Control Models Research Articles

Full Quantity or Full Credit? Choosing the Right Buyback Policy for a Behavioral Retailer

Problem definition: Despite extensive research on buyback contracts in supply chain management, little attention has been given to a direct comparison between a traditional full-quantity, partial-credit (FQ) buyback contract and an alternative full-credit, partial-quantity (FC) contract, especially when considering the behavioral biases of the retailer. This study aims to fill this research gap by exploring how these biases influence contract performance and offer practical guidelines for suppliers. Methodology/results: Through controlled laboratory experiments and structural model estimation, we show that the ordering decisions made by human retailers are jointly affected by three behavioral biases—loss aversion, prospective accounting, and psychological cost of inventory error—and these biases differ in magnitude between the two contracts. Incorporating these biases into a behavioral retailer’s utility function, we then analytically examine which buyback policy the supplier should choose. When the wholesale price is exogenously given, the supplier should adopt the FC contract for high-margin (low-cost) products. Conversely, when the supplier has the power to set both the wholesale and buyback prices, the FC contract is generally more beneficial for low-margin products. Finally, when the product cost is sufficiently high, a wholesale price contract may be advantageous over buyback policies. Managerial implications: The managerial implication of this paper is significant for suppliers who have to choose between different buyback policies. The paper suggests that the supplier should carefully consider not just the economic, but also the behavioral dimensions when making contract decisions, particularly when dealing with a retailer influenced by behavioral biases. Specifically, the choice between FQ and FC contracts is influenced by two key environmental factors: the production cost of the product and the nature of wholesale pricing. Understanding these elements allows suppliers to be flexible in contract choices and design appropriate return policies for their downstream supply chain partners. Funding: P. Yu was supported by the National Natural Science Foundation of China [Grants 72371038 and 72033003] and the Fundamental Research Funds for the Central Universities [Grant 2024CDJSKPT16]. T. Feng was supported by the National Natural Science Foundation of China [Grant 72131004]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0574 .

Problems of Development of Control Models and Mechanisms in Modern Ecosystems

Problems of Development of Control Models and Mechanisms in Modern Ecosystems

Research progress on operation control and optimal scheduling of irrigation canal systems

AbstractOpen canals are a common water transfer method used in water transfer projects and agricultural irrigation and drainage projects. With the emergence of drawbacks in traditional canal control models and the increasingly severe shortage of water resources, accurate transport and distribution of water in the canal system of the irrigation district, rational allocation of water resources, reduction in water loss, improvement in the efficiency and benefit of water resource utilization, and satisfaction of the water demand of different water users are needed. Many scholars have conducted extensive research on canal operation control and optimal scheduling. This paper systematically reviews and summarizes the relevant research progress, including the theory of unsteady flow in open canals, the operation mode of the canal system, the operation control model and algorithm of canal systems, and the optimization of water distribution in canal systems. By summarizing the research progress already achieved, the existing problems and future development directions are identified according to actual needs, providing a reference for the ongoing modernization of irrigation districts and the research and application of digital twin irrigation district technology.

A framework for conceptualizing integrated prescriptive maintenance and production planning and control models

Goal: This study aims to support researchers and managers in conceptualising new integrated prescriptive maintenance (PxM) and production planning and control (PPC) models. Design / Methodology / Approach: We perform a systematic literature review based on Thomé et al. (2016) and analyse literary findings using qualitative content analysis and quantitative correlation analyses. Results: This work identifies 94 integrated PxM and PPC planning models and 47 outcomes, 16 decision variables and 34 environment entities. Based on the quantitative analyses of these components, we derive a normative framework to guide researchers and practitioners in conceptualising integrated models. Limitations of the investigation: The study is limited to only one scientific database. Additionally, the quantitative analyses might be sensitive due to a low sample size for some components, and we only measure the linear dependency between two components. Lastly, we do not address solution algorithms. Practical implications: The framework constitutes a tool for managers to construct integrated models tailored to their specific planning problems, fostering alignment between production and maintenance departments, plans and controls. Originality / Value: We provide a descriptive overview and normative guidance in the selection of components that can or should be used for future PxM-aligned PPC planning studies, pinpointing possible research gaps.

