Energy Power, Mechanical Engineering and Their Applications

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Mechanics applmech	1.8	3.5	2020	24.5 Days	CHF 1400	Submit
Applied Sciences applsci	2.9	6.1	2011	16 Days	CHF 2400	Submit
Energies energies	3.9	8.3	2008	16.8 Days	CHF 2600	Submit
Symmetry symmetry	2.2	5.2	2009	15.8 Days	CHF 2400	Submit

24 pages, 2318 KB

Open AccessArticle

Wind-Resistant Adaptive Robust Control of Vector–Rotor Unmanned Aerial Vehicles for Omnidirectional Orchard Crop Inspection

by Ziheng Zhou, Liujie Li, Xinfeng Zhang, Jie Bai, Bing Rao, Jiawen Dai, Bangji Zhang and Zheshuo Zhang

Appl. Mech. 2026, 7(2), 46; https://doi.org/10.3390/applmech7020046 - 30 May 2026

Viewed by 267

Abstract

This paper investigates the flight-control problem of a vector–rotor UAV (VR-UAV) for orchard crop-inspection tasks, where wind acts as the dominant external disturbance source. In such tasks, the UAV is required to maintain position while adjusting its attitude for flexible sensor pointing. For [...] Read more.

This paper investigates the flight-control problem of a vector–rotor UAV (VR-UAV) for orchard crop-inspection tasks, where wind acts as the dominant external disturbance source. In such tasks, the UAV is required to maintain position while adjusting its attitude for flexible sensor pointing. For a conventional quadrotor UAV (QUAV), however, position and attitude are strongly coupled because the thrust directions are fixed relative to the fuselage, which limits its ability to perform stable hovering and directional sensing simultaneously. Although gimbal-based solutions can provide sensing-direction adjustment, they may become less suitable for wind-affected low-altitude inspection tasks involving large, elongated, or multi-sensor payloads, due to the added mass, inertia, structural compliance, and vibration sensitivity introduced by the additional mechanism. To address these limitations, this paper proposes a compact VR-UAV platform together with an adaptive robust constraint-following control (ARCFC) method. By incorporating tilting motors for thrust-vector adjustment, the proposed VR-UAV enables decoupled regulation of position and attitude, thereby improving fixed-point hovering capability and flexible sensor pointing. From the control perspective, the thrust-vectoring mechanism introduces strongly nonlinear coupled dynamics, while wind-induced disturbances and modeling uncertainties further complicate the control problem. To address these challenges, a constraint-following control framework is developed to handle the nonlinear dynamics, and an adaptive robust compensation mechanism is introduced to estimate the uncertainty bound online and compensate for unknown but bounded disturbances. The closed-loop stability and robustness of the proposed method are rigorously established by theoretical analysis. Comparative simulation results demonstrate that, relative to a conventional QUAV, the proposed VR-UAV with ARCFC achieves superior flight stability, stronger wind-disturbance rejection, and better trajectory-tracking performance in wind-affected orchard inspection scenarios. Full article

(This article belongs to the Topic Energy Power, Mechanical Engineering and Their Applications)

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36 pages, 5839 KB

Open AccessArticle

An Adaptive Multi-Scale Heterogeneous Ensemble Framework for Interpretable Wind Power Forecasting in Sustainable Grids

by Jiaoyang Gao, Hui Zhang, Zhongmiao Sun, Hui Xu, Jiahe Li and Jiani Heng

Symmetry 2026, 18(6), 921; https://doi.org/10.3390/sym18060921 - 27 May 2026

Viewed by 267

Abstract

Reliable short-term wind power forecasting is crucial for smart grid stability. However, high-dimensional noise and stochastic fluctuations in wind sequences often degrade the accuracy of traditional forecasting models. Moreover, wind power time series typically exhibit asymmetric rising and decaying patterns, which further complicate [...] Read more.

