Multi-body Dynamics Simulation Model Research Articles

Analysis of the degradation in transmission accuracy of RV reducers considering the wear clearance between cycloidal wheels and pinwheels

To accurately determine the transmission accuracy degradation pattern of Rotate Vector (RV) reducers due to wear, a predictive method is proposed that simultaneously considers the initial clearance and wear clearance between the cycloid wheel and the pinwheel. The initial clearance is derived from a comprehensive gear system analysis, considering assembly errors, manufacturing errors and modifications. Building on this, the wear depth of the cycloid wheel tooth profile is numerically simulated using Archard's wear theory, revealing the wear distribution pattern under various operating conditions. A Gaussian regression model is used to predict the maximum wear amount for different operational durations. Based on the predicted wear amount, a multi-body dynamic simulation model incorporating wear clearance was established to analyze the transmission error under varying clearance conditions. Results indicate that the wear depth along the tooth profile initially increases and then decreases. The depth and region of wear along the tooth profile gradually increase with load and output speed, with the impact of load on the wear region being greater than that of output speed. Under the initial clearance condition, the maximum transmission error is 22.91″. As the wear clearance increases, transmission accuracy declines sharply. When the cumulative wear clearance reaches 0.2 mm, the transmission error exceeds the allowable backlash limit. This study provides a theoretical reference for predicting accuracy degradation and guides the manufacturing design of RV reducers.

Rapid and precise calibration of soil microparameters for high-fidelity discrete element models in vehicle mobility simulation

In the realm of numerical simulations concerning vehicle mobility, the establishment of a high-fidelity soil discrete element model often necessitates substantial parameter adjustments to align with the mechanical responses of actual soil. In pursuit of a rapid and precise calibration of the microparameters of the soil model, this paper describes an approach rooted in machine learning surrogate models. This method calibrates the corresponding discrete element microparameters based on the macroscopic Mohr–Coulomb parameters derived from actual soil direct shear tests. The distinct contribution lies in the creation of a dataset that bridges the soil microparameters and macroparameters through simulated direct shear tests, which serves as training data for machine learning algorithms. Additionally, an adaptive particle swarm optimization neural network algorithm is proposed to represent the nonlinear relationships among parameters within the dataset, thus achieving intelligent calibration. To verify the reliability of the proposed soil calibration model in the context of vehicle mobility simulations, a co-simulation is conducted using a vehicle multibody dynamics simulation model and the calibrated soil model, with validation conducted across multiple criteria.

Research on non-linear dynamic simulation model of feeding system

Abstract The automatic gun feeding system is an important mechanism for achieving continuous shooting, but due to its complex structure, there is a lot of contact during firing, and its reliability is lower. To improve the reliability of the feeding system and its dynamic characteristics, a multi rigid body dynamic simulation model of the feeding system considering contact nonlinearity was established based on nonlinear dynamics theory. The dynamic characteristics of the feeding system were analyzed for single and continuous firing. The research results indicate that the presence of contact nonlinearity increases the interaction forces between components and also increases the uncertainty of component motion.

Optimization of the cruising speed for high-speed trains to reduce energy consumed by motion resistances

As one of the effective measures to reduce energy consumption of high-speed railway, train operation control has gained much attention because of its cost-effectiveness. Conventional approaches to eco-driving generally rely on single-mass train models and lack a thorough investigation into the vehicle cruising process, which can overlook real-world operation conditions and hinder further improvements in energy efficiency. To address these issues, this paper proposes a comprehensive framework for optimizing the cruising speed of high-speed trains (HSTs) based on track conditions to reduce energy consumed by motion resistances (ECMR). Firstly, a multibody dynamics simulation model of the HST is developed and validated to accurately evaluate ECMR under a range of operation scenarios. Simulation results show that the impact of speed on ECMR varies considerably according to track characteristics. Subsequently, a neural network is constructed to derive the regressive relationship between operation conditions and ECMR. On this basis, an optimization model for the cruising speed under different track conditions is formulated to minimize the ECMR of a railway segment with a given operation time. Finally, the effectiveness of the model is validated through case studies, which demonstrate that ECMR can be reduced by up to 27.85% compared to traditional control strategies. The proposed optimization method can be integrated with current train speed profiles to further enhance energy efficiency. This framework has broad applicability for addressing engineering problems related to train operation optimization.