Transmission potential of Streptococcus pyogenes during a controlled human infection trial of pharyngitis.

Controlled human infection (CHI) models can provide insights into transmission of pathogens such as Streptococcus pyogenes (Strep A). As part of the Controlled Human Infection with Penicillin for Streptococcus pyogenes (CHIPS) trial, we explored the potential for transmission among participants deliberately infected with the Strep A emm75 strain. Three approaches to understanding transmission were employed: the use of agar settle plates to capture possible droplet or airborne spread of Strep A; measurement of distance droplets could spread during conversation; and environmental swabbing of high-touch items to detect Strep A on surfaces. Of the 60 (27%) CHIPS trial participants across five cohorts, 16 were enrolled in this sub-study; availability of study staff was the primary reason for selection. In total, 189 plates and 260 swabs were collected. Strep A was grown on one settle plate from a participant on the second day, using plates placed 30 cm away. This participant received the placebo dose of penicillin and had met the primary endpoint of pharyngitis. Whole-genome sequencing identified this to be the challenge strain. Strep A was not detected on any swabs. In this small sample of CHI participants, we did not find evidence of Strep A transmission by the airborne route or fomites, and just one instance of droplet spread while acutely symptomatic with streptococcal pharyngitis. Although these experiments provide evidence of minimal transmission within controlled clinical settings, greater efforts are required to explore Strep A transmission in naturalistic settings.IMPORTANCEStreptococcus pyogenes remains a significant driver of morbidity and mortality, particularly in under-resourced settings. Understanding the transmission modalities of this pathogen is essential to ensuring the success of prevention methods. This proposed paper presents a nascent attempt to determine the transmission potential of Streptococcus pyogenes nested within a larger controlled human infection model.

Stability analysis for passive robots walking on inclined surfaces with local angles

For common-legged robots with a kind of stiff joints, the human-like and consecutive gait shown by passive walking robots is a bit difficult to achieve because of varying degrees of control, which is usually accompanied by computational cost. Of course, passive dynamic walking undoubtedly has its inevitable disadvantages because of the lack of control, which is stability. At the same time, the significant nonlinearity of the passive gait increases the difficulty of realizing the walking stability of the passive robot. Therefore, the passive robot still needs certain control to achieve stable walking even on the natural plane or smooth slope. In this paper, a passive robot model walking on an inclined plane with a local angle is studied. First of all, the approximate solution of the nonlinear dynamic equation is given by the perturbation method, and the conditions for the robot to achieve stable walking without external forces are obtained. Further, the input-output feedback linearization control based on hybrid zero dynamics is employed to carry out virtual constraints on the passive robot during the swing stage of walking, facilitating the transition from the unstable state to the stable periodic state. From the result of the experiments, the walking stability of the passive robot is improved over a larger range of walking status values compared with the condition without external force control, and the use of this method reduces the complicated work of solving the fixed point. These findings possibly have reference value in passive walking stabilization control. Meanwhile, the simulation results obtained by designing and studying the minimum controlled walking model show that human walking is based on the uncontrolled mechanical process. The exploration of the mechanism of passive gait can provide some enlightenment to the research of human texture and the application of exoskeleton.

Variational analysis of sensory feedback mechanisms in powerstroke-recovery systems.

Although the raison d'etre of the brain is the survival of the body, there are relatively few theoretical studies of closed-loop rhythmic motor control systems. In this paper we provide a unified framework, based on variational analysis, for investigating the dual goals of performance and robustness in powerstroke-recovery systems. To demonstrate our variational method, we augment two previously published closed-loop motor control models by equipping each model with a performance measure based on the rate of progress of the system relative to a spatially extended external substrate-such as a long strip of seaweed for a feeding task, or progress relative to the ground for a locomotor task. The sensitivity measure quantifies the ability of the system to maintain performance in response to external perturbations, such as an applied load. Motivated by a search for optimal design principles for feedback control achieving the complementary requirements of efficiency and robustness, we discuss the performance-sensitivity patterns of the systems featuring different sensory feedback architectures. In a paradigmatic half-center oscillator-motor system, we observe that the excitation-inhibition property of feedback mechanisms determines the sensitivity pattern while the activation-inactivation property determines the performance pattern. Moreover, we show that the nonlinearity of the sigmoid activation of feedback signals allows the existence of optimal combinations of performance and sensitivity. In a detailed hindlimb locomotor system, we find that a force-dependent feedback can simultaneously optimize both performance and robustness, while length-dependent feedback variations result in significant performance-versus-sensitivity tradeoffs. Thus, this work provides an analytical framework for studying feedback control of oscillations in nonlinear dynamical systems, leading to several insights that have the potential to inform the design of control or rehabilitation systems.

