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28 pages, 5564 KB  
Article
Virtual Model Development and Control for an EV3 BallBot Robotic System
by Gerardo Escandon-Esparza and Francisco Jurado
Processes 2025, 13(8), 2616; https://doi.org/10.3390/pr13082616 - 18 Aug 2025
Viewed by 632
Abstract
In this paper, the virtual model development and control for a BallBot Robotic System (BRS) are addressed. A virtual three-dimensional (3-D) EV3 BRS (EV3BRS) model is here developed through the Simscape Multibody environment from a BRS designed using the kit LEGO [...] Read more.
In this paper, the virtual model development and control for a BallBot Robotic System (BRS) are addressed. A virtual three-dimensional (3-D) EV3 BRS (EV3BRS) model is here developed through the Simscape Multibody environment from a BRS designed using the kit LEGO® MINDSTORMS® EV3. The mathematical model from the BRS is obtained through the Euler–Lagrange approach and used as the foundation to develop the EV3BRS Simscape model. The electrical model for the motors is derived through Kirchhoff’s laws. To verify the dynamics of the EV3BRS Simscape model, a Takagi–Sugeno Fuzzy Controller (TSFC) is designed using the Parallel Distributed Compensation (PDC) technique. Control gains are computed via Linear Matrix Inequalities (LMIs). To test the EV3BRS Simscape model under disturbances, an input voltage anomaly is considered. So, adding an H attenuation to the TSFC ensures that the EV3BRS Simscape model faces these kind of anomalies. Simulation results confirm that the TSFC with H attenuation improves the performance under anomalies at the input in contrast with the nominal TSFC, although this latter can maintain the body of the system near the upright position also. The dynamics from the EV3BRS Simscape model here developed allow us to realize how the real system will behave. Full article
(This article belongs to the Special Issue Modeling and Simulation of Robot Intelligent Control System)
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21 pages, 1569 KB  
Article
A Multibody-Based Benchmarking Framework for the Control of the Furuta Pendulum
by Gerardo Peláez, Pablo Izquierdo, Gustavo Peláez and Higinio Rubio
Actuators 2025, 14(8), 377; https://doi.org/10.3390/act14080377 - 31 Jul 2025
Viewed by 295
Abstract
The Furuta pendulum is a well-known benchmark in the field of underactuated mechanical systems due to its reduced number of control inputs compared to its degrees of freedom, and richly nonlinear behavior. This work addresses the challenge of accurately modeling and controlling such [...] Read more.
The Furuta pendulum is a well-known benchmark in the field of underactuated mechanical systems due to its reduced number of control inputs compared to its degrees of freedom, and richly nonlinear behavior. This work addresses the challenge of accurately modeling and controlling such a system without relying on traditional linearization techniques. In contrast to the common approach based on Lagrangian analytical modeling and state–space linearization, we propose a methodology that integrates a high-fidelity multibody model developed in Simscape Multibody (MATLAB), capturing the complete nonlinear dynamics of the system. The multibody model includes all geometric, inertial, and joint parameters of the physical hardware and interfaces directly with Simulink, enabling realistic simulation and control integration. To validate the physical fidelity of the multibody model, we perform a frequency-domain analysis of the pendulum’s natural free response. The dominant vibration frequency extracted from the simulation is compared with the theoretical prediction, demonstrating accurate capture of the system’s inertial and dynamic properties. This validation strategy strengthens the reliability of the model as a digital twin. The classical analytical formulation is provided to validate the simulation model and serve as a comparative framework. This dual modeling strategy allows for benchmarking control strategies against a trustworthy nonlinear digital twin of the Furuta pendulum. Preliminary experimental results using a physical prototype validate the feasibility of the proposed approach and set the foundation for future work in advanced nonlinear control design using the multibody representation as a digital validation tool. Full article
(This article belongs to the Special Issue Dynamics and Control of Underactuated Systems)
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23 pages, 7106 KB  
Article
A Simulation-Based Comparative Study of Advanced Control Strategies for Residential Air Conditioning Systems
by Jonadri Bundo, Donald Selmanaj, Genci Sharko, Stefan Svensson and Orion Zavalani
Eng 2025, 6(8), 170; https://doi.org/10.3390/eng6080170 - 24 Jul 2025
Viewed by 432
Abstract
This study presents a simulation-based evaluation of advanced control strategies for residential air conditioning systems, including On–Off, PI, and Model Predictive Control (MPC) approaches. A black-box system model was identified using an ARX(2,2,0) structure, achieving over 90% prediction accuracy (FIT) for indoor temperature [...] Read more.
