Search Results (125)

Polyurethane foam is widely used as a primary filling material in car seats. While it provides good damping and energy absorption, the mechanical properties are complex but play a vital role in vibration attenuation and vehicle ride comfort. This study proposes a comprehensive experimental and analytical method to characterize the visco-hyperelastic properties of seat-grade polyurethane foam. Quasi-static and dynamic compression tests were conducted on foam blocks to obtain load–deflection curves and dynamic stiffness. A visco-hyperelastic material model was developed, where the hyperelastic response was derived via the hereditary integral and difference-stress method, and viscoelastic behavior was captured using a Prony series fitted to dynamic stiffness data. The model was validated using finite element simulations, showing good agreement with experimental results in both static and dynamic conditions. The proposed method enables accurate characterization of the visco-hyperelastic material properties of seat-grade polyurethane foam. Full article

Automotive NVH (Noise, Vibration, and Harshness) performance significantly impacts driving comfort and traffic safety. Vehicles exhibiting superior NVH characteristics are more likely to achieve consumer acceptance and enhance their competitiveness in the marketplace. In the development of automotive NVH performance, traditional vibration reduction methods have proven to be mature and widely implemented. However, due to constraints related to size and weight, these methods typically address only high-frequency vibration control. Consequently, they struggle to effectively mitigate vehicle body and component vibration noise at frequencies below 200 Hz. In recent years, acoustic metamaterials (AMMs) have emerged as a promising solution for suppressing low-frequency vibrations. This development offers a novel approach for low-frequency vibration control. Nevertheless, conventional design methodologies for AMMs predominantly rely on empirical knowledge and necessitate continuous parameter adjustments to achieve desired bandgap characteristics—an endeavor that entails extensive calculations and considerable time investment. With advancements in machine learning technology, more efficient design strategies have become feasible. This paper presents a tandem neural network (TNN) specifically developed for the design of AMMs. The trained neural network is capable of deriving both the bandgap characteristics from the design parameters of AMMs as well as deducing requisite design parameters based on specified bandgap targets. Focusing on addressing low-frequency vibrations in the back frame of automobile seats, this method facilitates the determination of necessary AMMs design parameters. Experimental results demonstrate that this approach can effectively guide AMMs designs with both speed and accuracy, and the designed AMMs achieved an impressive vibration attenuation rate of 63.6%. Full article

Evaluating noise, vibration, and harshness (NVH) performance is crucial in vehicle development. However, NVH evaluation is often subjective and challenging to achieve through numerical simulation, and typically prototypes are required. Dynamic driving simulators are emerging as a viable solution for assessing NVH performance in the early development phase before physical prototypes are available. However, most current simulators can reproduce vibrations only in a single direction or within a limited frequency range. This paper presents a comprehensive design optimization approach to enhance the dynamic response of a full-spectrum driving simulator, addressing these limitations. Specifically, in complex driving simulators, vibration crosstalk is a critical and common issue, which usually leads to an inaccurate dynamic response of the system, compromising the realism of the driving experience. Vibration crosstalk manifests as undesired vibration components in directions other than the main excitation direction due to structural coupling. To limit the system crosstalk, a flexible multibody dynamics model of the driving simulator has been developed, validated, and employed for a global sensitivity analysis. From this analysis, it turns out that the bushings located below the seat play a crucial role in the crosstalk characteristics of the system and can be effectively optimized to obtain the desired performances. Bushings’ stiffness and locations have been used as design variables in a multiobjective optimization with the aims of increasing the direct transmissibility of the actuators’ excitation and, at the same time, reducing the crosstalk contributions. A surrogate model approach is employed for reducing the computational cost of the process. The results show substantial crosstalk reduction, up to 57%. The proposed method can be effectively applied to improve the dynamic response of driving simulators allowing for their extensive use in the assessment of vehicles’ NVH performances. Full article

This study proposes a novel control framework for semi-active seat suspensions, specifically targeting motion sickness mitigation through precision suppression of vertical vibrations within the 0.1–0.5 Hz frequency range. Firstly, a fractional-order band-stop filter in conjunction with a linear quadratic regulator (LQR) controller under frequency-domain sensitivity constraints (0.1–0.5 Hz) is proposed to achieve frequency-selective vibration attenuation. Secondly, the multi-objective butterfly optimization algorithm (MOBOA) is adopted to optimize the LQR controller’s weighting matrices (Q, R) by balancing conflicting requirements in terms of human body displacement limits, acceleration thresholds, and suspension travel. Finally, experimental validation under concrete pavement excitation and random road profiles demonstrates significant advantages over conventional LQR, i.e., a 41.04% reduction in vertical vibration amplitude and a 55.95% suppression of acceleration peaks within the target frequency band. The combined enhancements offer dual benefits of enhancing ride comfort and motion sickness mitigation in real-world driving scenarios. Full article

