Journal Description
Machines
Machines
is an international, peer-reviewed, open access journal on machinery and engineering, published monthly online by MDPI. The International Federation for the Promotion of Mechanism and Machine Science (IFToMM) is affiliated with Machines and its members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Inspec, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Mechanical) / CiteScore - Q1 (Control and Optimization)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.6 days after submission; acceptance to publication is undertaken in 2.7 days (median values for papers published in this journal in the second half of 2025).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Journal Cluster of Mechanical Manufacturing and Automation Control: Aerospace, Automation, Drones, Journal of Manufacturing and Materials Processing, Machines, Robotics and Technologies.
Impact Factor:
2.5 (2024);
5-Year Impact Factor:
2.6 (2024)
Latest Articles
Design and Implementation of a Model Elevator System for Mechatronics Education
Machines 2026, 14(5), 578; https://doi.org/10.3390/machines14050578 (registering DOI) - 21 May 2026
Abstract
Elevators exemplify mechatronics by integrating mechanical, electrical, and software systems. This paper discusses a four-story tabletop elevator model developed to demonstrate mechatronics and automation concepts in engineering education. The system utilized an Arduino MEGA microcontroller, 3D-printed components, an integrated servo motor, and standard
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Elevators exemplify mechatronics by integrating mechanical, electrical, and software systems. This paper discusses a four-story tabletop elevator model developed to demonstrate mechatronics and automation concepts in engineering education. The system utilized an Arduino MEGA microcontroller, 3D-printed components, an integrated servo motor, and standard electronics to replicate commercial elevator logic. The physical design features a ball screw linear actuator for vertical motion. It replicates dual-door systems with one door on the moving car and fixed doors at each floor that open simultaneously upon arrival. Development included designing the physical model, prototyping control algorithms, and integrating hardware and software. The model successfully demonstrated key functions: automatic dual-door operation, safety interlocks, smooth inter-floor motion, responsive floor-selection buttons with LED feedback, and efficient routing algorithms prioritizing requests based on current direction and location. Performance testing confirmed that the model accurately replicates modern elevator behavior and serves as an effective educational tool.
Full article
(This article belongs to the Special Issue The New Digital Era in Industrial Robotics, Mechatronics and Factory Automation)
Open AccessArticle
Material Homogeneity Criterion for Assessing Heterogeneous High-Strength Steel Joints with Austenitic Welds
by
Yaroslav Kusyi, Vitalii Ivanov, Andriy Dzyubyk, Nazarii Kusen and Juraj Hajduk
Machines 2026, 14(5), 577; https://doi.org/10.3390/machines14050577 (registering DOI) - 21 May 2026
Abstract
The modernization of global energy infrastructure within the Industry 5.0 framework requires the use of high-strength steels and reliable joining technologies to ensure safe, sustainable pipeline transport. This study focuses on the analysis of heterogeneous welded joints formed between high-strength alloy steel (34KhN2MA/EN
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The modernization of global energy infrastructure within the Industry 5.0 framework requires the use of high-strength steels and reliable joining technologies to ensure safe, sustainable pipeline transport. This study focuses on the analysis of heterogeneous welded joints formed between high-strength alloy steel (34KhN2MA/EN 34CrNiMo6) and an austenitic welded seam (ER 307). While austenitic welds mitigate the risk of cold cracking, they introduce significant structural and mechanical heterogeneity. To address this, the research proposes and validates a material homogeneity criterion (MHC) derived from the LM-hardness methodology. By analyzing the statistical dispersion of macrohardness (HRC) through indicators such as the Weibull homogeneity coefficient (m) and the coefficient of variation (ν), the study establishes a quantitative approach to assess material degradation and structural uniformity across key weld zones. Results demonstrate that macrohardness profiling effectively distinguishes between structurally heterogeneous regions near the weld axis characterized by low homogeneity coefficients (m = 4.04 < 10, Am = 0.742 < 0.878), elevated variability (ν = 29.68% > 11.6%), and high technological damageability (D = 0.92 > 0.81, jD = 11.87 > 4.38) with pronounced step-like variation in macrohardness (HRC ∈ [12.6; 47]), on the one hand, and stabilized homogeneous zones in the base material, where m = 24.89 > 10, Am = 0.947 > 0.878, ν = 4.39% < 11.6%, D = 0.52 ⟶ 0, jD = 1.09 ⟶ 0, and characteristic range of HRC = 47–55, on the other hand. This methodology provides a robust, quasi-non-destructive tool for enhancing predictive maintenance, digital twins, and the overall integrity management of “smart” pipeline systems.
