into the development/application of virus filtration in bioprocessing.

Color image hybrid noise filtering algorithm based on deep convolution neural network

To solve the problems of the classical color image hybrid noise filtering method, a deep convolutional neural network improved by evolutionary strategy and jump connection is proposed and applied to the filtering noise reduction of color images. First, the color information of the image is described quantitatively by digital means. The common method is to build color space model. According to the characteristics of color and the needs of human vision, mathematical algorithms are used to convert images into machine recognizable data. The distance between pixels is measured according to the difference of pixels in the color image determined above. Then, the probability density function and noise probability density function of Gaussian noise are calculated to determine the hybrid noise feature points of color image. The filtering algorithm structure designed this time is as follows: A color image hybrid noise filter is used to map the noise points in the mapped image to the feature space, and linear regression is performed on the noise point data. Relaxation variables are introduced in the network to improve the denoising ability. The experimental results show that the Peak Signal to Noise Ratio and structural similarity index values of the filtering algorithm designed in this study are higher than the two methods in the literature. The color image hybrid noise filtering model designed in this study has good filtering performance, good image cleanliness, and high filtering efficiency.

Antimicrobial Face Masks and Mask Covers with a Salt-Coated Stacked Spunbond Polypropylene Fabric: Effective Inactivation of Resilient Pathogens and Prevention of Contact Transmission.

In response to the ongoing threat posed by respiratory diseases, ensuring effective transmission protection is crucial for public health. To address the drawbacks of single-use face masks/respirators, which can be a potential source of contact-based transmission, we have designed an antimicrobial face mask and mask covering utilizing a stack of salt-coated spunbond (SB) fabric. This fabric acts as an outer layer for the face mask and as a covering over a conventional mask, respectively. We evaluated the universal antimicrobial performance of the salt-coated three-stacked SB fabric against enveloped/nonenveloped viruses and spore-forming/nonspore-forming bacteria. The distinctive pathogen inactivation efficiency was confirmed, including resistant pathogens such as human rhinovirus and Clostridium difficile. In addition, we tested other filter attributes, such as filtration efficiency and breathability, to determine the optimal layer for salt coating and its effects on performance. Our findings revealed that the outer layer of a conventional face mask plays a crucial role in contact transmission through contaminated face masks and respirators. Through contact transmission experiments using droplets involving three types of contaminants (fluorescent dyes, bacteria, and viruses), the salt-coated stacked SB fabric demonstrated a superior effect in preventing contact transmission compared to SB or meltblown polypropylene fabrics─an issue challenging to existing masks. Our results demonstrate that the use of salt-coated stacked SB fabrics as (i) the outer layer of a mask and (ii) a mask cover over a mask enhances overall filter performance against infectious droplets, achieving high pathogen inactivation and low contact-based transmission while maintaining breathability.

Sulfonated Pentablock Copolymer (NexarTM) for Water Remediation and Other Applications.

This review focuses on the use of a sulfonated pentablock copolymer commercialized as NexarTM in water purification applications. The properties and the use of sulfonated copolymers, in general, and of NexarTM, in particular, are described within a brief reference focusing on the problem of different water contaminants, purification technologies, and the use of nanomaterials and nanocomposites for water treatment. In addition to desalination and pervaporation processes, adsorption and photocatalytic processes are also considered here. The reported results confirm the possibility of using NexarTM as a matrix for embedded nanoparticles, exploiting their performance in adsorption and photocatalytic processes and preventing their dispersion in the environment. Furthermore, the reported antimicrobial and antibiofouling properties of NexarTM make it a promising material for achieving active coatings that are able to enhance commercial filter lifetime and performance. The coated filters show selective and efficient removal of cationic contaminants in filtration processes, which is not observed with a bare commercial filter. The UV surface treatment and/or the addition of nanostructures such as graphene oxide (GO) flakes confer NexarTM with coating additional functionalities and activity. Finally, other application fields of this polymer are reported, i.e., energy and/or gas separation, suggesting its possible use as an efficient and economical alternative to the more well-known Nafion polymer.

Robust error-state Kalman-type filters for attitude estimation

State estimation techniques appear in a plethora of engineering fields, in particular for the attitude estimation application of interest in this contribution. A number of filters have been devised for this problem, in particular Kalman-type ones, but in their standard form they are known to be fragile against outliers. In this work, we focus on error-state filters, designed for states living on a manifold, here unit-norm quaternions. We propose extensions based on robust statistics, leading to two robust M-type filters able to tackle outliers either in the measurements, in the system dynamics or in both cases. The performance and robustness of these filters is explored in a numerical experiment. We first assess the outlier ratio that they manage to mitigate, and second the type of dynamics outliers that they can detect, showing that the filter performance depends on the measurements’ properties.