This study presents a simulation-based evaluation of advanced control strategies for residential air conditioning systems, including On–Off, PI, and Model Predictive Control (MPC) approaches. A black-box system model was identified using an ARX(2,2,0) structure, achieving over 90% prediction accuracy (FIT) for indoor temperature and power consumption. Six controllers were implemented and benchmarked in a high-fidelity Simscape environment under a realistic 48-h summer temperature profile. The proposed MPC scheme, particularly when incorporating outdoor temperature gradient logic, reduced energy consumption by up to 30% compared to conventional PI control while maintaining indoor thermal comfort within the acceptable range. This virtual design workflow shortens the development cycle by deferring climatic chamber testing to the final validation phase. Full article
(This article belongs to the Section Chemical, Civil and Environmental Engineering)
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34 pages, 5960 KB  
Article
Motor Temperature Observer for Four-Mass Thermal Model Based Rolling Mills
by Boris M. Loginov, Stanislav S. Voronin, Roman A. Lisovskiy, Vadim R. Khramshin and Liudmila V. Radionova
Sensors 2025, 25(14), 4458; https://doi.org/10.3390/s25144458 - 17 Jul 2025
Viewed by 331
Abstract
Thermal control in rolling mills motors is gaining importance as more and more hard-to-deform steel grades are rolled. The capabilities of diagnostics monitoring also expand as digital IIoT-based technologies are adopted. Electrical drives in modern rolling mills are based on synchronous motors with [...] Read more.
Thermal control in rolling mills motors is gaining importance as more and more hard-to-deform steel grades are rolled. The capabilities of diagnostics monitoring also expand as digital IIoT-based technologies are adopted. Electrical drives in modern rolling mills are based on synchronous motors with frequency regulation. Such motors are expensive, while their reliability impacts the metallurgical plant output. Hence, developing the on-line temperature monitoring systems for such motors is extremely urgent. This paper presents a solution applying to synchronous motors of the upper and lower rolls in the horizontal roll stand of plate mill 5000. The installed capacity of each motor is 12 MW. According to the digitalization tendency, on-line monitoring systems should be based on digital shadows (coordinate observers) that are similar to digital twins, widely introduced at metallurgical plants. Modern reliability requirements set the continuous temperature monitoring for stator and rotor windings and iron core. This article is the first to describe a method for calculating thermal loads based on the data sets created during rolling. The authors have developed a thermal state observer based on four-mass model of motor heating built using the Simscape Thermal Models library domains that is part of the MATLAB Simulink. Virtual adjustment of the observer and of the thermal model was performed using hardware-in-the-loop (HIL) simulation. The authors have validated the results by comparing the observer’s values with the actual values measured at control points. The discrete masses heating was studied during the rolling cycle. The stator and rotor winding temperature was analysed at different periods. The authors have concluded that the motors of the upper and lower rolls are in a satisfactory condition. The results of the study conducted generally develop the idea of using object-oriented digital shadows for the industrial electrical equipment. The authors have introduced technologies that improve the reliability of the rolling mills electrical drives which accounts for the innovative development in metallurgy. The authors have also provided recommendations on expanded industrial applications of the research results. Full article
(This article belongs to the Section Industrial Sensors)
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30 pages, 5051 KB  
Article
Design and Validation of an Active Headrest System with Integrated Sensing in Rear-End Crash Scenarios
by Alexandru Ionut Radu, Bogdan Adrian Tolea, Horia Beles, Florin Bogdan Scurt and Adrian Nicolaie Tusinean
Sensors 2025, 25(14), 4291; https://doi.org/10.3390/s25144291 - 9 Jul 2025
Viewed by 409
Abstract
Rear-end collisions represent a major concern in automotive safety, particularly due to the risk of whiplash injuries among vehicle occupants. The accurate simulation of occupant kinematics during such impacts is critical for the development of advanced safety systems. This paper presents an enhanced [...] Read more.