Full article
(This article belongs to the Special Issue Innovations in the Design, Simulation, and Manufacturing of Production Systems)
Open AccessArticle
Displacement Centre of Gravity and Stability Arm in Longitudinal Tilt of a Floating Body with Circular Floats
by
Leopold Hrabovský, Pavla Karbanová and Ladislav Kovář
Machines 2026, 14(5), 576; https://doi.org/10.3390/machines14050576 (registering DOI) - 21 May 2026
Abstract
Floating belt conveyor routes consisting of serially arranged belt conveyors, the end parts of which are mechanically attached to floating bodies, are designed for the continuous transport of extracted granular materials from water. This paper deals with the analytical determination of the position
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Floating belt conveyor routes consisting of serially arranged belt conveyors, the end parts of which are mechanically attached to floating bodies, are designed for the continuous transport of extracted granular materials from water. This paper deals with the analytical determination of the position of the centre of gravity of the buoyancy force, the coordinates of which change depending on the longitudinal deflection of the floating body from the equilibrium state, which acts as a supporting element of individual conveyor belts. Analysis of the individual phases of deflection of the floating body, consisting of a pair of floats with a circular cross-section, shows that the complete submergence of one of the floats occurs at a higher value of the angle of inclination in the case when the floats are initially submerged under the surface to exactly half their diameter. On the realized experimental device, the buoyancy force was detected using strain gauges during the deflection of the floating body from the equilibrium position for three defined levels of immersion. The floating body of the experimental device consists of a pair of floats with a circular cross-section with a diameter of 80 mm. The output is a structured methodological procedure for determining the position of the centre of gravity of the displacement (centre of buoyancy) of a floating body when it deviates from the equilibrium position and a methodology for calculating the stability arm, which is a key parameter for assessing the buoyancy and stability of the body. On the basis of the laboratory measurements, the magnitude of the buoyancy force can be quantified as a function of the immersion depth of the floating body. It was found that the buoyancy force remains constant when the body deflects only when the immersion corresponds to half the diameter of a float with a circular cross-section. If the depth of the immersion is less than the radius of the float, the buoyancy force increases during deflection; however, if the immersion is greater than the radius of the float, the buoyancy force decreases.
Full article
(This article belongs to the Section Automation and Control Systems)
Open AccessArticle
Analytical Modeling of Slot Leakage Inductance for Hairpin Windings
by
Hasnain Nisar and Ali M. Bazzi
Machines 2026, 14(5), 575; https://doi.org/10.3390/machines14050575 (registering DOI) - 21 May 2026
Abstract
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With the increasing demand for higher efficiency and power density, innovative winding techniques have become crucial in modern electric machines. Hairpin windings are increasingly used in electric machines, particularly in high-current applications. A novel analytical model is proposed to estimate slot leakage inductance
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With the increasing demand for higher efficiency and power density, innovative winding techniques have become crucial in modern electric machines. Hairpin windings are increasingly used in electric machines, particularly in high-current applications. A novel analytical model is proposed to estimate slot leakage inductance in hairpin windings. Traditional models are limited to random windings, which fail to capture the complex mutual inductance between multiple coil layers. This paper derives a generalized model to estimate specific permeance and total mutual specific permeance for the hairpin windings, which are key factors in determining slot leakage inductance. The proposed model is also valid for fractional-pitch windings. The derived analytical model is validated through finite element analysis (FEA) on an electric motor similar to that employed in Tesla Model S. In addition, experimental validation is performed to further validate the proposed model. Furthermore, parametric analysis is conducted to analyze the influence of slot geometry and conductor dimensions on the slot leakage inductance. This paper contributes an accurate method for predicting slot leakage inductance in hairpin windings; this provides electrical machine designers with a valuable tool for precise modeling and optimization for improved efficiency and performance in various applications.
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Open AccessArticle
The Unreasonable Effectiveness of Neural Operators and Mambas in Detecting and Quantifying Electrical Machine Faults: A Case Study on Eccentricity
by
Latifa Yusuf, Belaid Moa and Ilamparithi Thirumarai Chelvan
Machines 2026, 14(5), 574; https://doi.org/10.3390/machines14050574 (registering DOI) - 21 May 2026
Abstract
Reliable fault detection and quantification are essential for the operational integrity of electric machines. While traditional current-based analysis relies on harmonic signatures or wavelet-based time-frequency representations, this study investigates modern learning formulations that capture spectral, multiscale, and temporal characteristics of fault-affected signals. Moving
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Reliable fault detection and quantification are essential for the operational integrity of electric machines. While traditional current-based analysis relies on harmonic signatures or wavelet-based time-frequency representations, this study investigates modern learning formulations that capture spectral, multiscale, and temporal characteristics of fault-affected signals. Moving beyond conventional models, including our earlier CNN-based approaches, we develop sequence-based and operator-learning architectures within a multi-output formulation for eccentricity fault analysis. Three models are investigated: Mamba for temporal dynamics, the Fourier Neural Operator for global spectral mapping, and the Wavelet Neural Operator for localized multiscale decomposition. Evaluated on induction, salient pole synchronous, and inverter-based reluctance synchronous machines, each model maps stator current waveforms to multiple diagnostic quantities, including voltages, operating conditions, and fault severity. With time-delay embedding, all three achieve low prediction errors, with severity RMSE reaching the scale for the induction machine, a notable reduction from the errors of our earlier hierarchical CNN models. These results show that modern sequence-based and operator-learning formulations can broaden machine fault analysis by enabling simultaneous prediction and estimation of multiple aspects of machine condition within a single model.