To enhance riding comfort for drivers of heavy-duty vehicles, this paper introduces a novel adaptive prescribed performance control (APPC) for active seat suspension systems. The model incorporates dynamic friction and hysteresis damping effects to capture the complex behavior of the seat suspension. The accuracy of the proposed model is validated through experimental data. The controller utilizes a prescribed performance function (PPF) to regulate the dynamic response of the system, combined with an adaptive backstepping control (ABC) method to account for system uncertainties, such as variations in driver weight, friction, suspension stiffness, and damping coefficients. A set of parameter estimators, governed by innovative adaptive laws, compensates for estimation errors. Furthermore, the stability of the controlled system is rigorously demonstrated. Both simulation and experimental tests, including bump and random excitation tests, are conducted to assess the controller performance in both time and frequency domains. The results confirm that the proposed controller effectively mitigates vibrations in the driver–seat system and demonstrates robustness against system uncertainties. Full article

Especially in real-world circumstances with uneven road surfaces and impulsive shocks, nonlinear dynamic effects in vehicle systems can greatly skew biometric data utilized to track passenger and driver physiological states. By creating a thorough multibody human–seat–chassis model, this work tackles the effect of vehicle-induced vibrations on the accuracy and dependability of biometric measures. The model includes external excitation from road-induced inputs, nonlinear damping between structural linkages, and vertical and angular degrees of freedom in the head–neck system. Motion equations are derived using a second-order Lagrangian method; simulations are run using representative values of a typical car and human body segments. Results show that higher vehicle speed generates more vibrational energy input, which especially in the head and torso enhances vertical and angular accelerations. Modal studies, on the other hand, show that while resonant frequencies stay constant, speed causes a considerable rise in amplitude and frequency dispersion. At speeds ≥ 50 km/h, RMS and VDV values exceed ISO 2631 comfort standards in the body and head. The results highlight the need to include vibration-optimized suspension systems and ergonomic design approaches to safeguard sensitive body areas and preserve biometric data integrity. This study helps to increase comfort and safety in both traditional and autonomous car uses. Full article

This research presents an IoT-empowered adaptive mobility framework that integrates high-dimensional gesture recognition with edge-cloud orchestration for safety-critical human–machine interaction. The system architecture establishes a three-tier IoT network: a perception layer with 60 GHz FMCW radar and TOF infrared arrays (12-node mesh topology, 15 cm baseline spacing) for real-time motion tracking; an edge intelligence layer deploying a time-aware neural network via NVIDIA Jetson Nano to achieve up to 99.1% recognition accuracy with latency as low as 48 ms under optimal conditions (typical performance: 97.8% ± 1.4% accuracy, 68.7 ms ± 15.3 ms latency); and a federated cloud layer enabling distributed model synchronization across 32 edge nodes via LoRaWAN-optimized protocols (κ = 0.912 consensus). A reconfigurable chassis with three operational modes (standing, seated, balance) employs IoT-driven kinematic optimization for enhanced adaptability and user safety. Using both radar and infrared sensors together reduces false detections to 0.08% even under high-vibration conditions (80 km/h), while distributed learning across multiple devices maintains consistent accuracy (variance < 5%) in different environments. Experimental results demonstrate 93% reliability improvement over HMM baselines and 3.8% accuracy gain over state-of-the-art LSTM models, while achieving 33% faster inference (48.3 ms vs. 72.1 ms). The system maintains industrial-grade safety certification with energy-efficient computation. Bridging adaptive mechanics with edge intelligence, this research pioneers a sustainable IoT-edge paradigm for smart mobility, harmonizing real-time responsiveness, ecological sustainability, and scalable deployment in complex urban ecosystems. Full article

