Multibody Vehicle Model Research Articles

Dynamic Load Analysis of Mine-Truck Using Multibody Dynamic Analysis Method

Abstract: Vehicle load distributed on front & rear axle assembly during various working conditions is one of the most important factors influencing working performance and service life of drive axle assembly. The dynamic load on axle assembly is higher compared to the rated load because of variations in vehicle speed and road surface conditions. Early failure of structural components is caused because of higher dynamic reaction forces due to uneven road profiles. The dynamic load calculation of axle assembly is presented in this paper for a Mine-truck with various road conditions and vehicle speeds. The road load conditions consist of grade, bump & path hole. Mine-truck with payload capacities of 63 Ton is considered for the study. The behaviour of vertical force is calculated for different vehicle speeds (3 - 12 km/hr.) of the machine on the front & rear axle assembly during running conditions. Multi-body dynamic Analysis tool ADAMS is used for this study. ADAMS helps to study the dynamics of moving parts and load distribution throughout mechanical systems during motion. The Mine-truck3D model was created with the help of computer-aided design (CAD) software. Major units of Mine trucks are considered to prepare 3D models like Cabin-engine mass, Bucket, front axle assembly, rear Axle assembly & tires. Multi-body vehicle models are prepared in simulation software ADAMS by importing 3D models prepared by computer-aided design (CAD) software. This provides guidelines for selecting dynamic load factors while designing structural parts of the vehicle.

Integration of brake block thermal equations within a railway vehicle multibody model: a multiphysics approach

ABSTRACT The paper shows the development of a finite-difference (FD) railway brake block thermal model and its integration within the multibody (MB) formalism of the Simpack commercial code. The block nodal temperatures are included among the dynamic states computed by the MB solver, through the definition of a user-defined force element, which determines the braking torque based on the applied brake cylinder pressure. The proposed approach overcomes the main limitations of existing detailed railway vehicle models, which solve the thermal and vehicle dynamics equations in different computational environments. Furthermore, the new strategy can thrust the development of models able to account for the coupling between the wheel and block thermal behaviour and the whole vehicle dynamics. Preliminary simulations of drag and stop braking operations of a reference European freight waggon prove that the proposed model is able to effectively consider the main heat fluxes and nonlinearities involved in tread braking operations.

PEM-based random vibration analysis under service-braking conditions on an irregular track

PurposeAccording to relevant research, non-uniform speed has a significant impact on the vehicle-track systems. Up to now, research work on it is still very limited. In this paper, the PEM is adopted to further transform it into a deterministic process to solve the vehicle’s problem of running at a non-uniform speed.Design/methodology/approachThe multi-body vehicle model has 10 degrees of freedom and the track is regarded as a finite long beam supported by lumped sleepers and ballast blocks. They are connected via linear Hertz springs. The vertical track irregularity is a Gaussian stationary process in the space domain. It is transformed into a uniformly modulated nonstationary random process in the time domain with respect to the non-uniform vehicle speed. By solving the equation of motion of the coupled vehicle-track system with the pseudo-excitation method, the pseudo-response and consequently the power spectral density and the standard deviation of the structural response can be obtained.FindingsTwo kinds of vehicle braking programs are taken in the numerical example and some beneficial conclusions are drawn.Originality/valueThe pseudo-excitation method (PEM) was used to perform the random vibration analysis of a coupled non-uniform speed vehicle-track system. Transforming the track irregularity into a uniformly modulated nonstationary random process in time domain with respect to the non-uniform vehicle speed was undertaken. The pseudo-response of the coupled system is solved by applying the Newmark algorithm with constant space integral steps. The random vibration transfer mechanism of the coupled system is fully discussed.