Full article
(This article belongs to the Special Issue Data-Driven Fault Diagnosis for Machines and Systems, 2nd Edition)
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Open AccessArticle
Friction and Wear Behavior of General Freight Train Composite Brake Shoes with Reinforced Steel Fibers
by
Hengxi Wang, Xin Zhang, Guansong Chen, Jiazheng Song, José Manuel Martínez-Esnaola and Chun Lu
Machines 2026, 14(5), 573; https://doi.org/10.3390/machines14050573 (registering DOI) - 21 May 2026
Abstract
High friction composite brake shoes containing reinforced steel fibers are now widely used in freight train tread braking systems. With the demand for higher transportation efficiency on railway lines with long steep slopes, it is necessary to explore the braking capabilities of existing
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High friction composite brake shoes containing reinforced steel fibers are now widely used in freight train tread braking systems. With the demand for higher transportation efficiency on railway lines with long steep slopes, it is necessary to explore the braking capabilities of existing general freight train high friction composite brake shoes under continuous braking conditions. In this paper, continuous braking tests at different speed levels were conducted using a friction and wear test rig. Through material characterization and interface damage analysis, it was found that reinforced steel fibers can exist as a contact platform at the brake shoe friction interface. Due to the strip-like morphology and high strength features of steel fibers, even after the steel fiber layer is fragmented, it can still promote the formation of a continuous contact platform with complex material composition on the surface, maintaining the progress of the braking process. For existing general freight train high friction composite brake shoes, at speeds up to 80 km/h, although the friction coefficient decreases to some extent, the wear rate maintains a relatively low range. When the speed increases to 100 km/h, the friction coefficient of the braking interface deteriorates severely, and the wear rate of the brake shoe increases sharply, seriously endangering braking safety. The research results reveal the evolution of wear behavior of high friction composite brake shoes containing reinforced steel fibers at different speed levels, providing theoretical support for exploring the braking capabilities and design optimization of brake shoes.
Full article
(This article belongs to the Special Issue Research and Application of Rail Vehicle Technology)
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Open AccessReview
A Review of Variable Stiffness in Continuum Robots: Mechanisms, Modeling and Control
by
Dexin Cheng, Tianao Zhang, Huanyu Deng, Compus Gan Yu Hong, Shihai Zhao, Yongzhuo Gao, Hui Dong, Zhijiang Du and Wei Dong
Machines 2026, 14(5), 572; https://doi.org/10.3390/machines14050572 (registering DOI) - 21 May 2026
Abstract
Variable stiffness endows continuum robots with both compliance and tunable rigidity, making them promising alternatives to traditional rigid manipulators in confined and unstructured environments. Over the past decade, great progress has been made in variable stiffness technologies involving structural design, actuation, modeling, and
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Variable stiffness endows continuum robots with both compliance and tunable rigidity, making them promising alternatives to traditional rigid manipulators in confined and unstructured environments. Over the past decade, great progress has been made in variable stiffness technologies involving structural design, actuation, modeling, and control. However, current research is fragmented and mostly focuses on individual aspects, lacking a systematic review and a unified framework integrating structure, modeling, and control. This paper presents a comprehensive review of variable stiffness in continuum robots, emphasizing the interrelationships among stiffness principles, modeling, and control strategies. We summarize classical and emerging variable stiffness methods, analyze their integration with control approaches, and evaluate the evolution of control strategies, especially multi-modal fusion of actuation, sensing, and control. Such fusion can improve control accuracy and robustness in human-centered environments and is regarded as a key driver for next-generation intelligent continuum robots. Finally, we outline future directions, highlight the “actuation–stiffness–control” paradigm, and discuss existing challenges and open research opportunities for high-performance intelligent control.
Full article
(This article belongs to the Special Issue Design and Control of Surgical Robots)
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Open AccessArticle
Design of Virtual Disturbance Feedforward Controller for Motion Sickness Mitigation
by
Seongjin Yim
Machines 2026, 14(5), 571; https://doi.org/10.3390/machines14050571 - 20 May 2026
Abstract
This study presents a virtual disturbance feedforward controller (VDFC) to mitigate motion sickness in vehicles equipped with active suspension systems. Because feedforward control is difficult to implement in practice owing to the limited availability of measurable or estimable road-disturbance information, a half-sine virtual
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This study presents a virtual disturbance feedforward controller (VDFC) to mitigate motion sickness in vehicles equipped with active suspension systems. Because feedforward control is difficult to implement in practice owing to the limited availability of measurable or estimable road-disturbance information, a half-sine virtual disturbance (HSVD) corresponding to a bump input is introduced and incorporated into the feedforward controller design. The proposed VDFC is integrated with a feedback controller developed from quarter-car and half-car models using linear quadratic static output feedback (LQ SOF) control. Furthermore, to enhance the motion-sickness-mitigation performance of the VDFC, a simulation-based optimization framework is formulated and solved using a heuristic optimization technique. Simulations with bump inputs are carried out in a vehicle dynamics simulation environment using the LQ SOF controller together with the optimized VDFCs. A sensitivity analysis is also performed for the parameters of the optimized virtual disturbance. The results indicate that, under the bump-like excitation conditions considered, the proposed method can improve ride comfort and reduce motion-sickness-related response measures.