A Unified Model of a Virtual Synchronous Generator for Transient Stability Analysis

A virtual synchronous generator (VSG) is prone to transient instability under a grid fault, which leads to the loss of synchronization between the new energy converter and grid, and threatens the operation safety of high-proportion new energy grids. There are a variety of control models in the existing VSG control, including active and reactive power models, which lead to their different transient stabilities. However, the evolution characteristics, correlation between different models of VSG, and the internal mechanism affecting transient stability have not been fully studied. To this effect, this paper analyzes their evolution characteristics based on the existing mainstream VSG control models and establishes a unified VSG model and its equivalent correspondence with other models. Then, the phase plane method is used to comprehensively analyze and compare the transient stability of the VSG unified model with other models. It is pointed out that the key factors affecting the transient stability of different models are three links of primary frequency regulation, reactive power regulation and reactive power tracking. Finally, the correctness of the established VSG unified model and the conclusion of transient stability analysis is verified by experiments.

Abstract P180: Female mice with systemic lupus erythematosus produce antibodies to mitochondrial antigens and have impaired renal mitochondrial function

Patients with autoimmune disorders like systemic lupus erythematosus (SLE) are at significant risk for renal and cardiovascular mortality. The pathology of SLE is driven by a loss of immune tolerance with the subsequent production of autoantibodies (IgG), and our laboratory previously demonstrated a mechanistic role for autoantibodies in autoimmune mediated hypertension. While anti-double stranded DNA (dsDNA) antibodies are pathognomonic for SLE, a breadth of autoantibodies may contribute to disease pathology. The goal of this study is to identify autoantibodies that may contribute to the renal and cardiovascular consequences associated with SLE. To accomplish this goal, an antigen array was performed (University of Texas Southwestern Genomics & Microarray Core Facility) using plasma samples collected from an established experimental mouse model of SLE (30 week old female NZBWF1, n=8) and healthy controls (30 week old female NZWLacJ, n=7). As anticipated, autoantibodies raised to nuclear antigens were prominently represented in the array and were significantly increased relative to control mice. This includes antibodies to dsDNA, ssRNA, chromatin, and histones (total) (p<0.02). In addition, SLE mice produce antibodies to mitochondrial antigens including cardiolipin and cytochrome C (p<0.02 vs control mice), critical components of the inner mitochondrial membrane and respiratory chain, respectively. In a separate study, renal mitochondrial function was tested using high resolution respirometry (Oroboros Instruments) in whole kidney homogenates from 30 week old female SLE (n=6) and control mice (n=5). Results show that coupled respiration, an estimation of oxidative phosphorylation, is significantly impaired at Complex I in kidneys from SLE mice compared to healthy controls (62±9 vs. 90±7 pmol/s/mg tissue, p<0.05). Uncoupled respiration, an estimation of maximal electron transport, is also reduced in the kidneys of female SLE mice compared to controls (157±23 vs. 212±14 pmol/s/mg tissue, p=0.07). These data provide insight for new mechanistic pathways to pursue in understanding the underlying mechanisms promoting cardiovascular risk factors like hypertension during SLE.