Parameter identification of multibody vehicle models using neural networks

Parameter identification of multibody vehicle models using neural networks

The random dynamic performances of EMUs with polygonal damages

Polygonalization is a typical non-uniform wear phenomenon that affects the performance and comfort of the vehicle/track system. Therefore, the vehicle system performance could be strictly troubled by polygonal damage close to the wheel circumference at the wheel/rail contact. A 3D vehicle/track an EMU type train consisting of 8 coupled vehicles model has been established. The coupled model car body and bogie frame are considered rigid and integrated with the flexible wheelset, rail, and slab track to investigate the elastic deformation caused by the impact load induced by the wheel polygonalization. The flexible track can be incorporated into the multi-body vehicle model using the movable reference frame formulation. Uncertainty parameters are presented, such as passenger weight, wind force, coefficient friction, and suspension variation. The proposed research is validated based on the existing research work and shows excellent agreement. The simulation result deliberated the vertical wheel-rail force, wheelset acceleration, rail acceleration, rail displacement, and slab track acceleration. The results of this study show that as the wheel polygonal damage amplitude increase, the value of wheel/rail normal forces and the dynamic vibrational response of the wheelset axle increase. Additionally, polygonal wear-induced impact stresses may cause the wheelset axle to resonate. When wheel polygonal damage amplitude and uncertainty parameters are corporate into the system dynamics, the maximum magnitude of the wheelset, rail, and slab track acceleration increases. Besides, the train failure degree is comparable to the polygonised wheel harmonic order, defect parameters, and amplitude of out-of-roundness.

Minimum-Lap-Time Planning of Multibody Vehicle Models via the Articulated-Body Algorithm

Minimum lap-time planning (MLTP) is a well-established problem in the race car industry to provide guidelines for drivers and optimize the vehicle’s setup. In this paper, we tackle the 3D nature of the problem in its full extension, making no simplifying assumptions on the mechanics of the system. We propose a multibody vehicle model, described by rigorous dynamical equations. To effectively handle the resulting complexity, we devised an efficient direct dynamics computational method based on Featherstone’s articulated-body algorithm (ABA). To solve the MLTP, we employed a direct-collocation technique, discretizing the problem so that all information of the 3D track is pre-processed and directly embedded into the discrete problem. This discretization approach turns out to be perfectly compatible with our vehicle model, leading to a solution in accessible computational time frames. The high level of detail of the model makes the proposed approach most useful for in-depth vehicle dynamics analyses on complex tracks. To substantiate the analysis, we provide a comparison with the results obtained by a double-track model on the Nürburgring Nordschleife circuit. Consistently with the average trend defined by the double track, the proposed model features a more dynamically rich behavior, realistically capturing the higher-order effects elicited by the sharp corners and the highly variable slope of the track.

A semi-analytical method for predicting train-induced vibrations considering train-track-soil and soil-pile-building dynamic interactions

A semi-analytical methodology was proposed to predict vibrations considering train-track-soil and soil-pile-building coupling. It contained three subsystems of vehicle-track-soil generation, ground-borne vibration propagation, and soil-pile-building dynamic interaction. The vibration generation was simulated with a 10-degree-of-freedom multi-body vehicle model and a three-layer track model, including the soil dynamics through the predicted complex stiffness from the layered soil under surface traction. An equivalent uniform pressure under each bogie was obtained which subsequently helped formulate the ground-borne vibration transmission model. Finally, the soil-pile-building dynamic interaction was established using the double Fourier transform and impedance method, with inputs from previously predicted free field motion. The methodology was applied to a case study where train-induced vibration predictions at the ground surface and column bases were compared with corresponding field measurements, through which it was demonstrated to have good prediction accuracy. Varied pile and building configurations were subsequently investigated through the parametric study to unveil the complex influence factors and demonstrate the applicability of the proposed method to different scenarios.

Real-Time Modeling of Vehicle’s Longitudinal-Vertical Dynamics in ADAS Applications

The selection of an appropriate method for modeling vehicle dynamics heavily depends on the application. Due to the absence of human intervention, the demand for an accurate and real-time model of vehicle dynamics for intelligent control increases for autonomous vehicles. This paper develops a multibody vehicle model for longitudinal-vertical dynamics applicable to advanced driver assistance (ADAS) applications. The dynamic properties of the chassis, suspension, and tires are considered and modeled, which results in accurate vehicle dynamics and states. Unlike the vehicle dynamics models built into commercial software packages, such as ADAMS and CarSim, the proposed nonlinear dynamics model poses the equations of motion using a subset of relative coordinates. Therefore, the real-time simulation is conducted to improve riding performance and transportation safety. First, a vehicle system is modeled using a semi-recursive multibody dynamics formulation, and the vehicle kinematics and dynamics are accurately calculated using the system tree-topology. Second, a fork-arm removal technique based on the rod-removal technique is proposed to reduce the number of bodies, relative coordinates, and equations constrained by loop-closure. This increase the computational efficiency even further. Third, the dynamic simulations of the vehicle are performed on bumpy and sloping roads. The accuracy and efficiency of the numerical results are compared to the reference data. The comparative results demonstrate that the proposed vehicle model is effective. This efficient model can be utilized for the intelligent control of vehicle ADAS applications, such as forward collision avoidance, adaptive cruise control, and platooning.