Full article
(This article belongs to the Special Issue Passive and Active Approaches for the Control of Nonlinear Vibrations in Mechanical Systems)
Open AccessArticle
Longitudinal Finite-Time Control of Intelligent Vehicle Fleet Considering Time-Delay and Interference
by
Songbo Wang, Dehua Shi, Shaohua Wang, Yongquan Xie and Yan Chen
Machines 2026, 14(5), 570; https://doi.org/10.3390/machines14050570 - 20 May 2026
Abstract
To address the robustness degradation of intelligent vehicle fleet longitudinal control systems caused by the coexistence of disturbances and time-delay, a longitudinal finite-time control strategy based on a predictive finite-time extended state observer (PFTESO) is proposed. First, a finite-time extended state observer (FTESO)
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To address the robustness degradation of intelligent vehicle fleet longitudinal control systems caused by the coexistence of disturbances and time-delay, a longitudinal finite-time control strategy based on a predictive finite-time extended state observer (PFTESO) is proposed. First, a finite-time extended state observer (FTESO) is designed to estimate system disturbances. To address the observer input asynchrony induced by time-delay, an improved Smith predictor is integrated into the FTESO to construct the PFTESO, thereby improving disturbance observation accuracy under delayed conditions. Meanwhile, a proportional–integral (PI) compensation controller is introduced based on the estimation error to further enhance control accuracy. Subsequently, a global fast integral terminal sliding mode controller (GFITSMC) is developed based on the PFTESO to improve the robustness and finite-time convergence performance of the intelligent vehicle fleet system under disturbances and time-delay. Finally, comparative simulation studies under different operating conditions are conducted to evaluate the effectiveness of the proposed strategy. Simulation results demonstrate that the proposed PFTESO effectively improves state observation accuracy under delayed conditions, where the RMSE values of z1 and z2 are reduced from 0.082 and 0.214 to 0.021 and 0.067, respectively. In addition, compared with conventional sliding mode control strategies, the proposed FTESO-GFITSMC reduces the peak acceleration chattering from ±0.23 m/s2 to 0.03 m/s2 while achieving a finite-time convergence time of 13 s. The proposed method exhibits superior robustness, faster convergence performance, and smoother acceleration response for an intelligent vehicle fleet under disturbances and delayed conditions.
Full article
(This article belongs to the Special Issue New Journeys in Vehicle System Dynamics and Control)
Open AccessArticle
Study on Thermal–Fluid–Solid Coupling Characteristics of a Scroll Compressor in an Oil–Gas Waste Heat Recovery Heat Pump System
by
Yingju Pei, Jingxian Zeng, Lei Zeng, Li Kou, Xu Luo and Yangqi Liu
Machines 2026, 14(5), 569; https://doi.org/10.3390/machines14050569 - 20 May 2026
Abstract
Heat pump technology can efficiently recover waste heat from oil and gas gathering, processing, and transportation. However, the energy transfer mechanism of high-speed rotating internal flow in the scroll compressor remains unclear under unbalanced load conditions, leading to low equipment energy efficiency and
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Heat pump technology can efficiently recover waste heat from oil and gas gathering, processing, and transportation. However, the energy transfer mechanism of high-speed rotating internal flow in the scroll compressor remains unclear under unbalanced load conditions, leading to low equipment energy efficiency and high operation and maintenance costs. This study adopted dynamic grid technology, finite element analysis and one-way thermal–fluid–solid coupling method to quantitatively study the flow field characteristics and mechanical response of four characteristic phases. The results showed that the internal pressure and temperature fields of the compressor presented a non-uniform distribution. The deformation of the scroll wraps was mainly concentrated in the compression chamber, and the maximum stress was concentrated at the wraps’ root. Further analysis revealed that temperature loading played a dominant role in the structural responses. At a spindle rotation angle of 0°, under temperature loading alone, the maximum deformation and maximum stress were 28.605 μm and 521.81 MPa, respectively, while the corresponding values under pressure loading alone were small. In addition, the deformation and stress under coupled loading were not a linear superposition of the individual loading effects, with a deformation deviation of 0.938 μm and a stress deviation of 7.18 MPa at a spindle rotation angle of 0°. In this study, a numerical model of the scroll compressor was established and experimentally verified, which provided a theoretical basis for optimizing scroll profile design, suppressing wrap tip wear and improving the energy efficiency of heat pump systems.