Improving the energy efficiency and riding comfort of high-speed trains across slopes by the optimized suspension control

As the link between cities, the high-speed train (HST) not only effectively enhances national and regional accessibility, but also induces much energy consumption. On the other hand, passengers have a higher requirement for riding comfort of HST than before. Considering the impacts of slope gradient on energy consumption and vertical carbody acceleration, this paper optimizes the scale factor of the damper controller depending on the running condition to juggle the energy efficiency and riding comfort when HST is across slopes. Firstly, the multibody dynamics simulation model of HST is established to evaluate the energy consumed by motion resistances and carbody vibrations. Then the Skyhook control strategy is applied to the secondary vertical damper of the vehicle model. The effects of vehicle speed, slope gradient, and scale factor of the Skyhook controller on energy saving and vertical carbody acceleration of HST are investigated. Based on the simulation results, the Gaussian process regression model is established to predict the vehicle performance and describe the bi-objective optimization problem. It is demonstrated that the optimized Skyhook control system can at most save energy consumed by motion resistances by 8.52 % or reduce vertical carbody acceleration by 37.14 % without sacrificing the other target. Finally, a comprehensive feasibility and economic analysis of the proposed control system is carried out to promote its practical implementation.

Evaluation of Ground Pressure, Bearing Capacity, and Sinkage in Rigid-Flexible Tracked Vehicles on Characterized Terrain in Laboratory Conditions.

Trafficability gives tracked vehicles adaptability, stability, and propulsion for various purposes, including deep-sea research in rough terrain. Terrain characteristics affect tracked vehicle mobility. This paper investigates the soil mechanical interaction dynamics between rubber-tracked vehicles and sedimental soils through controlled laboratory-simulated experiments. Focusing on Bentonite and Diatom sedimental soils, which possess distinct shear properties from typical land soils, the study employs innovative user-written subroutines to characterize mechanical models linked to the RecurDyn simulation environment. The experiment is centered around a dual-tracked crawler, which in itself represents a fully independent vehicle. A new three-dimensional multi-body dynamic simulation model of the tracked vehicle is developed, integrating the moist terrain's mechanical model. Simulations assess the vehicle's trafficability and performance, revealing optimal slip ratios for maximum traction force. Additionally, a mathematical model evaluates the vehicle's tractive trafficability based on slip ratio and primary design parameters. The study offers valuable insights and a practical simulation modeling approach for assessing trafficability, predicting locomotion, optimizing design, and controlling the motion of tracked vehicles across diverse moist terrain conditions. The focus is on the critical factors influencing the mobility of tracked vehicles, precisely the sinkage speed and its relationship with pressure. The study introduces a rubber-tracked vehicle, pressure, and moisture sensors to monitor pressure sinkage and moisture, evaluating cohesive soils (Bentonite/Diatom) in combination with sand and gravel mixtures. Findings reveal that higher moisture content in Bentonite correlates with increased track slippage and sinkage, contrasting with Diatom's notable compaction and sinkage characteristics. This research enhances precision in terrain assessment, improves tracked vehicle design, and advances terrain mechanics comprehension for off-road exploration, offering valuable insights for vehicle design practices and exploration endeavors.

Dynamic Performance Optimization of Monorail Rapid Transit Formation Vehicles Based on Improved Artificial Potential Field Algorithm

This paper presents a new type of monorail rapid transit vehicle, which can operate in formation. In order to optimize the dynamic performance of the formation vehic-les when passing through the small radius curve, this paper first analyzes the structure of the new monorail rapid transit vehicle, and establishes the vehicle dynamic model and multi-body dynamics simulation model. Then the improved artificial potential field algorithm is used to build the formation vehicle operation controller. Finally, the dynamic performance evaluation index of the new mono-rail rapid transit formation vehicle is formulated, and the formation vehicle passing through the small radius curve scene is simulated. The simulation results show that the controller of the formation vehicle with dynamic optimi-zation control can effectively optimize the load transfer coefficient of running wheels, unbalanced centrifugal acce-leration and roll angle of vehicle body when passing thro-ugh the curve. Through this control method, the dynamic performance of formation vehicles passing through small radius curve lines can be optimized.

Sensitivity of Mass Geometry Parameters on E-Scooter Comfort: Design Guide.