Rear-end collisions represent a major concern in automotive safety, particularly due to the risk of whiplash injuries among vehicle occupants. The accurate simulation of occupant kinematics during such impacts is critical for the development of advanced safety systems. This paper presents an enhanced multibody simulation model specifically designed for rear-end crash scenarios, incorporating integrated active headrest mechanisms and sensor-based activation logic. The model combines detailed representations of vehicle structures, suspension systems, restraint systems, and occupant biomechanics, allowing for the precise prediction of crash dynamics and occupant responses. The system was developed using Simscape Multibody, with CAD-derived components interconnected through physical joints and validated using controlled experimental crash tests. Special attention was given to modelling contact forces, suspension behaviour, and actuator response times for the active headrest system. The model achieved a root mean square error (RMSE) of 4.19 m/s2 and a mean absolute percentage error (MAPE) of 0.71% when comparing head acceleration in frontal collision tests, confirming its high accuracy. Validation results demonstrate that the model accurately reproduces occupant kinematics and head acceleration profiles, confirming its reliability and effectiveness as a predictive tool. This research highlights the critical role of integrated sensor-actuator systems in improving occupant safety and provides a flexible platform for future studies on intelligent vehicle safety technologies. Full article
(This article belongs to the Special Issue Intelligent Sensors for Smart and Autonomous Vehicles)
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23 pages, 4668 KB  
Article
Dynamic Modeling and Analysis of Industrial Robots for Enhanced Manufacturing Precision
by Claudius Birk, Martin Kipfmüller and Jan Kotschenreuther
Actuators 2025, 14(7), 311; https://doi.org/10.3390/act14070311 - 24 Jun 2025
Viewed by 741
Abstract
This study addresses the challenge of accurately modeling the dynamic behavior of industrial robots for precision manufacturing applications. Using a comprehensive experimental approach with modal impulse hammer testing and triaxial acceleration measurements, 360 frequency response functions were recorded along orthogonal measurement paths for [...] Read more.
This study addresses the challenge of accurately modeling the dynamic behavior of industrial robots for precision manufacturing applications. Using a comprehensive experimental approach with modal impulse hammer testing and triaxial acceleration measurements, 360 frequency response functions were recorded along orthogonal measurement paths for a KUKA KR10 robot. Two dynamic models with different parameter dimensions (12-parameter and 24-parameter) were developed in Matlab/Simscape, and their parameters were identified using genetic algorithm optimization. The KUKA KR10 features Harmonic Drives at each joint, whose high transmission ratio and zero backlash characteristics significantly influence rotational dynamics and allow for meaningful static structural measurements. Objective functions based on the Frequency Response Assurance Criterion (FRAC) and Root Mean Square Error (RMSE) metrics were employed, utilizing a frequency-dependent weighting function. The performance of the models was evaluated across different robot configurations and frequency ranges. The 24-parameter model demonstrated significantly superior performance, achieving 70% overall average Global FRAC in the limited frequency range (≤200 Hz) compared to 41% for the 12-parameter model when optimized using a representative subset of 9 measurement points. Both models showed substantially better performance in the limited frequency range than in the full spectrum. This research provides a validated methodology for dynamic characterization of industrial robots and demonstrates that higher-dimensional models, incorporating transverse joint compliance, can accurately represent robot dynamics up to approximately 200 Hz. Future work will investigate nonlinear effects such as torsional stiffness hysteresis, particularly relevant for Harmonic Drive systems. Full article
(This article belongs to the Special Issue Actuation and Sensing of Intelligent Soft Robots)
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20 pages, 3122 KB  
Article
Data-Driven MPC with Multi-Layer ReLU Networks for HVAC Optimization Under Iraq’s Time-of-Use Electricity Pricing
by Alaa Shakir, Ghamgeen Izat Rashed, Yigang He and Xiao Wang
Processes 2025, 13(7), 1985; https://doi.org/10.3390/pr13071985 - 23 Jun 2025
Viewed by 573
Abstract
Enhancing the energy management capabilities of modern smart buildings is essential for energy conservation, which is valuable for modern power networks maintaining a tight power balance under high renewable penetration. This study introduces a data-driven control strategy based on the model predictive control [...] Read more.