Analysis of magneto-natural convection and second law of thermodynamics of Cu-Al2O3-hybrid nanofluid in a vertical wavy cabinet having a localized non-uniform heat source

Improvements in thermal transference rate and minimization of entropy generation are critical issues in many industrial and engineering applications where heat transfer coefficient is essential to achieve optimal performance and minimal energy consumption. In the present investigation, a computational analysis has been conducted to analyze the impact of magnetic field on magneto-free convection and entropy generation inside a vertical wavy cabinet filled by Cu-Al2O3/H2O hybrid nanosuspension. In the geometry of this model, vertical boundaries of the chamber are designed as wavy and kept as cooled temperature (Tc), whereas the horizontal boundaries are modeled as square and are designed to be thermally adiabatic, except the centrally heated portion on the bottom wall. The centered bottom heated section is supposed to be isothermal with linearly changing temperature, and it changes linearly from Th1 to Th2, whereas it is modelled as a non-isothermal condition. The main focus, in this investigation, is on the entire chamber filled with the combination of hybrid nanoparticles regarded the volumetric concentration of copper and alumina nanoparticles (Cu-50 %+Al2O3-50 %) along with base liquid (H2O). The transformed dimensionless partial differential equations were solved by using finite volume method (FVM) with power law differencing scheme. The simulated flow and temperature fields are scrutinized by streamlines, isotherms, entropy formations, total entropy generation and average convective Nusselt number associated with varying number of undulations (0 ≤ N≤3) volume fraction of hybrid nano liquid (0 ≤ φ ≤ 0.04) magnetic orientation angles (0° ≤ ς ≤ 135°), Hartmann number (Ha = 0 and 50), and dimensionless temperature drop (Ω = 0.001–0.1). From this study, it is found that the average Nusselt number and entropy generation increase as the solid volume fraction of hybrid nanoadditives increases, while opposite trend is observed when the values of Hartmann number rises. The findings show that growth of undulation number (N) causes the reduction of convective heat transfer rate as well as average entropy production intensity. The obtained outcomes concluded that hybrid nano liquid is more effective and finest choice for the improvement of cooling of heat transfer process and minimal energy loss than single nanoliquid. According to the new proposed criterion (TPC), the results show that square-shaped enclosure (N=0) manifests the better cooling performance among the considered governing parameters. The novelty of this study is to scrutinize the flat/ vertical wavy boundaries of the cabinet which can be represented as a model of heat transfer controller, in which it manages the thermal and flow field characteristics. Predominantly, the isothermal line source is used to boost the overall convective heat transfer which is applied in buildings and fluid-mounted heaters. Additionally, many investigators have focused only on the enhancement of heat transfer. As it is known, to increase the thermodynamic efficiency of a system, optimization of entropy generation is an excellent tool which reduces the loss of energy. Hence, it recently does a good engineering sense to highlight an entropy irreversibility.

Modeling of an Adaptive HHO Gas Controller Based on Fuzzy Logic and Polynomial Function Controls to Improve Engine Torque of Gasoline Engine

Typical hydrogen-hydrogen-oxygen gas (HHO) usage to improve gasoline engine performance refers to the fixed HHO flow rate method, providing 0.25‒0.5 liters/minute of HHO for every 1000 cc engine size. However, the arising hypothesis expresses that the fixed HHO flow rate method does not optimally improve engine torque for various loads. The research objective is to propose an adaptive HHO gas controller that manages the HHO generator to produce an appropriate HHO flow rate for engine operation by adapting to load and engine speed variations. Hence, the engine torque improvement optimally occurs for various loads. The adaptive HHO controller combines fuzzy logic and polynomial function controls involving real-time engine data, such as mass airflow (MAF), air-fuel ratio (AFR), and the commanded AFR from the engine control unit (ECU), whose values vary with load and engine speed. A system simulation based on Matlab-Simulink investigates engine performance improvement due to the controller. The results show that the adaptive HHO flow rate due to the proposed adaptive HHO controller improves engine torque during small, medium, and big-loaded engine operations, respectively, by 1.5%‒4.7%, 6.8%‒26.8%, and 21.1%‒72.8% depending on engine speed 2500 rpm‒4000 rpm) and the commanded AFR (12.6‒15.4). Conversely, under the same condition, the fixed HHO flow rate with 0.75 liters/minute HHO for a 1500 cc engine, used for comparison, improves the engine torque by 0%‒0.6%, 0.3%‒14.2%, and 9.3%‒50.1%, respectively. The data show that the adaptive HHO controller provides better improvement. Moreover, the adaptive HHO controller improves engine thermal efficiency and reduces AFR error against the commanded AFR.