Reliable short-term wind power forecasting is crucial for smart grid stability. However, high-dimensional noise and stochastic fluctuations in wind sequences often degrade the accuracy of traditional forecasting models. Moreover, wind power time series typically exhibit asymmetric rising and decaying patterns, which further complicate accurate modeling. To address these challenges, this study proposes a hybrid intelligent system that integrates three components: data preprocessing, heterogeneous ensemble learning, and probabilistic interval forecasting. First, we build a multi-stage preprocessing workflow. Adaptive DBSCAN and Local Outlier Factor (LOF) remove spatial and density anomalies. Then multivariate variational mode decomposition (MVMD) synchronously separates multi-scale oscillatory patterns while preserving cross-channel correlations and frequency-domain symmetry across input variables. SHAP analysis quantifies feature importance, ensuring interpretability. The selected features are fed into a heterogeneous ensemble model consisting of Transformer, BPNN, ELM, XGBoost, and QRLSTM, which collectively capture multi-scale temporal dependencies and diverse data patterns. The ensemble weights are dynamically optimized by a modified multi-objective dragonfly algorithm (MMODA) that balances forecast accuracy and stability. Based on this ensemble, we apply MMODA to tune kernel density estimation for generating high-quality forecast intervals, maximizing coverage while minimizing interval width. Experiments on two wind farms in Shandong show that our MMODA-optimized ensemble reduces mean absolute percentage error by about 44.7% compared to single models, and ablations confirm that MVMD preprocessing adds a further 10.7% reduction. The proposed system provides an interpretable and reliable decision-support tool for sustainable grid operations. Full article

(This article belongs to the Topic Energy Power, Mechanical Engineering and Their Applications)

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18 pages, 6201 KB

Open AccessArticle

Lateral Stability and Synchronization Control for Dual-Motor Steer-by-Wire Vehicles

by Pengze Ma, Zonghao Li, Jinghui Zhao, Niaona Zhang and Zhe Zhang

Symmetry 2026, 18(5), 828; https://doi.org/10.3390/sym18050828 - 12 May 2026

Viewed by 350

Abstract

The steer-by-wire (SBW) system represents an optimal solution for achieving intelligent vehicle steering. However, the current reliability of SBW motors and electronic control units remains limited. Disturbances, including variations in the external road environment and time-varying parameters, can significantly impact vehicle stability. To [...] Read more.

The steer-by-wire (SBW) system represents an optimal solution for achieving intelligent vehicle steering. However, the current reliability of SBW motors and electronic control units remains limited. Disturbances, including variations in the external road environment and time-varying parameters, can significantly impact vehicle stability. To address these challenges, a hierarchical control strategy is proposed in this paper. In the upper layer, model predictive control (MPC) is employed to optimize the sideslip angle and yaw rate by tracking their reference values, thereby enhancing the stability of the SBW system. In the lower layer, a composite reaching law sliding mode control based on an extended state observer (ESO-CRLSMC) is developed to address dual-motor parameter mismatch and speed synchronization issues, thereby ensuring the reliability of the dual-motor system. Finally, hardware-in-the-loop experiments demonstrate that under time-varying disturbances and parameter mismatches, the proposed controller not only ensures vehicle handling stability but also improves steering response speed, robustness, and synchronization performance. Full article

(This article belongs to the Topic Energy Power, Mechanical Engineering and Their Applications)

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27 pages, 5291 KB

Open AccessArticle

Automatic Calibration Strategy Based on Artificial Neural Networks for Shift Control of Automatic Transmission

by Songlin Li, Yanle Zhao and Wei Guo

Appl. Sci. 2026, 16(9), 4432; https://doi.org/10.3390/app16094432 - 1 May 2026

Viewed by 259

Abstract

As the number of gears in automatic transmissions (AT) increases, the calibration parameters in the gear shift control process of the transmission control unit (TCU) increase exponentially, significantly increasing the calibration workload during engineering development. To address the challenges of high cost and [...] Read more.

As the number of gears in automatic transmissions (AT) increases, the calibration parameters in the gear shift control process of the transmission control unit (TCU) increase exponentially, significantly increasing the calibration workload during engineering development. To address the challenges of high cost and long cycle times associated with traditional manual calibration, this paper proposes an automatic calibration strategy for shift control based on artificial neural networks (ANNs). The core of this method lies in utilizing an ANN to establish a non-linear mapping relationship between shift characteristics and calibration parameters, thereby simulating and replacing the analysis and adjustment process of engineers. In this research, a vehicle simulation model based on a 9-speed automatic transmission (9AT) was first constructed. A large-scale dataset of shift characteristics was obtained by traversing various parameter combinations, and key features were extracted for model training. Simulation results demonstrate that the trained ANN model performs excellently in the automatic calibration process, requiring only 4 to 5 iterations to adjust shift quality to a level comparable to manual calibration. Its convergence speed and efficiency are significantly superior to traditional rule-based calibration methods. Furthermore, the model exhibits a certain degree of generalization ability and robustness across different throttle openings and gear-shifting conditions. The proposed automatic calibration method does not rely on high-precision physical models, effectively shortening the development cycle and improving calibration efficiency, which holds significant application value in the field of automatic transmission engineering development. Full article