Enhancing the energy management capabilities of modern smart buildings is essential for energy conservation, which is valuable for modern power networks maintaining a tight power balance under high renewable penetration. This study introduces a data-driven control strategy based on the model predictive control (MPC) for HVAC (heating, ventilation, and air conditioning) systems considering the time-of-use (ToU) electricity rates in Iraq. A multi-layer neural network is first constructed using time-delayed embedding for the modeling of building thermal dynamics, where the rectified linear unit (ReLU) is used as the activation function for the hidden layers. Based on such piecewise affine approximation, an optimization model is developed within the receding horizon control framework, which incorporates the data-driven model and is transformed into a mixed-integer linear programming facilitating efficient problem solving. To validate the efficiency of the proposed approach, a simulation model of the building’s thermal network is constructed using Simscape considering several thermal effects among the building components. Simulation results demonstrate that the proposed approach improves the economic performance of the building while maintaining thermal comfort levels within acceptable range. Full article
(This article belongs to the Special Issue Sustainable Development of Energy and Environment in Buildings)
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25 pages, 3538 KB  
Article
Photovoltaic System Performance Under Partial Shading Conditions: Insight into the Roles of Bypass Diode Numbers and Inverter Efficiency Curve
by Hatice Gül Sezgin-Ugranlı
Sustainability 2025, 17(10), 4626; https://doi.org/10.3390/su17104626 - 18 May 2025
Cited by 1 | Viewed by 796
Abstract
Partial shading is a common challenge influencing the performance of photovoltaic (PV) systems, particularly in urban and residential applications. A practical solution to mitigate hotspot formation due to shading is the use of bypass diodes. Increasing the number of bypass diodes further enhances [...] Read more.
Partial shading is a common challenge influencing the performance of photovoltaic (PV) systems, particularly in urban and residential applications. A practical solution to mitigate hotspot formation due to shading is the use of bypass diodes. Increasing the number of bypass diodes further enhances PV system performance but alters the global maximum power points (MPPs), shifting their voltage locations and power magnitudes, consequently resulting in a change in the operating points in the efficiency curve of the inverters. This study investigates the impact of bypass diode numbers and inverter efficiency curves on PV system performance under various partial shading conditions. The analysis systematically deals with three inverters with different efficiency characteristics in terms of loading and input voltage, as well as module configurations with different numbers of bypass diodes. Additionally, three more factors—ambient temperature, inverter loading ratio by varying the number of series-connected PV modules, and shading intensity—are considered in the context of bypass diodes and inverter characteristics through the efficiency curve. The global MPPs of PV modules under different cases are simulated using a Simscape/Simulink-based circuit model with random irradiance samples. The results indicate the formation of bands according to the voltage that vary with bypass diode configurations. In this manner, utilizing the probabilities of these bands and inverter efficiency curves, the average PV system performance is determined for each case. The findings reveal the effects of the relationship between bypass diode configurations and inverter efficiency on PV system performance. As partial shading is especially common in dense urban areas, the results are of interest for the development of resilient and sustainable PV installations. Full article
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16 pages, 3375 KB  
Article
Energy-Efficient Battery Thermal Management in Electric Vehicles Using Artificial-Neural-Network-Based Model Predictive Control
by Kiheon Nam and Changsun Ahn
World Electr. Veh. J. 2025, 16(5), 279; https://doi.org/10.3390/wevj16050279 - 17 May 2025
Cited by 2 | Viewed by 1553
Abstract
This study presents a Model Predictive Control (MPC) strategy for the Battery Thermal Management System (BTMS) in electric vehicles (EVs) to optimize energy efficiency while maintaining battery temperature within the optimal range. Due to the complexity of BTMS dynamics, a high-fidelity model was [...] Read more.