This study evaluates the safety aspects of a prototype electric vehicle designed to enable wheelchair users to independently perform simple farm tasks in rural settings, like sample collection and crop monitoring. The vehicle, built at CREA, features four in-wheel electric motors, a pneumatic suspension system, and a secure wheelchair anchoring system. Tests at the CREA experimental farm assessed the vehicle’s whole-body vibrations on different surfaces (asphalt, headland, dirt road) using two tyre models and multiple speeds. A triaxial accelerometer on the wheelchair seat measured vibrations, which were analysed in accordance with ISO standards. Frequency analysis revealed significant vibrations in the 2–40 Hz range, with the Z-axis consistently showing the highest accelerations, which increased with the speed. Tyre A generally induced higher vibrations than Tyre B, likely due to the tread design. At high speeds, the effective accelerations exceeded safety thresholds on asphalt and headland. Statistical analysis confirmed speed as the dominant factor, with the surface type also playing a key role—headland generated the highest vibrations, followed by dirt road and asphalt. The results of these first tests highlighted the high potential of the vehicle to improve the agricultural mobility of disabled people, granting safety conditions and low vibration levels on all terrains at speeds up to 10 km h⁻¹. At higher speeds, however, the vibration levels may exceed the exposure limits, depending on the irregularities of the terrain and the tyre model. Overcoming these limitations is achievable through the optimization of the suspensions and tyres and will be the subject of the next step of this study. This technology could also support wheelchair users in construction, natural parks, and urban mobility. Full article

Good seat comfort can bring a pleasant experience to commercial vehicle drivers. Therefore, it is necessary to study the vibration characteristics of commercial vehicle seats. This study focuses on commercial vehicle seats with air spring suspension. The friction damping expression of the suspension system was derived. Comprehensive simulation and experimental investigations were conducted on the vertical vibration transmission characteristics of the seat. A multi-objective optimization framework was established by integrating the NSGA-II algorithm with a BP neural network. Specifically, a nonlinear mathematical model was developed using the GA-BP neural network algorithm, with four design parameters as optimization variables: air spring stiffness (K₁), damper damping coefficient (C₁), cushion equivalent stiffness (K₂), and cushion equivalent damping coefficient (C₂). The optimization objective was defined as minimizing the maximum seat transmissibility (T_R) at the resonance frequency (f). Through the NSGA-II, Pareto optimal solutions were systematically explored, and an optimal parameter combination was identified to enhance the dynamic comfort of the commercial vehicle seat. Full article

Vibration can have a significant impact on long-term health, driver comfort, and vehicle performance. With a focus on steering wheel vibrations, this study examines both general and local vibrations that affect the driver. Under real-world conditions, a series of controlled test drives were conducted, with high-precision accelerometers mounted on the driver’s seat and steering wheel recording vibration data. The measurements were conducted in accordance with ISO 5349 and ISO 2631-1, which guaranteed a consistent assessment of vibration exposure. The results suggest that the daily vibration exposure for general vibrations at the driver’s seat is significantly lower than the legal limit, as evidenced by the presence of significant frequencies in the vertical (Z) axis. Nevertheless, steering wheel vibrations may cause pain due to their proximity to the resonance frequencies of the human hand–arm system, which have frequency maxima at approximately 35 Hz and harmonic 70 Hz. Additionally, the vibration intensity was elevated at vehicle velocities between 70 and 80 km/h, suggesting the potential presence of a resonance effect within the suspension or powertrain. The results emphasize the significance of advanced vibration reduction strategies in enhancing driver comfort and safety, including the implementation of a well-designed steering system and enhanced seat absorption. This research offers valuable insights for automotive engineers and ergonomics specialists who are interested in minimizing long-term health risks and vibration-induced fatigue. The aim of this study is to indicate the areas of the drive system fault that have a direct impact on the vibrations of the body structure. The article presents an analysis of the recorded vibration results based on which of the areas of change in the comfort of using the vehicle were selected. Full article

Winch-assisted harvesting has expanded considerably in recent years as it enables ground-based machines to work safely on steep slopes. To analyze operator exposure to whole-body and hand–arm vibration (WBV, HAV) and noise exposure (LA_eq, LC_peak) during winch-assisted harvesting (TW) and harvesting without winch assistance (NTW), a field study using a Ponsse Scorpion King harvester and an Ecoforst T-winch traction winch was conducted. Vibrations were measured at three locations inside the cabin (seat, seat base/floor, control lever), while noise exposure was recorded both inside and outside the cabin. WBV exposure during work time operations was highest in the Y-direction, both on the seat (0.49–0.87 m/s²) and on the floor (0.41–0.84 m/s²). The WBV and HAV exposure levels were highest while driving on the forest and skid road. Exposure during the main productive time was significantly influenced by the harvesting system, diameter at breast height (DBH), and tree species. Noise exposure was higher, while WBV and HAV exposures on the seat, floor and control lever were lower during non-work time than during work time. The daily vibration exposure on the seat exceeded the EU action value, while LC_peak noise exposure surpassed the limit value of 140 dB(C) on all measured days. Noise and vibration exposure were constantly higher during TW than NTW harvesting but differences were small. Compared to other studies, the results show that harvesting on steep terrain increases noise and vibration exposure, while non-work time has the opposite effect on vibration and noise exposure. Full article