(This article belongs to the Topic Energy Power, Mechanical Engineering and Their Applications)

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16 pages, 2833 KB

Open AccessArticle

Research on a Space–Time Modulation-Based Angle Demodulation Method for Magnetic Encoders

by Song Jin and Shuaihang Li

Appl. Sci. 2026, 16(7), 3128; https://doi.org/10.3390/app16073128 - 24 Mar 2026

Viewed by 436

Abstract

This paper presents a high-precision angle demodulation method for magnetic encoders by integrating orthogonal-signal correction with space–time modulation (STM). The proposed approach specifically addresses a critical vulnerability of STM-based high-frequency pulse interpolation: its interpolation accuracy is highly sensitive to zero-crossing timing jitter of [...] Read more.

This paper presents a high-precision angle demodulation method for magnetic encoders by integrating orthogonal-signal correction with space–time modulation (STM). The proposed approach specifically addresses a critical vulnerability of STM-based high-frequency pulse interpolation: its interpolation accuracy is highly sensitive to zero-crossing timing jitter of the quadrature signals. In practical magnetic encoders, non-idealities such as DC offsets, amplitude mismatch, and phase non-orthogonality in the sine/cosine outputs induce jitter and shift in the zero-crossing points. This directly leads to fluctuations in high-frequency counts and amplifies the final angle error. To mitigate this issue, an online orthogonal-signal correction module is first developed. This module sequentially performs offset estimation, amplitude normalization, and real-time phase orthogonalization, thereby enhancing the orthogonality and zero-crossing stability of the quadrature signals at the source. This preprocessing significantly reduces the sensitivity of the subsequent interpolation counting to noise and signal imperfections. Based on the corrected signals, an STM pulse-counting interpolator is adopted to convert angle information into a time-domain phase (time) difference, and high-frequency counting is used for fine subdivision. A Kalman-filter-based predictor is employed to estimate angular velocity and compensate the intrinsic latency of counting-based demodulation in dynamic conditions. Experimental results demonstrate that the proposed phase orthogonalization correction markedly suppresses zero-crossing timing jitter and enhances the stability of high-frequency pulse interpolation. Consequently, the overall demodulation error is reduced by more than 30 percent compared with existing methods, and the final angle error is maintained within 0.033°. Full article

(This article belongs to the Topic Energy Power, Mechanical Engineering and Their Applications)

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38 pages, 12849 KB

Open AccessArticle

Research on an Ultra-Short-Term Wind Power Forecasting Model Based on Multi-Scale Decomposition and Fusion Framework

by Daixuan Zhou, Yan Jia, Guangchen Liu, Junlin Li, Kaile Xi, Zhichao Wang and Xu Wang

Symmetry 2026, 18(2), 253; https://doi.org/10.3390/sym18020253 - 30 Jan 2026

Cited by 1 | Viewed by 505

Abstract

Accurate wind power prediction is of great significance for the dispatch, security, and stable operation of energy systems. It helps enhance the symmetry and coordination between the highly stochastic and volatile nature of the power generation supply side and the stringent requirements for [...] Read more.