Phase plane analysis applied to non-explicit multibody vehicle models

A new methodology for constructing stability maps (phase-plane analysis) is presented and validated for application to complex multibody vehicle models implemented in Multibody Dynamics simulation software (Adams®). Traditional methodologies are developed to be applied to explicit mathematical models. Given the complexity of some special multibody systems, particularly in vehicle dynamics, simplifications are needed to apply this stability analysis technique. The main limitation when using simplified models is the need to neglect components which could have a significant influence on the dynamic behavior of the system and therefore on its stability. In the proposed methodology it is not necessary to have access to explicit mathematical models of multibody systems. Thus, the stability map of a vehicle model can be constructed by considering highly nonlinear dynamic elements, such as tires and silent-blocks components, modeled using the nonlinear finite element technique.

Control strategy for vibration suppression of a vehicle multibody system on a bumpy road

The demand of accurate and real-time dynamics model has recently become critical for implementing effective vibration control in vehicles. The multibody dynamics method provides an appealing alternative for accurate modelling of closed-loop vehicles. In this work, vibration-suppression strategies for a vehicle traversing a bumpy road are proposed, which use a semi-recursive multibody model and a series of control algorithms. First, a 17-degree-of-freedom vehicle is modelled using a semi-recursive multibody method to perform real-time simulation. The vehicle multibody model is verified by using the results from a commercial software package. Second, the PID, fuzzy, and optimal control algorithms are tailored using the obtained vehicle states for vibration suppression. By applying different initial speeds and driving torques, the simulations of the vehicle traversing the bumpy road are performed. The results show that the controllers effectively suppress the vehicle’s vibration, and the optimal controller has the best performance. Furthermore, the effect of mass uncertainty on vibration-suppression is discussed. Numerical experiments are performed to verify the effectiveness of the optimal control strategy. The vibration-suppression method based on the vehicle multibody model and the optimal control algorithm can be used to improve the ride comfort in worse road conditions.

EVs on Road Ground-Impact Energy Evaluation Methodology: Dynamic of a Finite Element (FE)-Based Battery Pack Integrated into Full Vehicle Multi-Body Model on Abaqus

<div class="section abstract"><div class="htmlview paragraph">The present paper documents a comprehensive study on the ground-impact of battery packs in Electric Vehicles (EVs), a paramount concern for vehicle manufacturers. During an accidental crash, battery packs are usually exposed dangerously to possible intrusion of foreign objects (e.g., road debris). With the purpose of developing a generic methodology to evaluate the released energy content and due to high nonlinearities involved during the ground-impact maneuvers, a hybrid full vehicle model is needed. Hence, both FE-based battery case and virtual energy sensors have been integrated into the current Abaqus multi-body (MB) full vehicle model (suspensions, steering system, engine and a trimmed body). Energy peaks are estimated simulating a vehicle going over obstacles that a typical customer can encounter in daily-life (no off-normal situations) performed at different approaching speeds and obstacle sizes.</div><div class="htmlview paragraph">To evaluate the energy, the battery plate is divided as if it were a spaced grid of identical square-sized modules. Plate surface modularization is useful to install properly a certain amount of virtual sensors that store and measure the energy released during the impact. In addition, this strategic layout promotes the accuracy of the contact conditions between obstacles and the battery case.</div><div class="htmlview paragraph">The concept underlying the proposed multidisciplinary sequential procedure, based on three different phases (on road-impact energy evaluation, load cases definition and battery case/mechanical structure strength), ensures both to define specification for subsequent analyses (making iterations on the structure faster) and to possibly complete an effective design validation of the specific vehicle project under test. This methodology has been successfully applied transversally to several vehicle architectures (e.g., light commercial vehicles, sport/compact utility vehicles, supercars) and it shows the benefits of choosing the integration strategy over a typical co-simulation approach.</div></div>

Numerical Modeling of Wear on Powered Railway Wheelset Under Various Operating Conditions