This study presents a Model Predictive Control (MPC) strategy for the Battery Thermal Management System (BTMS) in electric vehicles (EVs) to optimize energy efficiency while maintaining battery temperature within the optimal range. Due to the complexity of BTMS dynamics, a high-fidelity model was developed using MATLAB/Simscape (2021a), and an artificial neural network (ANN)-based model was designed to achieve high accuracy with reduced computational load. To mitigate oscillatory control inputs observed in conventional MPC, an infinity-horizon MPC framework was introduced, incorporating a value function that accounts for system behavior beyond the prediction horizon. The proposed controller was evaluated using a simulation environment against a conventional rule-based controller under varying ambient temperatures. Results demonstrated significant energy savings, including a 78.9% reduction in low-temperature conditions, a 36% reduction in moderate temperatures, and a 27.8% reduction in high-temperature environments. Additionally, the controller effectively stabilized actuator operation, improving system longevity. These findings highlight the potential of ANN-assisted MPC for enhancing BTMS performance while minimizing energy consumption in EVs. Full article
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33 pages, 4714 KB  
Article
Development of a Small CNC Machining Center for Physical Implementation and a Digital Twin
by Claudiu-Damian Petru, Fineas Morariu, Radu-Eugen Breaz, Mihai Crenganiș, Sever-Gabriel Racz, Claudia-Emilia Gîrjob, Alexandru Bârsan and Cristina-Maria Biriș
Appl. Sci. 2025, 15(10), 5549; https://doi.org/10.3390/app15105549 - 15 May 2025
Cited by 1 | Viewed by 810
Abstract
This work aimed to develop both a real implementation and a digital twin for a small CNC machining center. The X-, Y-, and Z-axes feed systems were realized as closed-loop motion loops with DC servo motors and encoders. Motion control was provided by [...] Read more.
This work aimed to develop both a real implementation and a digital twin for a small CNC machining center. The X-, Y-, and Z-axes feed systems were realized as closed-loop motion loops with DC servo motors and encoders. Motion control was provided by Arduino boards and Pololu motor drivers. A simulation study of the step response parameters was carried out, and then the positioning regime was studied, followed by the two-axis simultaneous motion regime (circular interpolation). This study, based on a hybrid simulation diagram realized in Simulink–Simscape, allowed a preliminary tuning of the PID (proportional integral derivative) controllers. Next, the CAE (computer-aided engineering) simulation diagram was complemented with the CAM (computer-aided manufacturing) simulation interface, the two together forming an integrated digital twin system. To validate the contouring performance of the proposed CNC system, a circular groove with an outer diameter of 31 mm and an inner diameter of 29 mm was machined using a 1 mm cylindrical end mill. The trajectory followed the simulated 30 mm circular path. Two sets of controller parameters were applied. Dimensional accuracy was verified using a GOM Atos Core 200 optical scanner and evaluated in GOM Inspect Suite 2020. The results demonstrated good agreement between simulation and physical execution, validating the PID tuning and system accuracy. Full article
(This article belongs to the Special Issue Advanced Digital Design and Intelligent Manufacturing)
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17 pages, 3089 KB  
Article
An Analysis of the Altitude Impact on Roots Compressor Operation for a Fuel Cell System
by Pedro Piqueras, Joaquín de la Morena, Enrique José Sanchis and Ibrahim Saadouni
Appl. Sci. 2025, 15(10), 5513; https://doi.org/10.3390/app15105513 - 14 May 2025
Cited by 1 | Viewed by 628
Abstract
Hydrogen fuel cell vehicles are one of the most promising alternatives to achieve transport decarbonization targets, thanks to their moderately high efficiency and low refueling time, combined with their zero-exhaust-emission operation. In order to reach reasonable power density figures, fuel cell systems are [...] Read more.