RNA sequencing reveals transcriptomic changes in PC-12 cells following plasminogen activator, tissue type overexpression.

Pheochromocytoma and paraganglioma, collectively known as PPGL, are categorized as neuroendocrine tumors with the potential for malignancy. Plasminogen activator, tissue type (PLAT) is a protein encoding gene that encodes tissue-type plasminogen activator, which converts plasminogen to plasmin. There is limited research on the association between PLAT and PPGL. Previous studies have only found that the expression level of PLAT protein is significantly increased in PPGL with deficient blood supply, and its role in the occurrence and progression of PPGL remains unclear and needs further clarification. The purpose of this study is to provide some new clues to elucidate the role of PLAT in PPGL, in order to better guide future research directions. The PC-12 cell line was selected for this study, and lentivirus transfection technology was used to construct control and PLAT overexpression cell models. Transcriptomic information of PLAT regulation in PC-12 cells was obtained through RNA sequencing, and differentially expressed genes (DEGs) were screened using bioinformatics methods. The physiological functions and related signaling pathways of these genes were analyzed. After validating the overexpression cell model and performing quality control analysis on the transcriptome sequencing data, DEGs were identified. The Gene Ontology (GO) functional enrichment analysis of DEGs revealed significant enrichment in 46 GO functions, while the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed significant enrichment in seven pathways. It was found that these genes were significantly enriched in functional pathways associated with mitochondrial respiratory chain and energy metabolism. This study provides some insights into the role of PLAT in pheochromocytoma and suggests directions for further research on its involvement in tumor development and angiogenesis. However, the specific regulatory mechanisms still require further validation.

CLigOpt: controllable ligand design through target-specific optimization.

A key challenge in deep generative models for molecular design is to navigate random sampling of the vast molecular space, and produce promising molecules that strike a balance across multiple chemical criteria. Fragment-based drug design (FBDD), using fragments as starting points, is an effective way to constrain chemical space and improve generation of biologically active molecules. Furthermore, optimization approaches are often implemented with generative models to search through chemical space, and identify promising samples which satisfy specific properties. Controllable FBDD has promising potential in efficient target-specific ligand design. We propose a controllable FBDD model, CLigOpt, which can generate molecules with desired properties from a given fragment pair. CLigOpt is a variational autoencoder-based model which utilizes co-embeddings of node and edge features to fully mine information from molecular graphs, as well as a multi-objective Controllable Generation Module to generate molecules under property controls. CLigOpt achieves consistently strong performance in generating structurally and chemically valid molecules, as evaluated across six metrics. Applicability is illustrated through ligand candidates for hDHFR and it is shown that the proportion of feasible active molecules from the generated set is increased by 10%. Molecular docking and synthesizability prediction tasks are conducted to prioritize generated molecules to derive potential lead compounds. The source code is available via https://github.com/yutongLi1997/CLigOpt-Controllable-Ligand-Design-through-Target-Specific-Optimisation.

Modelling of Vehicle Longitudinal Dynamics for Speed Control

Longitudinal dynamics control is one of the essential tasks for an autonomous vehicle, where it deals with speed regulation to ensure smooth and safe operations. To design a good controller, a simple yet reliable mathematical model is needed so that it can be used as a plant and to tune the controller. Although there are many types of mathematical models available in the literature, finding the right one for control application is essential. The model cannot be too complex and can be too simple. Thus, the main objective of this work is to derive a simple yet reliable vehicle longitudinal model so that it can be used as a simulation plant in MATLAB Simulink to test or tune various types of control algorithm's performance. The model consists of three main parts which are the vehicle body dynamics, simplified power train dynamic, and braking dynamic. To validate the reliability of the model, standard urban drive cycles will be used as a reference speed and a hierarchical PID control structure with inverse plant model is used to control the pedal inputs replacing the driver in simulation environment. Results show that the controller managed to track the drive cycle with an acceptable pedal pressing response which is between 40% throttle press and 20% brake press that in line with the normal operation of a vehicle. Although only simulation result is presented, the model can be used as a good starting point for further development and testing of different types of control algorithms for future work.