Accurate wind power prediction is of great significance for the dispatch, security, and stable operation of energy systems. It helps enhance the symmetry and coordination between the highly stochastic and volatile nature of the power generation supply side and the stringent requirements for stability and power quality on the grid demand side. To further enhance the accuracy of ultra-short-term wind power forecasting, this paper proposes a novel prediction framework based on multi-layer data decomposition, reconstruction, and a combined prediction model. A multi-stage decomposition and reconstruction technique is first employed to significantly reduce noise interference: the Sparrow Search Algorithm (SSA) is utilized to optimize the parameters for an initial Variational Mode Decomposition (VMD), followed by a secondary decomposition of the high-frequency components using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN). The resulting components are then reconstructed based on Sample Entropy (SE), effectively improving the quality of the input data. Subsequently, a hybrid prediction model named IMGWO-BiTCN-BiGRU is constructed to extract spatiotemporal bidirectional features from the input sequences. Finally, simulation experiments are conducted using actual measurement data from the Sotavento wind farm in Spain. The results demonstrate that the proposed hybrid model outperforms benchmark models across all evaluation metrics, validating its effectiveness in improving forecasting accuracy and stability. Full article

(This article belongs to the Topic Energy Power, Mechanical Engineering and Their Applications)

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23 pages, 5456 KB

Open AccessArticle

Numerical Simulation of Fluid–Structure Interaction in Wind Turbines: A Reduced-Order Approach via Periodic Modeling and Substructuring

by Harouna Illou Abdoulaye and Rabii El Maani

Appl. Mech. 2026, 7(1), 1; https://doi.org/10.3390/applmech7010001 - 23 Dec 2025

Viewed by 972

Abstract

This paper presents a numerical study of fluid–structure interaction (FSI) applied to wind turbines, combining computational fluid dynamics (CFD) and finite element analysis (FEA). The study focuses on a 3D wind turbine blade inspired by the GE 1.5XLE model. The blade features a [...] Read more.

This paper presents a numerical study of fluid–structure interaction (FSI) applied to wind turbines, combining computational fluid dynamics (CFD) and finite element analysis (FEA). The study focuses on a 3D wind turbine blade inspired by the GE 1.5XLE model. The blade features a twisted geometry with S818, S825, and S826 aerodynamic profiles, and is made of an orthotropic composite material with variable thickness and an internal spar. The fluid domain is defined by two circular sections upstream and downstream, aligned along the Z-axis. Simulations are performed under a wind speed of 12 m/s and a rotational speed of −2.22 rad/s (Tip Speed Ratio (TSR) = 8), with air modeled as an incompressible fluid at ambient temperature. On the CFD side, a periodic and symmetric modeling approach is applied, reducing the fluid domain to one-third of the full configuration by simulating flow around a single blade and extrapolating results to the remaining ones. This method achieves a 47% reduction in computation time while maintaining high accuracy in aerodynamic results. On the FEA side, spar condensation is performed by creating a superelement using the substructuring method. This strategy reduces structural computation time by 45% while preserving reliable predictions of displacements, stresses, and natural frequencies. These results confirm the effectiveness of the proposed techniques for accurate and computationally efficient aeroelastic simulations. Full article

(This article belongs to the Topic Energy Power, Mechanical Engineering and Their Applications)

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21 pages, 9596 KB

Open AccessArticle

Thermal Behavior and Operation Characteristic of the Planetary Gear for Cutting Reducers

by Jiahe Shen, Wenyu Zhang, Chengjian Wang, Jianming Yuan, Fangping Ye, Lubing Shi and Daibing Wang

Appl. Sci. 2025, 15(24), 13219; https://doi.org/10.3390/app152413219 - 17 Dec 2025

Viewed by 716

Abstract

Bolter miners have been widely used in coal mining or excavation industries. Its efficiency is closely related to the performance of its cutting reducer, which is literally determined by the thermal behavior of the planetary gear set. Thus, this study conducts experimental investigation [...] Read more.

Bolter miners have been widely used in coal mining or excavation industries. Its efficiency is closely related to the performance of its cutting reducer, which is literally determined by the thermal behavior of the planetary gear set. Thus, this study conducts experimental investigation on the thermal behavior of a cutting reducer (produced by Zhengzhou Machinery Research Institute Transmission Technology Co., Ltd., rated input power 170 kW, transmission ratio 3.06), where the results show the high temperature rise around the intermediate shaft for unloaded condition and significant influence of the torque for loaded conditions. Then, the Finite Element Method (FEM) is used to analyze the temperature field and thermal–structural coupling of the planetary gear set. The thermal stress and deformation increase by 11.5% and 38.4%, respectively, indicating high risk of gear damage. Moreover, the load spectrum imitating the actual industrial condition is added to the KISSsoft to evaluate the reliability and contact of the planetary gear set. The findings including low safety factors of the sun gear tooth surface and planetary gear root, slipping during the sun gear and planetary gear meshing, and uneven contact fluctuations can benefit planetary gear set optimization. Full article