E-scooter vibrations are a problem recently studied. Theoretical models based on dynamic simulations and also real measurements have confirmed the high impact of e-scooter vibrations on driver comfort and health. Some authors recommend improving e-scooter damping systems, including tyres. However, it has not been suggested nor has any research been published studying how to improve e-scooter frame design for reducing driver vibrations and improving comfort. In this paper, we have modelled a real e-scooter to have a reference. Then, we have developed a multibody dynamic model for running dynamic simulations studying the influence of mass geometry parameters of the e-scooter frame (mass, centre of gravity and inertia moment). Acceleration results have been analysed based on the UNE-2631 standard for obtaining comfort values. Based on results, a qualitative e-scooter frame design guide for mitigating vibrations and increasing the comfort of e-scooter driver has been developed. Some application cases have been running on the multibody dynamic simulation model, finding improvements of comfort levels higher than 9% in comparison with the e-scooter reference model. The dynamic model has been qualitatively validated from real measurements. In addition, a basic sensor proposal and comfort colour scale is proposed for giving feedback to e-scooter drivers.

Study on Lateral Vibration of Tail Coach for High-Speed Train under Unsteady Aerodynamic Loads

As the speed of high-speed trains increases, the vehicle’s lateral stability steadily deteriorates. There have been observations of abnormal vibrations in the tail car, particularly on certain sections of the railway line. This study built a high-speed train aerodynamic simulation model for a three-car consist, and a multibody dynamics simulation model for an eight-car consist based on numerical simulations of train aerodynamics and multibody dynamics. It investigated both steady and unsteady aerodynamic loads, flow field characteristics, and the dynamic performance of vehicles under varied aerodynamic loads at 400 km/h. The results indicate that the aerodynamic loads generated during high-speed train operation exhibit highly unsteady characteristics. Steady aerodynamic loads have a relatively minor impact on the vehicle’s dynamic performance, whereas unsteady loads exert a more significant influence. Under unsteady aerodynamic forces, the tail car experiences severe lateral vibrations. The lateral stability index, displacement, velocity, and acceleration of the tail car under unsteady conditions were measured at 2.26, 7.54 mm, and 0.53 m/s2, respectively. These values represent increases of over 17.71%, 148.84%, and 111.24%, respectively, compared to the steady loads. Large oscillation amplitudes result in more significant lateral displacements and accelerations of the vehicle. This phenomenon is a crucial factor contributing to the “tail swing” effect observed in high-speed trains. This study emphasizes the importance of considering unsteady aerodynamic effects in assessing the lateral stability of high-speed trains and highlights the significance of mitigating the adverse impacts of such dynamic responses, particularly in the tail car.

A transfer learning-based method for marine machinery diagnosis with small samples in noisy environments

The operating conditions of marine machinery are demanding, and their operational state significantly affects the safety of marine structures. Detecting faults is crucial for machinery health management and necessitates a highly precise diagnostic method. In this paper, we propose a fault diagnosis framework that employs transfer learning and dynamics simulation. A denoising convolutional autoencoder is used to reduce noise when monitoring vibration data in marine environments. To address the challenge of limited sample sizes in marine machinery fault data, a multibody dynamics simulation model is developed to acquire data under fault conditions. The fault features are extracted using a convolutional neural network model. Parameter transfer is applied to enhance the accuracy of fault diagnosis. The effectiveness and applicability of the framework are demonstrated through a case study of a bearing fault dataset.

Machine learning-based rail corrugation recognition: a metro vehicle response and noise perspective.

Rail corrugation is a common problemin metro lines, and its efficient recognition is always an issue worth studying. To recognize the wavelength and amplitude of rail corrugation, a particle probabilistic neural network (PPNN) algorithm is developed. The PPNN is incorporated with the particle swarm optimization algorithm and the probabilistic neural network. On the basis ofthe above, the in-vehicle noise characteristics measured in the field are used to recognize normal rail wavelengths of 30 and 50 mm. A stepwise moving window search algorithm suitable for selecting features with a fixed order was developed to select in-vehicle noise features. Sound pressure levels at 400, 500, 630 and 800 Hz of in-vehicle noise are fed into the PPNN, and the average accuracy can reach 96.43%. The bogie acceleration characteristics calculated by the multi-body dynamics simulation model are used to recognize normal rail amplitudes of 0.1 and 0.2 mm. The bogie acceleration is decomposed by the complete ensemble empirical mode decomposition with adaptive noise, and a reconstructional signal is obtained. The energy entropy of the reconstructional signal is fed into the PPNN, and the average accuracy can reach 95.40%. This article is part of the theme issue 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.

