Abstract With the global energy transition and carbon neutrality goals, wind power has become a crucial source of green energy, making the condition monitoring of wind turbines increasingly essential. To ensure stable and reliable operation, deploying self-powered sensors in the transmission system provides an effective approach for real-time monitoring of critical components. Therefore, this paper proposes a novel speed increasing electromagnetic rotational energy harvester (SIEREH) for the transmission system of wind turbines, which achieves efficient energy conversion by integrating a planetary gear speed-increasing mechanism with the principle of electromagnetic induction. The speed-increasing section component employs a planetary gear system to achieve counter-rotation between the inner and outer cylinders, thereby increasing the output performance. The results demonstrate that as the rotational speed rises from 60 to 480 rpm, the open-circuit AC voltage generated by a single coil in the SIEREH increases from 0.88V to 6 V. Under the optimal load resistance of 9 Ω, the maximum root-mean-square (RMS) power output shows a significant enhancement, rising from 3.7 mW to 527.6 mW, with a corresponding maximum volume power density of 0.6138 mW/cm³. This research provides a novel approach to efficient energy harvesting, effectively addressing issues such as low efficiency and poor output stability in traditional rotational energy harvesters, and holds significant potential for practical engineering applications.

Abstract The active suspension system faces an inherent conflict between body acceleration and suspension deflection: reducing body acceleration to improve comfort often results in increased suspension deflection, while suppressing suspension deflection to enhance stability may exacerbate body vibrations. To address this issue, a nonlinear dual-objective cooperative control strategy (NCDOC) is proposed in this paper, which enhances the overall performance of the active suspension system by coordinating conflicting control terms. For body dynamics, a specialized quasi-sliding mode control method is employed, utilizing body acceleration information to reduce body acceleration and regulate body displacement. Meanwhile, for the faster-changing suspension deflection dynamics, a saturated PD sliding mode tracking control term is introduced to regulate suspension deflection and counteract disturbances in the suspension deflection. Based on Lyapunov stability theory, the finite-time convergence of the closed-loop system is proven. A comparative analysis with the nonlinear disturbance observer (NDO) method reveals that the proposed control scheme achieves excellent control performance while reducing the control input by more than 50%. The effectiveness of the designed control scheme is verified through simulations and experiments. Multiple results demonstrate that the designed controller can achieve improved active suspension performance with smaller control inputs, including reducing body acceleration by more than 40% and more effectively regulating suspension deflection.

Abstract Composite leaf springs with variable stiffness function (‘shape memory alloy (SMA) hybrid composite leaf springs’) were constructed by embedding three-dimensional SMA actuators into a multi-material composite system. Bench test of dynamic stiffness and fatigue characteristics revealed that epoxy resin matrix leaf springs exhibit the highest initial strength/stiffness but suffer rapid long-term decay due to brittle fracture and Joule thermal softening. Although SMA phase transformation enables temporary crack closure, the interplay between thermal damage and cyclic repair restricts durability. Thermoplastic polyimide (TPI) matrices exhibited outstanding fatigue resistance under actuation, attributed to superior thermal stability and molecular chain reconstruction, while SMA activation effectively inhibited crack propagation. Polydimethylsiloxane (PDMS) matrix leaf springs are suitable for long-term active control scenarios due to hyperelastic interfacial slip and modulus mismatch. However, while the short-term increase in stiffness and strength after energization is high, interfacial delamination triggers catastrophic failure after 5000 cycles, making PDMS matrix leaf springs suitable for short-term deformation requirements only. The TPI-SMA synergistic architecture provides a theoretical foundation for resolving the intrinsic trade-off between active stiffness tunability and fatigue resistance, thereby demonstrating the substantial potential of intelligent structural composites for advanced automotive applications.

Abstract The rapid advancement of artificial intelligence has spurred widespread interest in artificial muscles as core actuating components for soft robotics. Twisted and coiled artificial muscles (TCAMs), a novel class of soft actuators fabricated by twisting and coiling high-performance fibers, exhibit notable advantages, including low cost, high flexibility, long cycle life, large actuation strain, and high energy density. The TCAMs can generate multiple motion modes, including bending, twisting, contraction/extension, and buckling in response to external stimuli. The TCAMs demonstrate significant potential for application in fields such as soft robotics and wearable assistive devices. This review comprehensively examines the developmental trajectory and current research landscape of TCAMs, synthesizes progress in actuation strategies, actuation mechanisms, and machine learning applications, and concludes with perspectives on future research directions. We further assess persistent challenges in hysteresis suppression and manufacturing reproducibility, proposing cross-disciplinary solutions toward deployable artificial muscle systems.

Abstract At present, bidirectional piezoelectric actuators (PAs) typically utilise multiple PZT stacks, which make the structure and driving principle complicated. In this work, a non-resonant PA with bidirectional motion using a single PZT stack is proposed. It incorporates a secondary displacement magnification mechanism, which improves the two driving feet’s output displacement. A lever reversing mechanism is designed to change the lever’s output direction, which in turn switches the driving direction of the driving feet, thus enabling the bidirectional drive. The PA’s working principle is described: an oblique linear trajectory is composed at the end of the driving foot, achieved bipedal alternating driving the guide rail. The PA model is analysed using finite element simulation to confirm the structure’s magnification ratio and the driving foot’s motion trajectory. Subsequently, an experimental assessment is performed on the PA prototype, confirming its capability to achieve bidirectional motion. Experimental findings demonstrate that the velocities of driving the guide rail leftward and rightward are 3.894 mm s −1 and 4.07 mm s −1 , respectively, under the conditions of 140 V and 40 Hz. This paper introduces a new idea on the compact structure design of a bidirectional-driven PA.