Impact of fiber sizes on multi-fiber filter performance using coupled Eulerian-Lagrangian and Immersed boundary

Fibrous filters are widely used to remove particles from gas-solid flows. In the present research, the potential to enhance the collection efficiency of fibrous filters was investigated by increasing the number of filter rows and using varying sizes of square fibers. A two dimensional model was used to simulate the transport and deposition of particles, employing the developed Eulerian-Lagrangian solver coupled with the Immersed Boundary (IB) method. Several structures of filter fibers including the equal and unequal fibers in the arrangement of two, four and six rows were investigated. The results showed increasing the size difference between large and small fibers in the filter media increases the collection efficiency and pressure drop simultaneously. To find the effective structure of enhancing the filter performance, the quality factor was considered. The results of quality factor showed that using unequal fibers has an advantage over increasing the number of rows in an equal-fiber structure to increase the collection efficiency. Therefore, using the unequal fibers with the growth rate of 1.2 to 1.4, are more effective than increasing the number of rows in equal fiber structures.

Virus retention during constant-flux virus filtration using the Viresolve® Pro membrane including process disruption effects

The growing interest in process intensification and continuous processing has led to concerns regarding the performance of virus removal filters at low permeate fluxes. This paper presents a quantitative analysis of virus retention by the Viresolve® Pro membrane during constant permeate flux filtration and in response to process disruptions using ΦX-174, a bacteriophage, as a model for a mammalian parvovirus. Virus retention by a single layer of Viresolve® Pro membrane was reduced at lower permeate fluxes due to the greater diffusive mobility of phage, although the expected retention for a commercial device employing two layers of membrane remained above 4-logs. The retention data were well correlated with the ΦX-174 Péclet number for filtrate flux from 5 to 100 L/m2/h. Process disruptions caused an immediate transient increase in phage transmission, although this effect was much less pronounced at low permeate flux. The experimental data for phage retention, both with and without process disruptions, were well-described using an internal polarization model with the fraction of virus remaining mobile within the filter scaling as 1/Pe2. In contrast, the fraction of previously captured virus that were re-mobilized after a process interruption was independent of the flow rate. Model equations were developed for rapid estimation of virus performance behavior with the Viresolve® Pro membrane, facilitating the design and implementation of virus filtration processes operating at constant filtrate flux.

Improving Graph Collaborative Filtering with Directional Behavior Enhanced Contrastive Learning

Graph Collaborative Filtering is a widely adopted approach for recommendation, which captures similar behavior features through Graph Neural Network (GNN). Recently, Contrastive Learning (CL) has been demonstrated as an effective method to enhance the performance of graph collaborative filtering. Typically, CL-based methods first perturb users’ history behavior data (e.g., drop clicked items), then construct a self-discriminating task for behavior representations under different random perturbations. However, for widely existing inactive users, random perturbation makes their sparse behavior information more incomplete, thereby harming the behavior feature extraction. To tackle the above issue, we design a novel directional perturbation-based CL method to improve the graph collaborative filtering performance. The idea is to perturb node representations through directionally enhancing behavior features. To do so, we propose a simple yet effective feedback mechanism, which fuses the representations of nodes based on behavior similarity. Then, to avoid irrelevant behavior preferences introduced by the feedback mechanism, we construct a behavior self-contrast task before and after feedback, to align the node representations between the final output and the first layer of GNN. Different from the widely adopted self-discriminating task, the behavior self-contrast task avoids complex message propagation on different perturbed graphs, which is more efficient than previous methods. Extensive experiments on three public datasets demonstrate that the proposed method has distinct advantages over other CL methods on recommendation accuracy.