Full article
(This article belongs to the Section Turbomachinery)
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Robust Locomotion Control of Quadrupedal Wheel-Legged Robots via Contrastive History-Aware Reinforcement Learning in Complex Environments
by
Deyun Dai, Tao Liu and Tengfei Tang
Machines 2026, 14(5), 568; https://doi.org/10.3390/machines14050568 - 20 May 2026
Abstract
Quadrupedal wheel-legged robots possess exceptional mobility in complex terrains, but their robust locomotion control is severely hindered by the difficulty of accurate state estimation without external sensors. Existing reinforcement learning methods relying on two-stage imitation often suffer from representation collapse and information loss
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Quadrupedal wheel-legged robots possess exceptional mobility in complex terrains, but their robust locomotion control is severely hindered by the difficulty of accurate state estimation without external sensors. Existing reinforcement learning methods relying on two-stage imitation often suffer from representation collapse and information loss during sim-to-real transfer. To address these challenges, this paper proposes a novel end-to-end reinforcement learning framework for implicit state estimation, incorporating terrain and external force features. Inspired by internal model control, the proposed method leverages a history of purely proprioceptive observations to extract explicit kinematic responses, as well as implicit environmental and external force representations via prototypical contrastive learning, completely circumventing explicit terrain regression and the need for physical force sensors. Furthermore, a tailored composite reward function and a progressive curriculum training strategy with large-scale domain randomization are integrated to ensure dynamic stability and hardware safety. Extensive cross-simulator validations and real-world deployments demonstrate that the approach achieves highly agile and robust locomotion, including adaptive traversal over diverse terrains. Experiments show that the method significantly enhances robustness under external disturbances, notably reducing the lateral linear velocity tracking error from 0.2421 m/s to 0.1319 m/s. The proposed method realizes zero-shot sim-to-real transfer with superior sample efficiency, providing a reliable and universal control paradigm for wheel-legged robots in unstructured environments.
Full article
(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)
Open AccessCorrection
Correction: Song et al. SERail-SLAM: Semantic-Enhanced Railway LiDAR SLAM. Machines 2026, 14, 72
by
Weiwei Song, Shiqi Zheng, Xinye Dai, Xiao Wang, Yusheng Wang, Zihao Wang, Shujie Zhou, Wenlei Liu and Yidong Lou
Machines 2026, 14(5), 567; https://doi.org/10.3390/machines14050567 - 20 May 2026
Abstract
In the original publication [...]
Full article
(This article belongs to the Special Issue Dynamic Analysis and Condition Monitoring of High-Speed Trains)
Open AccessArticle
Optimization of Lightweight Design for a Certain Range Hood Model Under Strength and Vibration Limitations
by
Lihui Zhu, Zhiwei Hu, Xixia Zheng, Xiangrui Zhao, Feng Ye, Chunling Yu and Zhenlei Chen
Machines 2026, 14(5), 566; https://doi.org/10.3390/machines14050566 - 19 May 2026
Abstract
To address structural redundancy and excessive vibration in a specific range hood model, this study focuses on structural lightweighting design optimization. Under strength and resonance avoidance constraints, optimization integrates experimental testing and finite element analysis. Modal analysis reveals a prominent resonance at 49.8
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To address structural redundancy and excessive vibration in a specific range hood model, this study focuses on structural lightweighting design optimization. Under strength and resonance avoidance constraints, optimization integrates experimental testing and finite element analysis. Modal analysis reveals a prominent resonance at 49.8 Hz, which coincides with the test results. Topography optimization of the impeller side plate ribs shifts its natural frequency, eliminating resonance while reducing weight significantly. Subsequently, topography optimization of key parts such as the fan housing improves stiffness, facilitating further lightweighting. Two optimization methods, direct solver and orthogonal experiment were applied to minimize the total mass under strength and dynamic constraints. Both schemes met all design requirements with weight reductions of 17.7% and 18.3%, respectively. Vibration test of the optimized design shows that accelerations at key points were reduced significantly.
Full article
(This article belongs to the Section Machine Design and Theory)
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Open AccessArticle
Quantitative Investigation into Friction-Induced Vibration During Mold-Opening Transience in Ultra-High-Tonnage Two-Platen Injection Molding Machines with Massive Inertia and Constraint-Guided Sliding
by
Xiaozhou Chen, Bin Han, Wei Gu, Meng Chen, Chongyang Xie, Lu Ren and Haibo Huang
Machines 2026, 14(5), 565; https://doi.org/10.3390/machines14050565 - 19 May 2026
Abstract
As extreme-scale manufacturing evolves, the dynamic response of heavy moving components under ultra-high loads becomes a critical design challenge. This study focuses on friction-induced vibration of a more than 30-ton movable mass during the mold-opening stage in a two-platen machine with a clamping
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As extreme-scale manufacturing evolves, the dynamic response of heavy moving components under ultra-high loads becomes a critical design challenge. This study focuses on friction-induced vibration of a more than 30-ton movable mass during the mold-opening stage in a two-platen machine with a clamping force >17,000 kN. A mathematical model and a validated rigid/flexible multibody dynamics model with PID co-simulation were developed to analyze transient vibration using maximum acceleration amplitude and stability time as core metrics. The results show vibration stems from imbalance between anti-opening resistance and hydraulic driving force, amplified by vacuum collapse, static-to-dynamic friction transition at slide feet/rail interface and PID overshoot, featuring high amplitude density (>0.75 g), transience (<50 ms) and high impact (>60,000 N). The maximum vibration acceleration amplitude remains 79.22% even after there is no mold vacuum suction, indicating that a static friction force other than the vacuum suction is the dominant factor resulting in a severe friction-induced vibration. These mechanistic insights establish an applicable framework for the dynamic optimization of the heavy components in extreme-large-scale manufacturing equipment.