Long-term vibrations endanger driver health and affect ride performance. Semi-active seat suspension systems equipped with magnetorheological (MR) dampers can effectively reduce vibrations transmitted to drivers, exhibiting excellent potential for widespread applications owing to their outstanding performance characteristics. In this paper, we propose an adaptive backstepping control system with time-delay compensation (ABC-C) for an MR-damper-based semi-active seat suspension system to enhance ride comfort and stability in commercial vehicles. The control framework integrates a reference model, an adaptive backstepping controller, a time-delay compensator, and an MR damper inverse model. The reference model balances ride comfort and stability using high-pass and low-pass filters, while the adaptive controller ensures robustness against parameter uncertainties and disturbances. A time-delay compensator mitigates delays in the control loop, improving system stability and performance. Numerical simulations under harmonic, bump, and random excitations demonstrated the superior performance of the ABC-C controller. The experimental results show that under random road excitation conditions, the frequency-weighted root mean square (FW-RMS) of acceleration was reduced by 26.9%, the vibration dose value (VDV) decreased by 29.3%, and the root mean square of relative displacement (RMS_rd) was reduced by 58.46%. The results highlight the practical effectiveness of the ABC-C controller in improving ride comfort and safety for drivers of commercial vehicles, offering significant potential for real-world applications. Full article

This study examines the efficacy of a seat inertial suspension system in relation to vibration isolation and energy recovery in electric commercial vehicles. The research focuses on the structural modifications of the suspension system that arise from the incorporation of an inerter, a novel vibration isolation component. A dynamic model of the seat inertial suspension is constructed, which includes two different structures consisting of components connected in parallel and in series. The analysis explores how the absorption of suspension parameters affects both seat comfort and the characteristics of energy harvesting. Furthermore, an optimal design methodology for the seat inertial suspension is proposed, seat comfort and energy recovery efficiency are also taken into consideration. The findings reveal that the parallel-structured seat inertial suspension system demonstrates superior overall performance. Specifically, it achieves a 36.6% reduction in seat acceleration, a 55.3% decrease in suspension working space, and an energy harvesting efficiency of 41.9%. The seat inertial suspension significantly improves occupant comfort by reducing seat acceleration, significantly reducing the amplitude of seat suspension movement, and recovering most of the seat suspension’s vibration energy, in comparison to traditional seat suspension systems. Full article

Whole-body vibration (WBV) exposure presents occupational health risks across multiple industries, particularly in tasks involving heavy machinery and prolonged seating. This study examines WBV risk factors, intervention strategies, and the potential for digital monitoring solutions to strengthen workplace safety. A sector-wide analysis assessed vibration exposure levels, worker-reported discomfort, and the effectiveness of the existing control measures. The study introduces a conceptual framework for a mobile application designed to integrate real-time exposure tracking, structured worker feedback, and predictive risk assessment. The findings confirm that WBV exposure varies across industries, with the energy and maritime logistics sectors showing the highest levels of noncompliance. A tiered intervention strategy, classified by impact and effort, provides a structured method for prioritizing risk reduction measures. Immediate actions, such as real-time monitoring and preventive maintenance, require minimal effort but provide high-impact benefits, while long-term strategies, including ergonomic workstation redesign, demand greater investment but contribute to sustained exposure reduction. The proposed framework offers a scalable, data-driven approach to WBV risk management, transitioning workplace safety from compliance-based monitoring to proactive prevention. Future research should explore implementation feasibility, worker adoption, and the integration of AI-driven safety recommendations to support continuous improvements in workplace safety strategies. Full article

This paper systematically reviews research progress in semi-active suspension systems for agricultural machinery seats, focusing on key technologies and methods to enhance ride comfort. First, through an analysis of the comfort evaluation indicators and constraints of seat suspension systems, the current applications of variable stiffness and damping components, as well as semi-active control technologies, are outlined. Second, a comparative analysis of single control methods (such as PID control, fuzzy control, and sliding mode control) and composite control methods (such as fuzzy PID control, intelligent algorithm-based integrated control, and fuzzy sliding mode control) is conducted, with control mechanisms explained using principle block diagrams. Furthermore, key technical challenges in current research are summarized, including dynamic characteristic optimization design, adaptability to complex operating environments, and the robustness of control algorithms. Further research could explore the refinement of composite control strategies, the integrated application of intelligent materials, and the development of intelligent vibration damping technologies. This paper provides theoretical references for the optimization design and engineering practice of agricultural machinery suspension systems. Full article