Power Compensation Strategy and Experiment of Large Seedling Tree Planter Based on Energy Storage Flywheel

The intermittent hole-digging tree-planting machine shows a periodic short-time peak load law in planting operation, and the operation process is “idling” for small loads most of the time, leading to large torque fluctuations in the transmission system, unscientific power matching, and high energy consumption. To solve the above problems, this article proposes to use a series of energy-saving flywheels in the transmission system of the tree planting machine. On the premise of obtaining holes that meet the target young tree planting requirements, the optimal power compensation strategy for the flywheel system of the tree planting machine is studied to reduce torque fluctuations in the power transmission system, use smaller power drive units, and save energy. Firstly, the nonlinear multi-body dynamics simulation model of soil cutting by the hole-digging component is established. The boundary and contact conditions are set to simulate the power consumption of the hole-digging component at three rotating speeds. Based on the simulation results, the flywheel power compensation strategy is discussed, and the torque fluctuation of the flywheel balance system is analyzed. The results showed that the higher the speed, the greater the power consumption. The power value suddenly increased from 17.82 kW (1.28 s) to 27.93 kW (1.43 s) when the speed was 220 r/min. Then, the power value rapidly decreased, and the power consumption presented a short-term peak feature. The transmission system’s maximum input power is determined as 17.82 kW according to the various simulated power consumption characteristics. The part exceeding the power consumption is compensated by the energy storage flywheel. The total compensation energy was 2382.5 J. After the flywheel system was involved, the maximum output power of the tractor power output shaft decreased by 36.2%, and the peak torque decreased from 445.7 N·m to 285.1 N·m. The power consumption obtained from the field test and simulation was similar, but the energy required to overcome peak load was jointly provided by the flywheel and the engine. The actual input power of the power output shaft during the energy release period of the flywheel system was 18.51 kW when the rotating speed of the hole-digging component was 220 r/min, and the relative error with the simulation value was 2.43%. The measured actual speed reduction of the flywheel system was 8.9%. After installing an energy storage flywheel in the transmission system of the tree planting machine, the output power of the power unit can be stabilized. Tree planting machines can be equipped with smaller power units, which can reduce energy consumption and exhaust emissions.

Rollover Stability of Heavy-Duty AGVs in Turns Considering Variation in Friction Coefficient

This study analysed the impact of turning rate, the centre of mass height, and road adhesion coefficient on the rollover stability of heavy-duty automated guided vehicles (AGVs) using a multi-body dynamics simulation model. The lateral deflection angle of the centre of mass was used as a metric to evaluate the rollover behaviour of the AGVs, and the results were obtained quantitatively. The findings showed that the turning rate had the largest impact on AGV rollover stability, followed by the centre of mass height, while the road adhesion coefficient had the least impact. Despite having the lowest impact, the road adhesion coefficient was one of the key factors contributing to AGV slippage, and severe slippage could easily lead to rollover incidents. To further evaluate the rollover behaviour of the AGVs, a lateral-load transfer rate (LTR) index was derived from the change in wheel load generated by the lateral tilt angle during steering. The range of LTR values was determined for different ranges of turning rate, the centre of mass height, and road adhesion coefficient. The results indicated that the range of LTR values for turning rate was 0.23–0.45, for the centre of mass height was 0.323–0.393, and the minimum value of 0.337 was obtained for a road adhesion coefficient of 0.6.

A Control Algorithm of Active Wave Compensation System Based on the Stewart Platform

Aim at the actual engineering requirements of wind power operation and maintenance under complex sea conditions, a control method of the active wave compensation system for maintenance ships based on the Stewart platform is presented. The kinematics of the platform is analyzed, and the coordinate transformation, pose, and inverse solutions are analyzed and calculated. The multi-body dynamics simulation model is established by using MATLAB. For the problem of the load nonlinearity and strong coupling of the nonlinear Stewart platform, an active wave compensation active disturbance rejection control (ADRC) is built to attain the high-precision control of the six-degree-of-freedom (6-DOF) Stewart platform. The numerical simulation shows that the proposed control scheme has good tracking accuracy and strong anti-interference ability.

