Analysis of powered two-wheeler accident scenarios and multi-body simulations to support trunk protective equipment impact test methods.

Abstract In this work, a robust control design for balance and walking control of humanoid biped robot in presence of external disturbances is proposed. The controller combines Capture Point (CP) tracking controller with Extended State Observer (ESO) in order to achieve robustness against unknown disturbances, parametric uncertainties as well as unmodeled dynamics denoted as a composite disturbance. The effect of the composite disturbance is estimated by ESO as an extended state of the system and the estimate is used to augment the CP tracking controller in order to achieve robustness. Closed loop stability analysis under the proposed control is carried out. The efficacy of the design is first verified for a simplified Linear Inverted Pendulum Model (LIPM) and subsequently, through NAO multi-body simulations. It is shown that the proposed design achieves robust balance and walking control for biped humanoid robot in presence of unknown composite disturbances.

Abstract A scientific disparity exists on the question of how total knee arthroplasty (TKA) size and the main dimensions of a TKA affect wear on the tibial insert. Although some results have been presented about the existence of such a relationship, a closed form mathematical description or approximate solution has not yet been delivered. This paper provides a numerical description on the influence of TKA size and TKA-related dimensionless parameters on tibial tray wear by means of multibody dynamics simulations (MBD) involving six commercially available, cruciate retained (CR) TKAs. Boundary- and initial conditions for the multibody dynamics simulations were set according to ISO 14243-1-2009 standards to facilitate comparison with experimental data found in the relevant literature. Results showed that the all investigated parameters have a critical level of impact on wear and they can be predominantly approximated by linear functions. The specific TKA depth ratio (R2 = 0.89) has the strongest effect by having the highest positive slope (40.27). This parameter is followed by the specific TKA volume ratio (R2 = 0.77) with a relatively high positive slope (18.77). The third parameter in the rank is TKA size (R2 = 0.99), where the effect on wear, based on its slope (1.59), is considerable lower. The specific TKA width ratio (R2 = 0.91) was ranked as the fourth parameter, since as a quadratic function, has a peak, which also limits its maximum effect on wear. Therefore, this parameter was evaluated as the one with the least effect. These findings, together with the introduced dimensionless parameters, serve as practical design ratios, highlight alternatives on how to enhance TKA wear performance and ensure minimal wear by optimal sizing.

Automated driving (AD) is a developing technology aimed at decreasing traffic accidents and enhancing driving efficiency. This research seeks to create a decision-making approach for self-driving cars, emphasizing actions such as changing lanes, overtaking, and maintaining lane position on highways, through deep reinforcement learning (DRL). In order to achieve this, a driving environment simulating a highway is established in the commercial multi-body simulation software IPG CarMaker 11, allowing the ego vehicle to navigate around other vehicles safely and efficiently. A control framework with a hierarchical structure is established to oversee these vehicles, where the high-level control is tasked with making driving choices. Additionally, the Duel Deep Deterministic Policy Gradient (Duel-DDPG) algorithm, which is a Deep Reinforcement Learning (DRL) method, is employed to create the highway decision-making strategy, which is simulated using MATLAB software. The computational methods of the Duel-DDPG and DDPG algorithms are examined and contrasted. A series of simulation evaluations are performed to evaluate the efficacy of the suggested decision-making policy. The results emphasize the advantages of the proposed framework regarding convergence rate and control effectiveness. The findings indicate that the Duel-DDPG-based approach effectively and safely performs highway driving activities.

Multibody simulations are fundamentally important as they allow for reducing time to market, prototype development, and safety risks. In dynamic simulations involving ground vehicles, tire modelling is particularly relevant, as the majority of forces and the resulting moments act on the vehicle through the tire–ground contact. This paper analyzes the case of a forklift produced by Toyota Material Handling Manufacturing Italy (TMHMI), equipped with solid rubber tires. The simulated maneuver consists of an impact with a cleat. The aim of the study is to reproduce the vehicle's bump response in order to obtain load histories required for subsequent durability analyses. To this end, an effective tire model with low computational cost is proposed. To this end, the authors developed three models to describe the radial dynamics of the wheel, based on experimental data obtained from a test bench at the University of Pisa. The models were validated by comparing the vertical acceleration signals obtained from multibody simulations with those acquired during an experimental campaign on the vehicle, in which the obstacle-crossing test was replicated. The results highlight the importance of using hysteretic models, such as the Bouc-Wen model, to describe the rheological behaviour of tires.