Abstract A novel coarse-grained molecular dynamics (MD) simulation model is developed to investigate the influence of microstructure evolution on the dynamic properties of magnetorheological elastomers (MREs) during curing and shearing processes. The model explicitly accounts for particle–matrix interactions by introducing viscous damping and elastic restoring forces, enabling accurate representation of the mechanical constraints imposed by the elastomeric matrix. A series of numerical simulations are conducted to examine the effects of magnetic field intensity, particle concentration, and excitation frequency on the shear modulus of MREs. The results reveal that stronger magnetic fields and higher particle concentrations promote the formation of anisotropic, chain-like structures, thereby enhancing the shear modulus. While magnetic fields during curing initiate initial particle alignment, those applied during shearing more effectively increase stiffness by continuously reinforcing particle interactions beyond the alignment plateau. The simulation outcomes show good qualitative agreement with existing experimental findings, validating the model’s capability to capture both microstructural characteristics and macroscopic mechanical responses. This work offers valuable insights into the structure–property relationships of MREs and highlights the potential of advanced simulation techniques in guiding the design and optimization of magneto-responsive smart materials.

Abstract This work explores a novel hybrid composite design that incorporates thin SMA sheet inserts within glass fiber-reinforced polymer (GFRP) laminates. By using flat NiTi and Cu-Al-Mn alloy plates-instead of traditional SMA wires-the study evaluates whether increased material volume improves vibration damping. Brass inserts were also tested as a nontransforming control. The composites were subjected to free vibration, tensile, and flexural testing. NiTi inserts yielded the best damping and most consistent mechanical behavior. Cu-Al-Mn inserts showed potential as a lower-cost alternative but exhibited greater variability.Laser-cut patterns in NiTi inserts reduced damping slightly but enhanced flexural strength and interfacial adhesion. The findings underline how SMA type and insert design influence the balance between damping efficiency and structural performance.

Abstract In this study, we developed a novel method to fabricate a shape memory composite film composed of a continuous PEDOT:PSS matrix and isolated epoxy islands, using an air plasma-treated polypropylene (PP) substrate. Vertical phase separation was achieved by tuning the substrate’s surface energy to lie between those of the two immiscible polymers. Air plasma treatment increased the PP substrate’s surface energy, driving PEDOT:PSS to accumulate at the film–substrate interface, forming a continuous bottom layer with dispersed epoxy islands. During thermal curing, epoxy islands enlarged due to water evaporation from the PEDOT:PSS solution and subsequent epoxy crosslinking, enhancing their integrity. The PEDOT:PSS-rich bottom layer established a conductive path, while its incorporation improved the storage modulus and reduced the glass transition temperature ( T g ) through plasticization, without compromising the shape memory behavior. The resulting composite film demonstrated excellent fixity (98.6%) and recovery (93.1%) ratios while maintaining electrical resistance during shape transitions.

Abstract Additively manufactured piezoresistive sensors offer a promising route for creating smart structures with integrated Structural Health Monitoring capabilities. However, their performance is highly dependent on geometric design, which presents a complex multi-objective optimization problem. To address this, this work presents a combined experimental and computational framework for optimizing 3D-printed, conductive PLA piezoresistive strain sensors. A design of experiments was conducted to investigate four geometric parameters (trace width, inter-trace distance, thickness, and end-loops) across three integration types. The resulting response surfaces-linking geometry to gauge factor ( GF ), maximum strain ( ɛ max ), and elastic modulus ( E )-were modeled using Gaussian process regression. A multi-objective particle swarm optimization algorithm, coupled with TOPSIS, was then employed to navigate the conflicting objectives of maximizing sensitivity while minimizing structural stiffness impact. Key optimized solutions were fabricated and experimentally validated via uniaxial tensile tests monitored with digital image correlation. The fully embedded configuration yielded the highest sensitivity ( GF = 59) but compromised host stiffness. However, an optimized, scaled variant of this design restored stiffness to near-native levels ( E = 2.18 GPa) while retaining high sensitivity. The validated ‘Experiment-Model-Optimize-Validate’ workflow provides a generalizable methodology for designing and tailoring additively-manufactured sensors for specific applications.

Abstract Wind is a form of renewable energy that carries a considerable amount of energy, and the development of efficient methods for harnessing and converting it presents considerable promise for sustainable power generation. This paper presents a novel rotational piezoelectric energy harvester (RPEH) designed to efficiently harness wind energy for powering low-power wireless sensors. Based on Hertzian contact theory and Euler–Bernoulli beam Theory, the study models the response of the piezoelectric beam during both the excitation phase and the damping oscillation phase. A custom-designed experimental testing system was employed to investigate and analyze the structural variables of the energy harvester. Experimental results demonstrate that under conditions of a gear diameter of 70 mm, a rotational speed of 500 rpm, and a 10 kΩ load resistor, a single piezoelectric element achieved a maximum power output of 9.27 mW, which is sufficient to power small wireless sensor devices. Furthermore, the practicality of the piezoelectric energy harvester in energy harvesting applications was validated through LED illumination and charge capacity experiments. In conclusion, the proposed RPEH offers an innovative solution for wind energy capture and wireless sensor power supply, providing a significant reference for the development of self-powered distributed sensor networks.