Vehicle Dynamics Simulation Research Articles

Optimizing vehicle dynamics co-simulation performance by introducing mesoscopic traffic simulation

Microscopic traffic simulation is often used in conjunction with vehicle dynamics simulation to test cooperative or perception-based driver assistance functions. On the other hand, visualization and the interaction of a large number of swarm vehicles is computationally burdensome, limiting the size of scenarios. To remedy this problem, this paper introduces a mesoscopic traffic model, namely the extension of the shockwave profile model to road networks, that handles traffic as continuous flows of vehicles. Adopting the idea of level of detail from computer graphics, the modeling of swarm vehicles is carried out in less detail farther away from the EGO vehicle. These levels are defined using the classical (macroscopic, mesoscopic, and microscopic) categorization of traffic modeling. The macroscopic traffic model is responsible for the traffic demand and traffic assignment. The proposed mesoscopic model is capable of capturing the fluctuating nature of traffic on lane level. Closer to the EGO vehicle microscopic traffic simulation is employed while the EGO vehicle is modeled in full-detail including vehicle dynamics too. The 3D rendering of the simulation is performed by the vehicle dynamics simulator. The challenge in the proposed methodology is transitioning between the mesoscopic and the microscopic models, i.e., selecting the boundary and spawning/destroying vehicle agents. The paper addresses this challenge with a linear (w.r.t. the vehicle number) time complexity algorithm. Practically, a dynamic downscaling of the microscopic simulation to mesoscopic level is realized outside the vicinity of the EGO vehicle. The proposed methodology is generic, and can be adapted to most existing vehicle dynamics and microscopic traffic simulator software. The solution is tested with SUMO as microsimulation and Carla as vehicle dynamics simulation through a simple path following test case in two scenarios: a congested residential area and a complex scenario with both a highway section and an urban area. Simulation results suggest that the simulation performance could be improved by 200–500% while retaining modeling accuracy, compared to the case when only microscopic simulation is used.

Measurement and Modeling of a Cargo Bicycle Tire for Vehicle Dynamics Simulation

In the field of inner-city cargo transportation, solutions such as electrified cargo trailers are increasingly being used. To provide an intelligent drivetrain control system that improves driving dynamics and enables safety, it is necessary to know the characteristics of the trailer system. This includes the behavior of the tires. Existing investigations of bicycle tires focus on camber-angle-dependent models. However, in most trailers, a rigid mounting of the tires without camber is used. For this reason, a bicycle tire model is created within the scope of this study using real measurement data that represent a 20 in tire with typical wheel loads and without camber. The measurements were collected with the mobile tire measurement laboratory of the Bern University of Applied Sciences on an asphalt test site under real conditions. Crosstalk occurring in the measurement hub during the data collection was successfully corrected using a matrix method. With help of the so-called Magic Formula, a tire model was created that can be used for driving dynamics simulations and controller design.

High-Fidelity Dynamics Modelling for the Design of a High-Altitude Supersonic Sounding Rocket

The accurate modelling and simulation of vehicle dynamics is a fundamental prerequisite for the design and experimental flight testing of aerospace vehicles. In the case of high-altitude supersonic sounding rockets, it is critically important to produce realistic trajectory predictions in a representative range of operational and environmental conditions as well as to produce reliable probability distributions of terminal locations. This article proposes a methodology to develop high-fidelity flight dynamics models that accurately capture aeroelastic, turbulence, atmospheric and other effects relevant to sounding rockets. The significance of establishing a high-fidelity model and of addressing such a problem in the context of developing a digital twin are discussed upfront, together with the key tools utilised in the analysis. In addition to state-of-the-art computational methods to determine the aerodynamic forces, moments and mass changes in various flight regimes (including parachute release), a detailed methodology for incorporating the dynamic aeroelastic response of the rocket is presented. The validity of the proposed method is demonstrated through a simulation case study, which utilises data from an existing rocket prototype. Results corroborate the correct implementation of the proposed algorithms and provide foundations for future research on virtual sensing and digital twin for autonomous navigation and guidance.