Highly sensitive protection scheme considering the PV operation control models

The integration of distributed generation (DG) based on inverters into power systems has increased significantly, necessitating a thorough understanding of its impact on fault analysis and the performance of distribution networks' protection mechanisms. This study addresses this issue by examining how various inverter management modes influence protective relay systems within IEEE 9-bus redial and mesh networks, CIGRE and IEEE 33-bus networks featuring Photovoltaic (PV) farms and Battery Energy Storage Systems (BESS), by IEEE1547–2018 and German grid code standards. By analyzing grid-connected scenarios with five distinct PV control modes, the research introduces a novel protection methodology termed the Photovoltaic Overcurrent Relay (PVOCR). This method introduces a current-voltage characteristic to optimally coordinate Overcurrent Relays (OCRs), aiming to reduce their operational time and eliminate mis-coordination events. The proposed PVOCR is evaluated against standard inverse time, SOCR, and modern adaptive voltage, VOCR, relay schemes across various fault scenarios differing in type and location. Furthermore, the PVOCR scheme effectively operates across all PV inverter modes without experiencing miscoordination events, whereas the SOCR and VOCR schemes encountered such issues during the operation of Control 4. These results underscore the potential utility of the PVOCR methodology in enhancing the reliability and efficiency of protection systems in inverter-based DG networks.

Cargo E-Bike Robust Speed Control Using an MPC Battery Thermal Lumped Model Approach

Cargo e-bikes are expected to convey heavy loads in all aspects of daily life. Also, these vehicles are expected to maintain a consistent speed to meet mobility needs while optimizing the battery design. In this paper, a control model is developed to improve rotational speed motor control via the battery model predictive controller (MPC) thermal model designed based on experimental field test data. Experimental field tests are performed to provide the relation between battery surface and ambient temperatures in different road types and weight conditions. For this purpose, in different slope ranges, the pedal load/activity and voltage-current data are logged to use as experimental input in an MPC-integrated 1D model. To obtain the desired thermal conditions in the Li-Ion battery, the MPC battery thermal model is defined based on the thermal lumped model approach. In the next step, the generated MPC model is used as a function for longitudinal speed control in the MPC motor torque control model subjected to uncertain road disturbances. Then, the outputs of the control models are compared using the MPC parameters oc weight factors and prediction horizon. Thus, the speed control model for cargo e-bikes is presented with increased robustness using the MPC battery thermal lumped model approach considering energy and Li-Ion battery life-cycle efficiency methods regardless of driving performance needs.

MRI T2w Radiomics-Based Machine Learning Models in Imaging Simulated Biopsy Add Diagnostic Value to PI-RADS in Predicting Prostate Cancer: A Retrospective Diagnostic Study.

Currently, prostate cancer (PCa) prebiopsy medical image diagnosis mainly relies on mpMRI and PI-RADS scores. However, PI-RADS has its limitations, such as inter- and intra-radiologist variability and the potential for imperceptible features. The primary objective of this study is to evaluate the effectiveness of a machine learning model based on radiomics analysis of MRI T2-weighted (T2w) images for predicting PCa in prebiopsy cases. A retrospective analysis was conducted using 820 lesions (363 cases, 457 controls) from The Cancer Imaging Archive (TCIA) Database for model development and validation. An additional 83 lesions (30 cases, 53 controls) from Hong Kong Queen Mary Hospital were used for independent external validation. The MRI T2w images were preprocessed, and radiomic features were extracted. Feature selection was performed using Cross Validation Least Angle Regression (CV-LARS). Using three different machine learning algorithms, a total of 18 prediction models and 3 shape control models were developed. The performance of the models, including the area under the curve (AUC) and diagnostic values such as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were compared to the PI-RADS scoring system for both internal and external validation. All the models showed significant differences compared to the shape control model (all p < 0.001, except SVM model PI-RADS+2 Features p = 0.004, SVM model PI-RADS+3 Features p = 0.002). In internal validation, the best model, based on the LR algorithm, incorporated 3 radiomic features (AUC = 0.838, sensitivity = 76.85%, specificity = 77.36%). In external validation, the LR (3 features) model outperformed PI-RADS in predictive value with AUC 0.870 vs. 0.658, sensitivity 56.67% vs. 46.67%, specificity 92.45% vs. 84.91%, PPV 80.95% vs. 63.64%, and NPV 79.03% vs. 73.77%. The machine learning model based on radiomics analysis of MRI T2w images, along with simulated biopsy, provides additional diagnostic value to the PI-RADS scoring system in predicting PCa.