Wheel wear prediction is a high priority in rolling stock research since it has a significant influence on performance, maintenance, and safety risks. It is crucial for the planning of reprofiling and replacement operations, estimating residual life, and managing the wheels supply chain. The evolution of wheel profile due to wear is a critical and complex issue strongly depending on operating conditions. In this work, a numerical modeling process, based on a multi-body modeling approach for wheel wear prediction, is presented and applied to a locomotive designed to operate in various operational situations. The modeling methodology includes track and vehicle multi-body model, wheel-rail contact solving with Hertz and FASTSIM models and wear computation using Archard model. Numerical simulations have been performed for different operating configurations in order to evaluate the influence of rail profile, track curves, and operating speed on volume and depth distribution of wheel wear in locomotive’s powered wheelset. The results show that the UIC60 rail profile is significantly better than the AREMA profile for wheels with the S1002 profile. It has been also found out that both increasing the speed and reducing the radius of curvature increase wheel wear.

An efficient prediction model for vibrations induced by underground railway traffic and experimental validation

This study proposes an efficient prediction model for the vibration generated by underground railways. The proposed model is based on an analytical approach for a tunnel in a horizontally multi-layered half-space, showing the advantage of high computational efficiency and accuracy. Three alternative modelling strategies regarding hypotheses about the cross-section behavior of the slab and the connection condition between the slab and tunnel are introduced. A multi-body vehicle model is subsequently coupled with the track-tunnel-ground system in the moving frame of reference to determine the train-induced vibration. The predicted vibrations on the track, tunnel, and ground surface induced by the passage of trains are compared with the measured vibrations from an underground railway line in London from the literature. The predicted results for the double-beam track model with uniform support and the continuum track model exhibit a good agreement with the site measurements. The cross-section deformation of the track can be ignored and has little influence on the responses of the tunnel and ground. However, the assumption of the one-line connection between the slab and tunnel results in an overestimation of the track vibration, up to 20 dB, and an underestimation of the tunnel and ground vibration, up to 10 dB.

A Screw-Axis Approach to the Stability of Two-Wheeled Vehicles

The stability of two-wheeled vehicles is predominantly characterized by the well-known weave and wobble vibration modes, which have been extensively investigated in the literature, mainly in terms of their frequencies and damping ratios. In this work the focus is towards their mode shapes, which are investigated using the screw-axis (also called Mozzi-axis), instead of the classic compass diagrams, for a better understanding of their three-dimensional patterns. The analysis is then carried out using the velocity centres for a characterization from the top, rear and side view of the vehicle. The multibody vehicle model employed for the numerical analysis is built in Adams. The dataset resembles that of a 250cc sport motorcycle, and has been derived from laboratory tests. The stability analysis is carried out in the frequency domain. It is found that, depending on the selected plane for the projection of the three-dimensional vibration motion, the trajectories of the velocity centres of the weave and wobble can cross either aft or fore the centre of mass, which has been associated to the under- and over-steering behaviour in the literature.

Performance of leaf spring suspended axles in model approaches of different complexities

Axles with leaf spring suspension systems are still a popular choice in many commercial vehicles. However, leaf springs are not in perfect conformity to standard multibody vehicle models because they combine guidance and suspension in one single element. Combining standard multibody vehicle models with sophisticated finite element leaf spring models results in rather complex and computing time-consuming solutions. Purely kinematic models, defined by lookup tables or the design kinematics approach, cover only some but not all features of the leaf spring suspension. As shown here, the five-link model, which incorporates a quasi-static solution of the leaf spring compliance, provides a very practical model. It is comparatively lean and provides results of sufficient accuracy in the whole application range.

Data-driven vehicle modeling of longitudinal dynamics based on a multibody model and deep neural networks

The vehicle dynamics simulation and preview control require a dedicated vehicle model, such as multibody dynamics model. However, the multibody model has higher computational complexity which affects the response time of the vehicle controller. This issue can be alleviated by using a data-driven vehicle dynamics model due to its effective generalization and computational speed. In this work, we propose a data-driven modeling approach based on deep neural networks (DNNs) for computing and predicting the vehicle characteristics. The high-fidelity simulations of a validated vehicle multibody model are performed for data acquisition. This data is then used for training and testing the proposed model. The DNN inputs comprise the initial speed of the vehicle and the torque applied on front wheels to imitate vehicle acceleration and deceleration. The DNN outputs comprise the driving distance and the longitudinal velocity of the vehicle. The dynamics characteristics resulting from both the data-driven model and the multibody model are investigated and compared. Furthermore, the accuracy of the data-driven model is analyzed in terms of various error functions. The data-driven model is verified by using the results obtained from a commercial software package. The simulation results show that the data-driven vehicle model predicts the accurate velocity and driving distance in real-time. The data-driven model can be used for real-time simulation and preview control in autonomous vehicles.