Hydrogen fuel cell vehicles are one of the most promising alternatives to achieve transport decarbonization targets, thanks to their moderately high efficiency and low refueling time, combined with their zero-exhaust-emission operation. In order to reach reasonable power density figures, fuel cell systems are generally supercharged by radial compressors, which can encounter significant limitations associated with surge and choke operation, especially at high altitudes. Alternatively, the current paper explores the altitude operation of a fuel cell system combined with a Roots compressor. First, the balance of the plant model is built in the Simscape platform, combining a physical and chemical 1D fuel cell model for the stack, calibrated against literature data at different pressure and temperature values, as well as the characteristic maps of the Roots compressor. Then, the model is used to explore the balance-of-plant operation in a working range between 10 and 200 kW and an altitude range between sea level and 5 km. The results show that the compressor is capable of operating around the highest efficiency area (between 60 and 70%) for a wide range of altitude and power conditions, limiting the negative impact of the altitude on the system efficiency to up to 3%. However, once the compressor efficiency falls below 60%, the balance-of-plant performance rapidly drops, overcoming the benefits of the working pressure on the fuel cell stack operation and limiting the peak net power produced. Full article
(This article belongs to the Special Issue Advances in Fuel Cell Renewable Hybrid Power Systems)
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16 pages, 6323 KB  
Article
Mechanistic Integration of Network Pharmacology and In Vivo Validation: TFRD Combat Osteoporosis via PI3K/AKT Pathway Activation
by Chang Tan, Shibo Cong, Yanming Xie and Yingjie Zhi
Int. J. Mol. Sci. 2025, 26(8), 3650; https://doi.org/10.3390/ijms26083650 - 12 Apr 2025
Viewed by 743
Abstract
In the context of osteoporosis closely linked to bone metabolism imbalance caused by estrogen deficiency, total flavonoids of Rhizoma Drynariae (TFRD) exhibit potential anti-osteoporotic activity, yet their multicomponent synergistic mechanism and association with the PI3K/AKT signaling pathway remain unclear. This study aimed to [...] Read more.
In the context of osteoporosis closely linked to bone metabolism imbalance caused by estrogen deficiency, total flavonoids of Rhizoma Drynariae (TFRD) exhibit potential anti-osteoporotic activity, yet their multicomponent synergistic mechanism and association with the PI3K/AKT signaling pathway remain unclear. This study aimed to systematically elucidate the molecular mechanisms by which TFRD regulate bone metabolism and improve osteoporosis in ovariectomized (OVX) rats through the PI3K/AKT pathway, integrating network pharmacological predictions with animal experimental validation. Methods involved identifying TFRD’s active components using UPLC/MS-MS, predicting targets with SwissTargetPrediction, constructing a “component-target-disease” network, and performing GO/KEGG enrichment analysis with MetaScape (v3.5). In vivo experiments established an OVX rat model, randomized into sham, OVX, low-/high-dose TFRD, and sim groups, assessing bone mineral density (BMD) and mandibular Micro-CT parameters after 12 weeks. Western blot analyzed PI3K, p-AKT1, and related protein expressions. Results showed the high-dose TFRD group significantly increased BMD, improved trabecular bone quantity and structure, and upregulated PI3K, p-PI3K, and p-AKT1 protein expressions compared to the OVX group. Molecular docking confirmed stable binding energy between core components and PI3K/AKT targets. TFRD may ameliorate estrogen deficiency-induced osteoporosis by activating the PI3K/AKT signaling pathway, inhibiting bone resorption, and promoting osteogenic differentiation, providing pharmacological evidence for multitarget treatment of osteoporosis with traditional Chinese medicine. Full article
(This article belongs to the Section Molecular Pharmacology)
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25 pages, 12941 KB  
Article
Dynamic Multibody Modeling of Spherical Roller Bearings with Localized Defects for Large-Scale Rotating Machinery
by Luca Giraudo, Luigi Gianpio Di Maggio, Lorenzo Giorio and Cristiana Delprete
Sensors 2025, 25(8), 2419; https://doi.org/10.3390/s25082419 - 11 Apr 2025
Cited by 3 | Viewed by 725
Abstract
Early fault detection in rotating machinery is crucial for optimizing maintenance and minimizing downtime costs, especially in medium-to-large-scale industrial applications. This study presents a multibody model developed in the Simulink® Simscape environment to simulate the dynamic behavior of medium-sized spherical bearings. The [...] Read more.