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(This article belongs to the Special Issue New Advances in Science of Mechanisms and Machines)
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Open AccessArticle
Using Type-1 and Type-2 Fuzzy Logic Controllers for the Trajectory Tracking Task of a Wheeled Robot: A Comparison Study
by
Mohammed Taqiyeddine Mahdi, Lakhmissi Cherroun, Mohamed Nadour, Puig Vicenç, Ahmed Hafaifa, Giovanni Angiulli and Fabio La Foresta
Machines 2026, 14(5), 564; https://doi.org/10.3390/machines14050564 - 19 May 2026
Abstract
The robotic path-tracking task is of interest to researchers because it offers the potential to develop an efficient navigation system for robots. Fuzzy logic is successfully used in many control systems, especially in robotic tasks, due to its ability to model the uncertainties
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The robotic path-tracking task is of interest to researchers because it offers the potential to develop an efficient navigation system for robots. Fuzzy logic is successfully used in many control systems, especially in robotic tasks, due to its ability to model the uncertainties and vagueness of the physical world. In this paper, the application of type-1 and type-2 fuzzy logic controllers for trajectory tracking of differential drive robots has been investigated. Initially, a comprehensive review of related work is provided, followed by a detailed description of the differential-drive robot, including its kinematic and dynamic models. Both type-1 and type-2 fuzzy controllers are implemented to evaluate their performance in tracking complex, challenging trajectories. Simulation results demonstrate the effectiveness of each fuzzy controller, with a focus on comparative analysis. All comparisons are conducted under strictly identical conditions to ensure a fair and unbiased evaluation of both controllers. A comparison study highlights differences in performance metrics across scenarios, revealing that the type-2 fuzzy logic controller outperforms the type-1 controller in improving trajectory tracking accuracy. Quantitative performance indicators, including root-mean-square errors (RMSEs) for distance and orientation, as well as transient response times, are employed for comparison. Specifically, the type-2 fuzzy controller reduced the average tracking error by more than 75% and the angular error by over 80% across different trajectories, while also decreasing the response time by up to 80% compared to the type-1 fuzzy controller.
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(This article belongs to the Section Automation and Control Systems)
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Open AccessArticle
Hydrogen Enrichment in Methanol Dual-Fuel CI Engines: A Computational Assessment of Engine Performance and Major Combustion Parameters and Emissions
by
Takwa Hamdi, Samuel Molima, Juan J. Hernández, José Rodríguez-Fernández and Mouldi Chrigui
Machines 2026, 14(5), 563; https://doi.org/10.3390/machines14050563 - 18 May 2026
Abstract
Hydrogen enrichment of compression ignition (CI) engines has emerged as a promising strategy to simultaneously enhance thermal efficiency and reduce carbon-based emissions. This study numerically investigates how hydrogen enrichment affects engine performance and emissions in methanol–diesel dual-fuel CI engines, a combustion mode gaining
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Hydrogen enrichment of compression ignition (CI) engines has emerged as a promising strategy to simultaneously enhance thermal efficiency and reduce carbon-based emissions. This study numerically investigates how hydrogen enrichment affects engine performance and emissions in methanol–diesel dual-fuel CI engines, a combustion mode gaining increasing attention for replacing fossil diesel with sustainable fuels, particularly in hard-to-abate sectors such as maritime transport. The simulations are based on the Unsteady Reynolds-Averaged Navier–Stokes (URANS) equations, incorporating the RNG k–ε turbulence model, the Eddy Dissipation Concept (EDC) for turbulence–chemistry interaction, and the G-equation for turbulent premixed flame propagation. The numerical model is validated against experimental data for in-cylinder pressure and heat release rate at 45% methanol substitution ratio (by energy). The results indicate that increasing the hydrogen enrichment ratio (HER, defined on an energy basis) from 5% to 20% raises the Sauter mean diameter (SMD) of the diesel fuel from 20.2 µm to 28.0 µm (+38%), driven by reduced aerodynamic breakup intensity associated with modified gas-phase properties under hydrogen enrichment. Furthermore, hydrogen’s elevated adiabatic flame temperature and superior mass diffusivity intensify combustion, raising peak in-cylinder pressure from 75.2 to 79.1 bar (+5.2%), amplifying the peak heat release rate from 129 to 211 J/°CA (+63.6%), and elevating maximum in-cylinder temperature from 1542 to 1735 K (+193 K). Under the investigated CFD operating conditions, these thermodynamic gains translate into an engine-level 6% improvement in indicated thermal efficiency and a 14% reduction in indicated specific fuel consumption (accounting for hydrogen, methanol, and diesel) at HER 20%. On the emissions front, CO2 declines by 24% in direct proportion to the carbon-containing fuel mass displaced by hydrogen substitution, while NOₓ increases approximately twofold from 0.10 g/kWh at HER 0 to 0.21 g/kWh at HER 20, driven by peak temperature elevation. These findings establish hydrogen-enriched methanol–diesel dual-fuel combustion as a viable pathway toward high-efficiency, low-carbon CI engine operation for heavy-duty transport applications.