The impact of refrigerant leakage on the dynamic operating performance of R600a refrigerator systems

Refrigerant leakage in refrigeration and freezing systems reduces efficiency and even results in reliable risks like insufficient cooling and component damage. This paper establishes a dynamic model of a dual-temperature zone refrigerator that combines physical and control models. It investigates the impact of refrigerant micro-leakage on the system’s dynamic operational performance, studies the effects of different leakage areas and compressor speeds on leakage performance, and identifies the critical leakage area (Ac) and critical compressor speed (Rc) based on the temperature variation patterns within the cabinets. Furthermore, this paper analyzes the coupled influence of the compressor speed and leakage area on the cabinet’s temperature. The findings reveal that after leakage occurs, the first noticeable deviations are in system pressure and the amount of refrigerant in the accumulator. Once the refrigerant in the accumulator fully vaporizes, the temperature in the cabinets is affected. Throughout the leakage process, both the system pressure and the heat exchange capacity of the evaporator decrease. At a compressor speed of 2000 rpm, the critical leakage area is 0.013 mm2, and the maximum refrigerant leakage that allows the refrigerator cabinet to cool to the shutdown temperature is 67.6 %. If the leakage area is larger than Ac, it reduces the time for alternating cooling between the freezer and refrigeration cabinets, resulting in a rapid rise in the comprehensive weighted average temperature deviation (CATD). For smaller leakage areas (<0.015 mm2), Rc exists. Operating the compressor at Rc can significantly reduce CATD. For larger leakage areas (≥0.015 mm2), Rc does not exist, increasing compressor speed has a lesser impact on CATD. The research results provide guidance for establishing a refrigerant leakage detection system and improving its accuracy, enhancing the operational reliability of refrigeration systems.

Temperature Control System Design Via Fuzzy PID

This paper investigates the integration of Fuzzy Logic with PID (Proportional, Integral, Derivative) controllers to enhance the performance of temperature control systems. Traditional PID controllers, widely used in various applications, often encounter difficulties with nonlinear, time-varying, and uncertain systems, resulting in performance issues like oscillations and overshoots. To mitigate these challenges, the adoption of Fuzzy PID control, which improves adaptability, robustness, and responsiveness by incorporating fuzzy logic into the control mechanism. The study involves simulations using Simulink to compare three distinct control models: conventional PID, standalone Fuzzy Control, and the hybrid Fuzzy PID Control across standardized control scenarios. Our results show that Fuzzy PID controllers significantly outperform traditional methods, especially in complex environments lacking precise mathematical modeling. The enhanced system response times and stability demonstrated by Fuzzy PID controllers suggest substantial potential for broader application across diverse industries, promising considerable improvements in operational efficiency and reliability.

Design, modeling, and validation of a 0.5 kWh flywheel energy storage system using magnetic levitation system

The flywheel energy storage system (FESS) has excellent power capacity and high conversion efficiency. It could be used as a mechanical battery in the uninterruptible power supply (UPS). The magnetic suspension technology is used in the FESS to reduce the standby loss and improve the power capacity. First, the whole system of the FESS with the magnetic levitation system is introduced, and the control diagrams of the charging/discharging processes are developed. Moreover, the force modeling of the magnetic levitation system, including the axial thrust-force permanent magnet bearing (PMB) and the active magnetic bearing (AMB), is conducted, and results indicate that the magnetic forces could stably levitate the flywheel (FW) rotor. The stator part and the FW rotor are analyzed using the FEM model, and the results could satisfy the requirements on stress and strength of the FESS at the rated speed. Then, the control models are established to accomplish the rapid charging/discharging functions of the FESS. Finally, experiments are performed to test the charging/discharging ability, and the results show that an excellent control current could enhance the charging/discharging efficiency so the stable DC link voltage could be outputted at the discharge process. Therefore, the test results prove that the designed FESS could be used as an auxiliary power supply for the UPS when the grid power fails.