Early fault detection in rotating machinery is crucial for optimizing maintenance and minimizing downtime costs, especially in medium-to-large-scale industrial applications. This study presents a multibody model developed in the Simulink® Simscape environment to simulate the dynamic behavior of medium-sized spherical bearings. The model includes descriptions of the six degrees of freedoms of each subcomponent, and was validated by comparison with experimental measurements acquired on a test rig capable of applying heavy radial loads. The results show a good fit between experimental and simulated signals in terms of identifying characteristic fault frequencies, which highlights the model’s ability to reproduce vibrations induced by localized defects on the inner and outer races. Amplitude differences can be attributed to simplifications such as neglected housing compliancies and lubrication effects, and do not alter the model’s effectiveness in detecting fault signatures. In conclusion, the developed model represents a promising tool for generating useful datasets for training diagnostic and prognostic algorithms, thereby contributing to the improvement of predictive maintenance strategies in industrial settings. Despite some amplitude discrepancies, the model proves useful for generating fault data and supporting condition monitoring strategies for industrial machinery. Full article
(This article belongs to the Special Issue Feature Papers in Fault Diagnosis & Sensors 2025)
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17 pages, 7222 KB  
Article
Flexibly Parameterizable Vehicle Dynamics Models
by Dániel Nemes and Sándor Hajdu
Designs 2025, 9(2), 46; https://doi.org/10.3390/designs9020046 - 9 Apr 2025
Viewed by 612
Abstract
The following article presents the longitudinal modeling and simulation of a generic electric vehicle. The purpose of the research is to describe the applied modeling procedures and their MATLAB solutions. Furthermore, the goal is to demonstrate how to build a framework for a [...] Read more.
The following article presents the longitudinal modeling and simulation of a generic electric vehicle. The purpose of the research is to describe the applied modeling procedures and their MATLAB solutions. Furthermore, the goal is to demonstrate how to build a framework for a MATLAB R2024b Simulink and Simscape model that facilitates future optimization and ensures modularity, thereby facilitating collaboration among different research groups. After presenting the applied vehicle dynamics model and the created framework, some additional application examples are presented for which the method has already been tested. Full article
(This article belongs to the Section Vehicle Engineering Design)
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22 pages, 1086 KB  
Article
Design of Experiments Approach for Structural Optimization of Urban Air Mobility Vehicles
by Marco Claudio De Simone, Salvio Veneziano, Alessia Porcaro and Domenico Guida
Actuators 2025, 14(4), 176; https://doi.org/10.3390/act14040176 - 3 Apr 2025
Viewed by 624
Abstract
The current global context demands the development of new solutions that prioritize energy efficiency, time optimization, safety, and sustainability. Urban transportation is one of the sectors undergoing significant transformation. Pursuing new urban transportation solutions has become increasingly intense, involving research institutions and companies. [...] Read more.
The current global context demands the development of new solutions that prioritize energy efficiency, time optimization, safety, and sustainability. Urban transportation is one of the sectors undergoing significant transformation. Pursuing new urban transportation solutions has become increasingly intense, involving research institutions and companies. Considering this context, this study focused on the optimization procedures for designing a new vehicle capable of vertical take-off for urban air mobility applications. This paper reports on the optimization process of a thruster deployment mechanism using statistical techniques. In particular, the authors tested the use of Design of Experiments (DOE) techniques for the optimal design of a structural component of a new vehicle for urban mobility purposes under development at the Applied Mechanics laboratory of the Department of Industrial Engineering of the University of Salerno. For this reason, it was decided that a parametric multibody model would be developed in the Simscape Multibody environment for structural optimization using designed experiment plans to “guide” the designer in the analysis phase and search for an optimal configuration using a minimum number of configurations. Finally, employing FEM analysis, the chosen configuration was validated. This study allowed us to test the use of DOE techniques to design new systems. It allowed us to evaluate different configurations, the static and dynamic behavior, the constraining reactions present in the joints, and the active forces and torques of the actuators, highlighting the correlation between factors that can guide the designer in identifying optimal solutions. Full article
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