Abstract The design of delta robots poses significant challenges as their mechanical behavior depends on a high number of dimensional parameters and dynamic factors. This is further compounded by the presence of demanding performance requirements, particularly in terms of position accuracy during high-dynamics motion tasks. By leveraging theoretical models, dynamic optimization techniques and advanced simulations, the present paper aims to streamline the design process, providing a structured engineering method and tool to address the dimensional synthesis of delta robots, encompassing kinematics, dynamics, link flexibility, and ball joint clearance. The systematic design process incorporates user requirements, including bounding box specifications, cycles per minute for pick-and-place operations, end-effector accuracy tolerance, maximum static payload, and cost minimization. The methodology involves an initial dynamic optimization phase employing a genetic algorithm to derive optimal dimensional parameters. Analytical models implemented in Matlab expedite the iterative optimization process. Then, the optimized design is virtually prototyped in RecurDyn flexible multibody simulation tool for validation by including the link flexibility and the effect of ball joint clearances. The iterative approach ensures that the final design aligns with user expectations. Additionally, the paper addresses motor selection based on torque requirements and proposes an approach for evaluating the robot performance in terms of maximum end-effector acceleration and payload. Finally, the efficacy of the tool is evaluated through a case study focused on designing a manipulator as an integral part of a collaborative research project with an industrial partner. Graphical Abstract

Space mesh antennas require large-diameter reflectors to achieve aperture surfaces with high gain. To date, many pioneering studies have pursued deployable mechanisms capable of achieving high deployment ratios, primarily focusing on ring and umbrella structures for spaceborne antennas. In this work, a conceptual design of a Deployable Pantograph Rib structure-based parabolic Antenna (De-PaRA) is presented by employing pantograph structures that ensure high stowage efficiency. This approach addresses the shortcomings of conventional space antenna mechanisms. In parallel, this study aims to overcome the structural safety issues that may arise from insufficient axial stiffness of the rib geometry after deployment. To achieve these objectives, superelastic shape memory alloy (SMA) wires were integrated along the antenna ribs to reinforce axial stiffness while maintaining constant inter-rib spacing. Modal analysis demonstrated that SMA wire integration increases the axial stiffness by approximately 2-fold, with eigenfrequency rising from 9.932 to 14.3 Hz. A prototype with a 1.6 m deployed diameter, achieving a volume deployment ratio of 58.8, was quantitatively evaluated through multi-body dynamics simulations and experiments. These results demonstrate reliable deployment operation and mechanical feasibility.

BACKGROUND: For trucks, dependent suspension with longitudinal semi-elliptical springs is the most common. The widespread use of the suspension system with leaf springs caused by the simplicity of its design, low cost and low maintenance complexity, as well as the fact that the leaf springs simultaneously perform the functions of an elastic and guiding element. However, despite the widespread use and obvious advantages, few-leaf springs function modeling in a multibody dynamic system is a difficult task. To study the dynamics of vehicles with leaf spring suspensions, it is necessary to have an accurate and at the same time high-performance model. Therefore, it is very important to choose a reasonable mathematical model of a leaf spring. AIM: Comparison of multibody simulation mathematical models of well-known few-leaf springs, used in suspension of wheeled vehicles. METHODS: TThe solution of the problem is carried out by comparing the known methods of modeling leaf springs in terms of calculation time and accuracy of the results obtained in the NX software package in the environment of dynamics of coupled bodies Simcenter 3D Motion. RESULTS: In the course of the work, the 4 most common methods of modeling small leaf springs in the environment of dynamics of solids are considered. Based on the analysis, the most rational method was identified, providing the highest accuracy and calculation speed (less than 5 seconds). CONCLUSION: The chosen method of leaf spring suspension modeling can be used for studying vehicle dynamics, so high-quality results in a short period of time may be obtained.