Parameter optimization for a vibration attenuation system on ambulance stretchers

In this work a parameter optimization method is applied to determine the best values of damping and stiffness properties which will minimize the magnitude of the vertical acceleration of the ambulance stretcher. Thus, an 8-DOF vehicle dynamic model was developed to be used for the parameter optimization method. Subsequently, the results obtained by the model were compared to a full vehicle multi-body model of Carsim software. Damping and stiffness properties, which are obtained by a parameter optimization method, contribute to reducing the magnitude of the vertical acceleration of the ambulance stretcher. The approach developed in this study provides sources for designing a mechanism to reduce the vertical acceleration to which the patient is exposed during transportation in an ambulance.

State, parameter and input observers based on multibody models and Kalman filters for vehicle dynamics

The aim of this work is to present a novel accurate estimator for vehicle dynamics. Following the multibody dynamics approach, a vehicle can be modeled with a high level of detail including non-linear dynamics. As a consequence, a rich simulation data-set is available for engineering analysis, richer than with vehicle analytical models.The proposed novel estimator is a new form of a dual Kalman filter. The first filter uses an indirect extended Kalman filter (i.e. the errorEKF) incorporating force estimation and using a vehicle multibody model. The second filter is an unscented Kalman filter (UKF) used to increase the accuracy of the errorEKF by estimating uncertain modeling parameters such as the mass of the vehicle and the tire-road friction coefficient.The performance of the proposed state-parameter-input (SPI) observer is tested in a simulation environment. The performance of the observer is demonstrated using two maneuvers, out of which one covers aggressive driving conditions. The results show that the new observer estimates with high accuracy the variables of interest for vehicle dynamics, such as the tire forces.

Research on Cab Vibration Control Based on Parameter Hierarchical Interaction Model

The vibration level of a cab affects the passenger’s ride comfort and safety significantly. It is of great importance to control the vibration level of cabs under various driving conditions. The associated vibration transfer paths of cabs are studied by using a hierarchical analysis method of a parameter index. The multiobjective design analysis is carried out by using the multiparameter joint optimisation design. Further, the optimal control of the cab vibration level is obtained from a full-condition simulation environment. Additionally, a multibody vehicle model is established. The simulation analysis under multiple working conditions is conducted. The optimal parameter distribution of the cab mounting structure was established by analysing the influence of the design parameters and experimental verification. This greatly improves the comfort of the cab.

Evaluation of injury thresholds for predicting severe head injuries in vulnerable road users resulting from ground impact via detailed accident reconstructions.

The aim of this study was to evaluate the effectiveness of various head injury criteria and associated risk functions in prediction of vulnerable road users (VRUs) severe head injuries caused by ground impact during vehicle collisions. Ten VRU accidents with video information were reconstructed by using Chalmers Pedestrian Model, vehicle multi-body system models and the THUMS (Ver. 4.0.2) finite element model. The head kinematics were used to calculate injury risks for seven head kinematics-based criteria: head angular velocity and acceleration, linear acceleration, head injury criterion (HIC), head impact power (HIP) and two versions of brain injury criterion (i.e., BRIC and BrIC). In addition, the intracranial responses were used to estimate seven tissue injury criteria, Von Mises stress, shear stress, coup pressure (C.P.) and countercoup pressure (CC.P.), maximum principal strain (MPS), cumulative strain damage measure (CSDM), and dilatation damage measure (DDM). A review of the medical reports for all cases indicated that each individual suffered severe head injuries and died. The injury risks predicted through simulations were compared to the head injuries recorded in the medical or forensic reports. The results indicated that 75-100% of the reconstructed ground impact accidents injuries were correctly predicted by angular acceleration, linear acceleration, HIC, C.P., MPS and CSDM0.15. Shear stress, CC.P. and CSDM0.25 correctly predicted 50-75% of the reconstructed accidents injuries. For angular velocity, HIP, BRIC and BrIC, the injuries were correctly predicted for less than 50% of the reconstructed accidents. The Von Mises stress and DDM did not correctly predict any reconstructed accidents injuries. The results could help to understand the effectiveness of the brain injury criteria for future head injury evaluation.