Full article
(This article belongs to the Special Issue Advances in Combustion Science for Future IC Engines, 2nd Edition)
Open AccessArticle
A Physics-Informed Stability-Driven Approach to Wavelet Packet Band Selection for Crack Severity Classification Across Operating Conditions
by
Francesco Melluso, Vincenzo Niola, María Jesús Gómez García and Cristina Castejon
Machines 2026, 14(5), 562; https://doi.org/10.3390/machines14050562 - 16 May 2026
Abstract
Accurate crack severity classification in rotating shafts remains a challenging task due to the strong spectral overlap between adjacent damage levels and the absence of distinct fault-specific frequency components. In such conditions, conventional vibration-based approaches relying on global spectral descriptors often fail to
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Accurate crack severity classification in rotating shafts remains a challenging task due to the strong spectral overlap between adjacent damage levels and the absence of distinct fault-specific frequency components. In such conditions, conventional vibration-based approaches relying on global spectral descriptors often fail to provide sufficient discriminatory information. This work proposes a stability-driven multi-resolution framework for crack severity classification based on the Wavelet Packet Transform (WPT). The approach aims to identify frequency bands that exhibit consistent diagnostic relevance across multiple decomposition levels while maintaining a monotonic relationship with crack severity. To this end, an interpretability-driven analysis based on Random Forest feature importance is combined with a frequency stability criterion and a monotonicity constraint, enabling the selection of physically meaningful and consistent spectral regions. The proposed framework has been evaluated on vibration data acquired from a rotating shaft test bench under multiple operating speeds and damage conditions. The results have shown that crack progression is characterised by distributed energy variations across specific frequency regions rather than by the emergence of isolated spectral peaks. It can be concluded that the proposed stability-driven band selection approach enables the identification of these regions in a consistent manner across spectral resolutions and operating conditions. Furthermore, the integration of WPT-based features with conventional time- and frequency-domain descriptors leads to a hybrid multi-scale representation that improves classification performance, particularly in intermediate severity regimes where spectral overlap is most pronounced. Overall, the proposed methodology provides a physically interpretable and consistent framework for vibration-based crack severity classification, with potential applicability to a wide range of rotating machinery diagnostics problems.
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(This article belongs to the Special Issue Advanced Machine Condition Monitoring and Fault Diagnosis)
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Open AccessArticle
Partial Natural Torsional Frequency Modification of Vehicle Driveline Considering Modal Damping
by
Kui-Yang Gao, Guo-Feng Yao, Min Wang, Jun-Lin Chen and Zhi-Wen Xu
Machines 2026, 14(5), 561; https://doi.org/10.3390/machines14050561 - 16 May 2026
Abstract
Torsional resonance is a common phenomenon in engineering vehicle drivelines. To avoid the influence of resonance on the driveline, it is typical to modify the frequency. However, traditional frequency modification methods cannot precisely achieve expected frequencies while keeping others unchanged. They often cause
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Torsional resonance is a common phenomenon in engineering vehicle drivelines. To avoid the influence of resonance on the driveline, it is typical to modify the frequency. However, traditional frequency modification methods cannot precisely achieve expected frequencies while keeping others unchanged. They often cause frequency ‘overflow’ and fail to account for the influence of modal damping on drivelines. To address the issues above, a passive modification method is proposed to modify the natural frequencies of engineering vehicle drivelines, considering modal damping. In this paper, the dynamic equations for gears and shafts are derived by a lumped-parameter model that employs the Lagrange method to establish a reasonably equivalent model as a serial-parallel system consisting of (moment of inertia)-(torsional spring)-(torsional damper) with free boundary conditions. Additionally, the passive structural modification for the partial eigenvalue assignment (PEVAPSM) method is employed to modify the specified partial natural torsional frequencies to realizable expected values, while others remain unchanged. The modal damping of the original driveline is modified based on the orthogonal decomposition method. Finally, the practical applicability of the method proposed in this paper is demonstrated through a specific example. Results indicate that the PEVAPSM method has been successfully extended and supplemented from a theoretical translational system, ignoring modal damping, to a practical torsional system considering modal damping to modify natural frequencies of the structure. The improved PEVAPSM method enables to precisely determine the moment of inertia and modal damping of gears in the driveline, preventing resonance with other structures at the same frequency. It offers valuable guidance for studying the torsional vibration characteristics of engineering vehicle drivelines.