Time-invariant hybrid zero dynamics control of quadruped robot incorporating multibody simulation in MSC ADAMS

Squat is a type of rail defect that frequently poses challenges for railway tracks, as they generate dynamics and accelerate track degradation. Detecting rail squats is resource-intensive, given their relatively small size compared to the railway track. Often, by the time they are detected, damage has usually already occurred in other track components. Currently, rail squats are primarily detected using dedicated railway measurement vehicles. There has been a recent trend in research towards utilizing trains in regular traffic to monitor the condition of railway tracks. However, there is a lack of research and general guidelines regarding the optimal placement of accelerometers or sensors on trains for squat detection. In this study, multibody simulation software GENSYS Rel.2209 is employed to simulate a passenger train traversing rail squats under various scenarios, with each scenario characterized by a distinct set of typical feature values for the squats. The results demonstrate that the front wheel set, positioned closest to the defects, exhibits the highest sensitivity to vertical accelerations. Squat length is much more sensitive than depth for detection at typical speeds, and accelerometers on bogies or the car body require speeds below 40 km/h to ensure reliability. The acceleration response mechanism during squat traversal is explored, revealing the effects of varying squat geometries and train speeds. This finding enables a detection method capable of locating squats and estimating their length with over 90% accuracy. Practical recommendations are provided for optimizing squat detection systems, including squat width detection, sensor selection criteria, and suggested train speeds. It offers a pathway to detect squat more efficiently with optimized installation locations of accelerometers on a train.

BackgroundTo reach Vision Zero, injuries with long-term consequences (LTCs) need to be considered in the development of (public) vehicles. In the EU project ProtAct-Us, methods for the assessment and principles for countermeasures will be developed.MethodsThe German GIDAS and MHH database were analyzed to identify bus and shuttle occupant injuries and the accident scenarios in which they occur. Accident type, collision partners and collision speeds as well as gender, age, passenger position (seated or standing), impact points in the bus, injured body regions and associated injuries were identified.ResultsThis led to the definition of three basic use cases, all in an urban environment. The main scenario leading to injuries was braking maneuver, followed by frontal and side collisions. The velocities / decelerations are 7 m/s² (braking) and 30 kph for frontal/side collision. Scenarios will be simulated with standing, forward and sideward sitting passengers. For the identified scenarios, Finite Element (FE) and Multibody (MB) simulations are conducted in several ways. The first option is to use MB models of the full body and determine the boundaries (angle, velocity) of their contact at potentially unsafe spots in the bus. Further, the kinematics is transferred to more detailed FE models which are then used to calculate the injury risk. The second option is to run simulations with FE full body models (Human body models) which are directly assessed. For the calculation of the head injury risk it is further possible to transfer the kinematic boundaries to the Strasbourg University Finite Element Head Model (SUFEHM). For those body regions, which are known from statistics to be most likely injured, the risk is assessed. This includes head, rib and in some cases femur injuries.ConclusionsIn order to mitigate the long-term consequences of these injuries, the project will develop concepts for countermeasures, the principles of which are presented in this publication.Key messages• A method for the assessment of injuries with long-term consequences for bus occupants is presented. FE and MB simulations are used to quantify the injury risk for most vulnerable body regions.• Injured body regions of bus occupants and the impact locations on buses are identified in accident statistics. Principles of countermeasures for these spots are presented to avoid these injuries.TopicBus occupants, Long-term injuries, MB/FE simulation.

BackgroundAddressing serious injuries with long-term consequences (LTCs) remains a key challenge for achieving Vision Zero. Cyclists and e-scooter riders represent a large share of road users involved in major injury accidents. In the context of EU-funded project ProtAct-Us data analysis shows that head and brain injuries (HBI) account for around 40% of all LTC-related outcomes among these groups, making them the most critical injuries.MethodsThis study assesses HBI risk for cyclists and e-scooter users through multibody accident reconstructions and finite element (FE) simulations to propose LTC-reducing countermeasures. The most common accident scenarios were identified using MHH Accident Research Unit and REHABIL-AID data, covering both single-vehicle and vehicle collisions. Multibody simulations recreated these scenarios to extract head kinematics before impact. These were then used in a predictive FE head model to assess HBI risk. Helmet effectiveness, with and without anti-rotational technology, was also evaluated under the same conditions.ResultsIn total, 42 simulations were run to capture pre-impact head conditions. FE results revealed a high risk of skull fractures and brain injuries — over 90% — when no helmet was used. However, wearing a helmet significantly reduced the injury risk in all cases, regardless of anti-rotational features. This confirms the strong protective value of helmets in reducing LTC-related head trauma.ConclusionsThe study emphasizes the high risk of serious head injuries for unprotected cyclists and e-scooter users, including skull fractures and neurological damage. These findings offer insights for public authorities and aim to raise awareness among users about helmet use. They support discussions on mandatory helmet laws and the development of improved helmet designs and safety standards for modern urban mobility.Key messages• Risk of LTCs associated with skull fracture and neurological injuries for unprotected cyclists and e-scooter riders involved in accidents is high.• Wearing a helmet, whether it includes anti-rotational technology or not, significantly reduces the risk of head/brain injury in all accident scenarios.TopicBicycle and e-scooter accidents, long-term head Injury consequences, head protective systems.