Enhancing indoor air quality: Examination of formaldehyde adsorption efficiency of portable air cleaner fitted with chemically-treated activated carbon filters

The pursuit of salubrious living environments necessitates a holistic approach to assuring indoor air quality. This entails considering not only particulate matter but also gaseous pollutants, particularly formaldehyde – a carcinogenic and prevalent pollutant in household environment. In addressing the persistent challenge in balancing efficiency, operating costs and environmental impact in formaldehyde removal, our study pioneers to empirically explore and compare the relationship between Carbon Tetrachloride Activity (CTC), Clean Air Delivery Rate (CADR), and Cumulate Clean Mass (CCM) in the context of formaldehyde adsorption, using both raw and 2-Imidazolidone-treated activated carbon (AC) filters fitted in a Portable Air Cleaner (PAC). Our experimental results show that the formaldehyde CADRs of an air cleaner with chemically-treated CTC70 and CTC100 filters were about 251 m3/h and 286 m3/h respectively, representing an increase of 1.52 and 2.5 times over untreated filters, with the treated CTC100 AC filters outperforming the CTC70 filters by approximately 12 percent under new condition. While the precise mechanisms by which 2-Imidazolidone enhances the performance of AC filters are still unknown, these findings provide an first-of-its-kind directive for future research on the interplay among the parameters (CTC, CADR and CCM) of PACs, casting a foundation for further investigations that aim at optimizing the performance of AC filters, thereby making significant strides in the enhancement of indoor air quality.

Removal Characteristics of Gas-Phase D-Limonene in Biotrickling Filter and Stoichiometric Analysis of Biological Reaction using Carbon Mass Balance

Volatile organic compounds (VOCs) pose significant risks to human health and environmental quality, prompting stringent regulations on their emissions from various industrial processes. Among VOCs, d-limonene stands out due to its low threshold and contribution to malodorous emissions. While biofiltration presents a promising approach for VOC removal, including d-limonene, a comprehensive understanding of its performance and kinetics is lacking. This study aims to comprehensively assess the performance of a lab-scale biotrickling filter in treating gas-phase d-limonene. The experimental results indicate that the biotrickling filter efficiently removed d-limonene, achieving a critical loading rate of 19.4 g m−3 h−1 and a maximum elimination capacity of 31.8 g m−3 h−1 (correspondingly, up to 85% removal) at the condition of 94.2 s of EBRT. Microbial activity played a significant role in biotrickling filter performance, with a strong linear correlation being observed between CO2 production and substrate consumption. The Michaelis–Menten model was employed to represent enzyme-catalyzed reactions, suggesting no inhibition during biotrickling filter operation.

Separation performance of boron nitride nanotube stainless-steel filter

In this study, boron nitride nanotubes (BNNTs) were utilized as covering and reinforcing materials owing to their extraordinary insulation and extremely high hydrophobicity. The gas–liquid–solid annealing process was used to manufacture the BNNT stainless-steel filter, with a 120 mesh stainless steel filter serving as the substrate and B2O3 as the raw material. Scanning electron microscopy showed that the average diameter of the nanotubes was 0.40 μm. The BNNTs were bamboo shaped, and the BNNT stainless-steel filter was superhydrophobic, with a water contact angle was 150.49°. The materials demonstrated good separation performance, as indicated by the separation results obtained under four different test conditions (0 and 0.3 MPa, 3 and 10 mL/min). The solid–liquid separation effect of the BNNT stainless-steel filter was better than that of the Teflon filter. In oil–water separation experiments with varying water contents (1.2 and 5.8 wt%), the BNNT stainless-steel filter was more hydrophobic. Based on the results, the role of the hydrodynamic method in the separation of two superhydrophobic materials is discussed. The method introduced in this study can serve as a reference for the application of other filtration separation technologies. Furthermore, the superior separation performance of the superhydrophobic BNNT stainless-steel filter may enable the quick, effective, and continuous collection of water contaminated with oil, giving it a wide range of potential applications.

Adaptive VSG-Based power allocation strategy for hybrid energy storage

Abstract Aiming at the stochasticity of photovoltaic output and the problem of power, voltage, and frequency fluctuation caused by the lack of system inertia and damping parameters, a photovoltaic storage microgrid is constructed as a research object. Firstly, a virtual synchronous motor VSG is used to control the grid-connected inverter and to improve the dynamic performance of the system further. The inertia and damping parameters of the VSG are adjusted adaptively. Secondly, the hybrid energy storage device composed of a supercapacitor and battery adopts a second-order filter to avoid the integrating effect of the first-order filter on the high-frequency power and improve the poor performance of the first-order filter at the cutoff frequency to improve the accuracy of power distribution. Moreover, two negative feedback links of power error are added in the power distribution link to correct the reference power of the energy storage device, which further improves the power tracking effect of the energy storage system. Finally, the effectiveness of the above strategy is verified by a Matlab simulation session.