Safety Comparison of Simple and Spiral Horizontal Curves Based on Side Friction Factor Dynamic Modeling

A horizontal curve’s geometric design is considered an important factor in highway accidents, and simple and spiral curves are regarded as the most common types of horizontal curves. Various factors affect the safety of horizontal curves, one of the most important of which is the side friction factor in the horizontal curves. Therefore, in this study, the safety of simple and spiral horizontal curves was investigated for the E-class sedan, E-class SUV, and two-axle conventional truck based on the side friction factor. In this regard, CarSim and TruckSim vehicle dynamic simulation software were utilized using 360 scenarios, including vehicle speed, vehicle type, curve radius, and road geometry. It was revealed that the maximum side friction factor for all vehicles in the simple horizontal curve was higher than the spiral horizontal curve. Also, the process of increasing the side friction factor was carried out with a gentler slope in the spiral horizontal curve. Except for the radius of 0.7 times the maximum radius of the spiral horizontal curve (R) for the truck and the radii of 0.7 R and 0.9 R for the sedan and SUV, the maximum side friction factor in simple and spiral horizontal curves was lower than the AASHTO recommended values, which shows that the spiral horizontal curve was better and safer compared to the simple horizontal curve based on the side friction factor.

Impact of combined alignments and adverse weather conditions on vehicle skidding

Roadways in Wyoming are characterized by challenging horizontal profiles, vertical profiles, a combination of the two and adverse weather conditions, all of which affect vehicle stability. In this study, we investigated the impact of different operating speeds when negotiating combined horizontal and vertical curves under unfavorable environmental conditions on Wyoming's interstates via vehicle dynamics simulation software. The simulation tools provided the acting forces on each tire of the vehicle and the side friction (skidding) margins. This allowed for examining the interaction between vehicle dynamics and road geometry in such alignments. Also, linear regression analysis was implemented to investigate the skidding margins based on the simulation results to demonstrate when a vehicle is more likely to deviate from its desired trajectory. Specifically, this examines the contributing factors that significantly influence the skidding margins. The results indicated that: 1)the skidding margins are dramatically decreased by adverse weather conditions even with lower degree of curvature and gradient values of combined curves and more particularly at higher operating speeds conditions. Increasing the vehicle speed on the curve by 10%, the skidding margin dropped by 15%. 2) Compared to heavy trucks and sports utility vehicles (SUVs), passenger cars require the highest side friction demand. 3) The effect of applying brakes on vehicle stability depends on the road surface condition; applying the brakes on snowy road surfaces increases the potential of vehicle skidding especially for heavy trucks. This study assessed the curve speed limits and showed how important to assign safe and appropriate limits speed since the skidding likelihood is significantly sensitive to the vehicle speeds. This study is beneficial to Wyoming's roadway agencies since hazardous sections having combined horizontal and vertical curves are identified. Also, critical situations that require additional attention from law enforcement agencies are pinpointed. Finally, recommendations that are valuable to roadway agencies are made based on this study's findings.

A modified electromagnetic force calculation method has high accuracy and applicability for EMS maglev vehicle dynamics simulation

The traditional electromagnetic force calculation method does not consider the non-linear magnetization characteristics of the ferromagnetic material or the magnetic resistance in full circuit, resulting in large calculation errors when the electromagnet operation state is far from the rated state, and causing the dynamics simulation results to diverge from the actual situation. A more accurate analytical formula for electromagnetic force is derived based on the full circuit magnetic resistance modification and considering the non-linear magnetization characteristics of ferromagnetic materials. Then combined with the finite element simulation analysis, the magnetic resistance modification (MRM) method is proposed for calculating electromagnetic levitation force and guiding force. This MRM method greatly improves the accuracy of electromagnetic force calculations and provides greater accuracy for EMS maglev vehicle dynamics simulations.

Modeling of a Bicycle Cargo Trailer with Magic Formula Tire Model for Vehicle Dynamics Simulation

Modeling of a Bicycle Cargo Trailer with Magic Formula Tire Model for Vehicle Dynamics Simulation

Agricultural tractor dynamics simulation research based on a driving simulator with real-time human-machine interaction