Research on intelligent formation operation performance of straddle-type rapid transit vehicles in heterogeneous operating environment

This paper presents an intelligent formation operation mode (IFOM) based on straddle-type rapid transit vehicles. Taking the straddle-type rapid transit vehicles operating in IFOM as the object, the operation mode of the vehicle is defined in the control system architecture of the straddle-type rapid transit system. In addition, considering the heterogeneous operating environ-ment of formation vehicles, an evaluation index system for formation vehicles is proposed. Then, according to the vehicle longitudinal dynamics model and the artificial potential field formation algorithm, we build the formation vehicle operation controller. After that, referring to the vehicle dynamics model, a multi rigid body dynamics simulation model of formation vehicles in a heterogeneous operating environment is established. Finally, the operating performance of formation vehicles in heterogeneous operating environment is analyzed. The analysis results show that the operation performance of the formation vehicle meets the requirements of the evaluation index system, which proves the feasibility of the formation operation of straddle-type rapid transit vehicles operating in IFOM.

Determining the structural life of an electric vehicle battery from road loads

Abstract Although the electrical system is important in the development of electric vehicles, the durability of the battery system against mechanical loads and the performance of the battery against shock reactions are just as important. The objective of this study is to develop a methodology to determine the structural life of the battery of the C-platform sports utility vehicle (SUV). For this purpose, a power spectral density (PSD) durability test profile is generated and compared to battery test standards such as ISO 6469:2019, AK-LH 5.21 and SAE J2380. Analytical Virtual Proving Ground (VPG), a multibody dynamics simulation model, is also developed and correlated to test data. The results show that FDS values for AK-LH is higher than the fatigue damage of the collected vehicle data, while the FDS results for ISO standard are lower compared to the vehicle data. The results also indicate that the loads in the longitudinal (x-direction) and lateral (y-direction) directions are different. Therefore, loads of different amplitudes should be used for these directions, contrary to SAE J2380 and USABC standards. Finally, it is concluded that the VPG model can be used for determining the fatigue life when there is no test data, thanks to its high accuracy.

Coordination and matching of tire system of new straddle-type rapid transit vehicle

Under the trend of promoting economy, environmental protection and high efficiency in the urban rail transit industry, this paper proposes a new type of straddle-type rapid transit system. Compared with most straddle-type monorail systems, it has the advantages of low construction cost and low operating cost, which makes it more suitable for urban rail transit system in small and medium-sized cities. In the process of vehicle development and design, in order to achieve the coordination and matching of tire systems and reduce the wear of tire systems, this work uses a multi-objective optimisation method to reduce the guiding torque of each tire system when the vehicle passes through the curve. Based on the vehicle dynamics model, the multi-body dynamics simulation model of the vehicle is established. The guiding torque of each tire system is taken as the optimisation objective, and the position and dynamic parameters of each tire system are taken as the optimisation parameter. Based on the NSGA-II algorithm, the ISIGHT and SIMPACK software are used for co-simulation. Finally, the guiding torque of each tire system is effectively reduced, and the coordination and matching of tire system is realised.

Vibration Analysis and Control of the Suspension System of the Drum Washing Machine by Applying SMA

The suspension system of the drum washing machine is the object of study. To reduce the vibration of drum washing machines during high-speed dehydration, a shape memory alloy is proposed to be used to make suspension spring. The spring stiffness can be controlled according to the characteristic that the elastic modulus of SMA varies with temperature to achieve damping effect. The mathematical model and multi-body dynamics simulation model are established for the suspension system of the drum washing machine, the vibration generation mechanism of the drum washing machine and the SMA active vibration control principle are analyzed, and the vibration control effect of the SMA suspension spring is studied for different speed simulations. The results show that the SMA variable stiffness suspension spring has a significant vibration control effect compared with the spring of general material.

Development of multi-body dynamics simulation model of agricultural 4WD electric vehicle platform for upland farming

Development of multi-body dynamics simulation model of agricultural 4WD electric vehicle platform for upland farming

Building a multibody dynamics simulation model of railway vehicle considering wheel slide re-adhesion control

The contact between wheel and rail of railway has a strong influence on the running safety. But under the wet condition, adhesion coefficient between wheel and rail decease, and skid may occur when railway vehicle is breaking. This is a serious safety risk to the operation of vehicle. Therefore, many research to reveal the adhesion between wheel and rail have been performed. In this paper, we built a multibody dynamics simulation model of railway vehicle considering wheel slide re-adhesion control using Simpack, in order to study on the best way of breaking of railway vehicle under wet condition reflecting the previous research results. In addition, breaking simulation under low adhesion coefficient condition was performed using the simulation model with wheel slide re-adhesion control.