This study investigates the influence of suspension elastokinematics on vehicle handling and stability through a combined research of experimental testing and numerical simulation. Laboratory tests were conducted on the front suspension of a Mercedes-Benz S320 using a quarter-car test rig equipped with specialized sensors to measure wheel displacements, steering angles, camber, and accelerations. Complementary dynamic tests were carried out under real driving conditions, including braking in a turn and “fishhook” maneuvers, to capture suspension behavior under critical operating scenarios. Based on the experimental data, an MSC Adams/Car multibody simulation model was used, incorporating varying stiffness values of suspension elastomeric elements that replicated progressive aging and degradation effects. The simulation results were compared with experimental data to validate the model’s predictive capability. Key findings indicate that reductions in elastomer stiffness significantly affect wheel kinematics, vehicle yaw response, and lateral acceleration, particularly during high-intensity maneuvers. The results underline the critical importance of accounting for elastomeric component degradation in suspension modeling to ensure vehicle safety and performance over the operational lifespan. The developed methodology demonstrates the effectiveness of integrating experimental measurements with advanced simulation tools to assess elastokinematic effects on vehicle dynamics.

In comparison to internal combustion engines, which usually have low frequency, broadband excitations, in electric vehicles, tonal excitations from the electric drivetrain are noticeable and disturbing. As the acoustic and structural dynamic behavior, often referred to as noise, vibration, and harshness (NVH), strongly influences customers’ quality perceptions, optimizing it is a key challenge in development. This study investigates the influence of static rotor–stator eccentricity on the NVH behavior of an electric drivetrain using a transient elastic multibody simulation (eMBS) model incorporating non-linear gear meshing, bearing contact, and electromagnetic forces. The analysis identifies the 36th order excitation of the electric machine as the dominant source, leading to a maximum total acceleration level of 152 dB. Two specific excitation directions were found to reduce this amplitude most effectively. However, varying the amount of static eccentricity in these directions resulted in only minor vibration reductions (<1.5 dB). The findings indicate that the symmetric mode shapes of the cylindrical housing govern the response, indicating that addressing the excitability of housing modes by developing asymmetric housing designs could offer a more effective approach for NVH optimizations of electric drivetrains.

A coordinated profile co-optimization strategy for the piston–liner pair was introduced to simultaneously reduce friction losses and dynamic excitation. Based on the main parameters of the engine. Lubrication theory and the finite element method, and explicitly accounting for elastic deformation of flexible bodies, a multibody dynamics simulation model of the piston–connecting rod–crankshaft–cylinder liner system was developed in AVL Excite. This model was used to evaluate the dynamic and tribological performance of five cylinder-liner pre-compensation geometries at rated operating conditions. A bottleneck-shaped liner exhibited the best tribological performance, reducing the average total piston–skirt friction loss by 20.8% and the peak asperity–contact pressure by 19.7%, while leaving piston kinematics essentially unchanged (an increase of 0.001 mm in the maximum radial displacement and 0.009° in the maximum tilt angle). Building on this liner, key piston–skirt profile parameters were optimized via response–surface methodology; with the optimized skirt, the maximum radial displacement decreased from 0.123 mm to 0.113 mm, the maximum tilt angle decreased from 0.463° to 0.462°, the third-order Fourier component of lateral acceleration decreased from 14.53 m/s2 to 13.26 m/s2, and the cycle-averaged total skirt friction loss decreased from 0.307 kW to 0.250 kW.