(This article belongs to the Topic Energy Power, Mechanical Engineering and Their Applications)

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19 pages, 2686 KB

Open AccessArticle

The Method of Cleaning Cutting Fluid Using Ultrasonic Treatment

by Anna Kim, Adil Kadyrov, Kirill Sinelnikov, Karibek Sherov and Vassiliy Yurchenko

Appl. Mech. 2025, 6(4), 83; https://doi.org/10.3390/applmech6040083 - 18 Nov 2025

Viewed by 1514

Abstract

Cutting fluids are widely used in mechanical engineering to reduce friction and heat generation during metal machining. However, during operation, these fluids become contaminated with metal particles, dust, and microorganisms, leading to degradation of their functional properties and environmental concerns. This study investigates [...] Read more.

Cutting fluids are widely used in mechanical engineering to reduce friction and heat generation during metal machining. However, during operation, these fluids become contaminated with metal particles, dust, and microorganisms, leading to degradation of their functional properties and environmental concerns. This study investigates the ultrasonic cleaning and regeneration of contaminated cutting fluids. A rheological model of the elastic–viscous medium was analyzed, and a physical model describing the ultrasonic cleaning mechanism was proposed. Experimental investigations were conducted to validate the theoretical assumptions. The results confirmed that ultrasonic treatment promotes dispersion and phase separation of the fluid, removes putrefactive odor, and partially destroys microorganisms. The regenerated fluid exhibited enhanced clarity and stability compared with the contaminated samples. The findings contribute to a deeper understanding of the physicochemical processes occurring during ultrasonic treatment and demonstrate the potential of this method for sustainable reuse of cutting fluids in industrial applications. Full article

(This article belongs to the Topic Energy Power, Mechanical Engineering and Their Applications)

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23 pages, 14097 KB

Open AccessArticle

Comparative Analysis of Local Flow Fields of Typical Inner Jet Holes-Type Reverse Circulation Drill Bit for Pneumatic Hollow-Through DTH Hammer Based on CFD Simulation

by Jiwei Wen, Jiang Chen and Fengtao Zhang

Symmetry 2025, 17(10), 1625; https://doi.org/10.3390/sym17101625 - 1 Oct 2025

Viewed by 938

Abstract

The reverse circulation drill bit is the key component for the efficient and smooth implementation of the pneumatic hollow-through down-the-hole (DTH) hammer reverse circulation continuous coring (sampling) technology. To obtain the structural form of a reverse circulation drill bit with better reverse circulation [...] Read more.

The reverse circulation drill bit is the key component for the efficient and smooth implementation of the pneumatic hollow-through down-the-hole (DTH) hammer reverse circulation continuous coring (sampling) technology. To obtain the structural form of a reverse circulation drill bit with better reverse circulation performance, revealing its local flow fields by computational fluid dynamics (CFD) simulation is an effective approach. Taking the inner jet holes-type reverse circulation drill bit as the research object, three kinds of symmetrical and asymmetrical structures of inner jet holes were proposed. The CFD simulation results show that increasing the air volume supply and the number of inner jet holes leads to an increase in the velocity of air flow jet within the inner jet holes, an increase in the negative pressure formed in the central through channel below the inner jet holes, an enhancement of the reverse circulation performance and suction capacity formed by the reverse circulation drill bit, and an acceleration of the upward flow velocity of the rock cores (samples) located at the bottom of the borehole. Additionally, the reverse circulation performance formed by the reverse circulation drill bit with staggered arranged inner jet holes is superior to that of the reverse circulation drill bit with uniformly distributed inner jet holes. Under the same simulation conditions, the static pressure (i.e., negative pressure) and the upward flow velocity formed by the JB6 model are 2.34 kPa and 30.778 m/s higher than those formed by the JB3-3 model, while these two values formed by the JC6 model are 0.197 kPa and 3.689 m/s higher than those formed by the JB6 model, respectively. In conclusion, an asymmetric structural design would be more reasonable for the design of the inner jet holes-type reverse circulation drill bit. Full article

(This article belongs to the Topic Energy Power, Mechanical Engineering and Their Applications)

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