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(This article belongs to the Section Vehicle Engineering)
Open AccessArticle
Safety-Filtered Residual Reinforcement Learning over Model Predictive Control for Friction-Aware Autonomous Vehicle Platooning
by
Ali S. Allahloh, Atef M. Ghaleb, Mohammad Sarfraz, Abdalla Alrashdan, Mohammed A. H. Ali and Adel Al-Shayea
Machines 2026, 14(5), 560; https://doi.org/10.3390/machines14050560 - 16 May 2026
Abstract
This paper presents a deployment-oriented longitudinal platoon-control architecture for connected and autonomous vehicles operating under repeated leader hard-braking, cut-ins, and spatially varying road friction. The proposed stack combines four elements: (i) a lightweight scalar Kalman filter (KF) that smooths a friction-related signal and
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This paper presents a deployment-oriented longitudinal platoon-control architecture for connected and autonomous vehicles operating under repeated leader hard-braking, cut-ins, and spatially varying road friction. The proposed stack combines four elements: (i) a lightweight scalar Kalman filter (KF) that smooths a friction-related signal and feeds friction-dependent constraint tightening; (ii) a model predictive control (MPC) backbone whose weights and horizon are selected offline using multi-objective GA/NSGA-II tuning; (iii) a bounded proximal policy optimization (PPO) residual policy, trained with the aid of a learned surrogate model, that refines the MPC command during transient events; and (iv) a command-level safety projection that enforces instantaneous actuation and clearance constraints at the fast control tick. The contribution is therefore not a new MPC formulation or a new reinforcement-learning algorithm in isolation, but an integrated and experimentally characterized control stack that keeps the safety-critical structure explicit while using learning to improve transient behavior. The method is evaluated in a CARLA digital twin of a six-vehicle platoon over a 5 km mixed urban–highway route and is further assessed in hardware-in-the-loop (HIL) on an automotive ECU using a multi-rate ROS 2/AUTOSAR implementation (50 Hz estimation/safety loop, 10 Hz MPC/RL refresh). Across 10 held-out disturbance seeds, the full stack improves spacing regulation, maintains non-amplifying disturbance propagation according to the reported string-stability indices, and reduces a route-normalized positive tractive-energy-at-the-wheels proxy by about 12% relative to Manual MPC and by up to 18% relative to a PID-CACC reference. Because the PID-CACC baseline does not enforce hard constraints and can collide under the tested disturbance suite, the main performance comparison is among collision-free controllers. The friction signal used in CARLA is derived from simulator road-surface annotations before filtering, so the present study should be interpreted as a friction-aware control and integration study rather than a validated onboard friction-estimation result. Likewise, the reported energy metric is an effort proxy and is not a calibrated fuel or battery consumption model.
Full article
(This article belongs to the Special Issue Reinforcement Learning for Autonomous Vehicle Control)
Open AccessArticle
Sustainable Multi-Energy Microgrid Operation: Birds of Prey-Based Day-Ahead Scheduling Under Seasonal Renewable Uncertainty
by
Hany S. E. Mansour, Hassan M. Hussein Farh, Abdullrahman A. Al-Shamma’a, AL-Wesabi Ibrahim, Abdullah M. Al-Shaalan, Amira S. Mohamed and Honey A. Zedan
Machines 2026, 14(5), 559; https://doi.org/10.3390/machines14050559 - 16 May 2026
Abstract
The increasing integration of renewable energy resources into modern microgrids requires reliable scheduling methods capable of managing uncertainty, seasonal variability, operating cost, and environmental impact. This study proposes a stochastic day-ahead scheduling approach for a representative grid-connected multi-energy microgrid comprising photovoltaic generation, wind
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The increasing integration of renewable energy resources into modern microgrids requires reliable scheduling methods capable of managing uncertainty, seasonal variability, operating cost, and environmental impact. This study proposes a stochastic day-ahead scheduling approach for a representative grid-connected multi-energy microgrid comprising photovoltaic generation, wind generation, a microturbine, a fuel cell, an energy storage system, and utility-grid exchange. The proposed model was implemented and simulated in a MATLAB (2024b) environment. The Birds of Prey-Based Optimization algorithm is applied to determine the optimal 24 h dispatch schedule by minimizing a weighted objective function that combines operating and emission costs. Uncertainties in solar irradiance, wind speed, electrical load, ambient temperature, and electricity prices are modeled using probabilistic distributions and Monte Carlo simulations. To improve computational efficiency, 1000 generated scenarios are reduced to 10 representative scenarios using Fast Forward Selection based on Kantorovich distance. Seasonal case studies for winter, spring, summer, and autumn are used to evaluate the proposed method. Compared with five metaheuristic algorithms, the proposed approach achieves the lowest fitness value in all seasons, with reductions of 15.2%, 26.5%, 6.8%, and 23.9%, respectively. The results confirm improved economic and environmental microgrid operation under seasonal renewable uncertainty.
Full article
(This article belongs to the Special Issue Sustainable Intelligent Design, Control and Optimization for Renewable-Integrated Power Systems)
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