This study introduces a computational framework that formalizes rollover risk in heavy-duty vehicles by integrating simulation-informed physical modeling with sensor-driven decision logic. The approach combines high-fidelity fluid–structure interaction modeling (via CFD) with multibody vehicle dynamics simulations to capture the complex behavior of rotating, partially filled mixer tanks under dynamic conditions. Rollover thresholds were identified by extracting the maximum safe speeds across a range of maneuvers (e.g., steady-state turning and step steering), using tire lift-off as the critical indicator. These thresholds were then formalized into decision rules using onboard sensor data, such as lateral acceleration, steering input, and tank rotation speed, allowing a real-time rollover warning system to continuously compare current vehicle states against critical limits. By systematically extracting critical force and moment responses and translating them into limit values provided by conventional onboard sensors (lateral acceleration, roll angle, steering input), the framework bridges high-fidelity simulation and real-time monitoring. A concrete truck mixer is used as a case study to demonstrate the utility of this approach in formalizing rollover thresholds for real-world decision support. Beyond the specific vehicle type, this work contributes to the broader discourse on how computational methods can contribute to new control or assistance strategies for safety-critical systems.

Rail transport is widely acknowledged as one of the safest modes of land transportation. However, derailments remain a significant safety concern that can lead to catastrophic outcomes. This paper presents results from a research aimed at supporting the design of effective derailment containment measures through numerical simulation techniques, employing a multibody model to simulate the post-derailment behaviour of a railway trainset. This model is combined with a finite element model of a track-based derailment containment device and is used to predict the forces on this structure resulting from the impact with the derailed train. The key innovations presented in this paper include the modelling of the entire trainset instead of a single vehicle, considering the effect of inter-vehicle interaction forces due to the traction gear and buffers, and the modelling of guard rails as an alternative to derailment containment walls which were previously investigated. The introduction of these new features enhances the scope and accuracy of the model, particularly providing a more accurate prediction of the impact forces which considers the effect of the interaction between adjacent vehicles, and the possibility to compare different derailment mitigation measures.

Fuzzy Control Design for Steering and Speed in Autonomous Agricultural Vehicles: A Multibody Simulation Study

Increasing axle loads and speeds in heavy-haul railway systems have intensified rail and wheel damage, leading to elevated maintenance costs and reduced operational efficiency. A promising solution to this issue without compromising service demands is enhancing wheel – rail interaction through optimisation of rail profiles. This study introduces a rail profile optimisation framework tailored for a broad-gauge heavy-haul network experiencing excessive rail wear, utilising Non-dominated Sorting Genetic Algorithm II (NSGA-II). The framework is designed to minimise wear and rolling contact fatigue (RCF) while maintaining satisfactory and safe vehicle dynamic performance. The framework includes optimisation of both high and low rail profiles for sharp and mild curves, as well as optimisation of two rail profiles for tangent track to improve contact point distribution and reduce hollow wear. The optimisation process is based on in-service profiles to ensure practical grindability and incorporates multi-body simulations (MBS) to assess wheel and rail damage as well as vehicle dynamic behaviour. The results indicate that the optimised profiles substantially reduce wear and RCF across various track sections. Furthermore, long-term wear and RCF evaluation of rail profiles on sharp and mild curves confirm the superior performance of optimised profiles, thereby validating their potential for integration into maintenance practices.

The accurate motion of roller-bearing-supported rings is critically influenced by shape and positional tolerances, which are often underestimated in conventional modeling approaches. The aim of this study is to develop and validate a multibody dynamic framework capable of quantifying the impact of roundness and positional errors on the motion accuracy of roller-bearing-supported rings. Shape errors are modeled using Fourier series and incorporated into a high-fidelity multibody simulation environment. Experimental validation using laser triangulation reveals a maximum runout error of 72.9 μm, compared to a numerically predicted value of 88.6 μm, resulting in a quantified numerical overestimation of 21.5%. Parametric studies investigated the effects of harmonic order, error amplitude, and combined error scenarios on key performance metrics, including trajectory runout and initial offset displacement. Results reveal that the trajectory errors range between 0.29 mm and 0.63 mm for shape error orders and can escalate to 2.84 mm for high amplitude errors, demonstrating the critical role of error order and amplitude. Furthermore, combined simulations show that bearing position errors exert a more pronounced effect on radial accuracy than shape deviations alone. The proposed approach enables precision design evaluation and tolerance optimization in high-accuracy applications, including robotics, aerospace mechanisms, and optical alignment systems.