Vehicle dynamics simulation based on the driving simulator has great application potential. Compared with field tests, it has the advantages of low cost, high reproducibility, safety, and controllability. Compared with commercial dynamics simulation software, it can realize real-time human-machine interaction by providing a highly immersed virtual scene and operational environment. In order to verify the feasibility of agricultural tractor dynamics simulation based on the driving simulator, the dynamics model of 8 degrees of freedom (8DOF) was built using MATLAB/Simulink and Visio Studio, and the human-machine interaction environment composed of the tractor cab, data acquisition system, controller, central server and display system was constructed. Secondly, the simulation software based on the dynamics model was developed based on the virtual reality engine of Unity3D. Finally, Carsim was applied as the feasibility verification tool with similar tractor models and virtual environments. The turning road test, undulating road test, and cross-slope road test were carried out in the driving simulator and Carsim with the same simulation conditions. Yaw rate and roll angle given by both platforms above were analyzed with statistical methods and error analysis. The results showed that dynamics curves of the simulator had high shape similarity with the curves of Carsim. No significant difference was demonstrated between curves of the simulator and Carsim. There was a relative error from 6.34% to 19.63% in yaw rate data from the simulator compared with Carsim results. Likewise, the relative error for roll angle data given by the simulator ranged from 6.12% to 20.72%. The results verified the feasibility of high-accuracy dynamics simulation in the driving simulator. Our research laid the foundation for further research and application of agricultural tractor dynamics simulation based on driving simulators with real-time human-machine interaction.

Online Fault Detection for Four Wheeled Skid Steered UGV Using Neural Network

This paper proposes a neural network-based actuator fault detection scheme for four-wheeled skid-steered unmanned ground vehicles (UGV). The neural network approach is first validated on vehicle dynamics simulations. Then, it is tailored for the experimental setup. Experiments involve a motion tracking system, Husarion Rosbot 2.0 UGV with associated network control systems. For experimental work, the disturbance is intentionally induced by augmenting wheels with a bump. Network size optimization is also carried out so that computing resource is saved without degrading detecting accuracy too much. The resulting network exhibit fault detection and isolation accuracy over 97% of the test data. A scenario is experimentally illustrated where a fault occurs, is detected, and tracking control is modified to continue operation in the presence of an actuator fault.

VALIDATION OF PARAMETRIC OPENDRIVE ROAD SPACE MODELS

Abstract. The standard OpenDRIVE is widely used for exchanging road space models in order to simulate the traffic of a city or individual driving situations. For modeling continuous road courses at lane level, OpenDRIVE utilizes its own parametric geometry model. However, violations of continuity requirements due to geometric leaps or kinks can cause the vehicle dynamics simulation to fail when testing vehicle components. But also defective lane predecessor and successor relations can result in an OpenDRIVE dataset not being usable as a reference map for vehicle navigation. Since these geometric, topological, and semantic constraints go beyond the rules encoded in the schema, this article presents a framework and a first implementation for validating OpenDRIVE datasets. As the lane widths are defined parametrically relative to the reference line of the respective road, lane connectivities at road transitions are evaluated using explicit geometries derived from the parametric geometry representations. Moreover, a derived CityGML representation enables a visual inspection of the parametric models to identify unexpected but visible defects. The implemented framework is applied to examine a total of 99 OpenDRIVE datasets, where significant lane gaps were detected in the explicit representation for about 20% of the datasets.

Measurement System for the Experimental Study and Testing of Electric Motors at the Faculty of Engineering, University of Debrecen

The Faculty of Engineering of the University of Debrecen has a long-standing tradition of developing electric and pneumatic-driven prototype race cars. These vehicles are regular participants in domestic and international university competitions. For more conscious development, thus, for more successful racing, a vehicle dynamics simulation program was developed by our research group. One of the main parts of the above program is the simulation of the drive system, including the electric motor. The input data for the motor simulation programs are the electromagnetic and dynamic characteristics of the motor. Most of these characteristics are usually not specified in the motor catalogue; thus, they have to be measured. In this paper, a detailed description of a recently developed measurement system (MS), which is capable of measuring all the above-mentioned characteristics, is presented. Additionally, by applying it, test measurements can also be performed on the motors to check the accuracy of the output functions generated by the simulation programs. Several experimental arrangements and procedures for specific experimental tasks are also presented here as examples for the application of the MS.

Reduced Interface Models for Haptic Interfacing With Virtual Environments

Haptic interfacing typically requires high communication frequencies in order to render realistic interactions between a user and a virtual environment. In this work, we introduce reduced interface modelling (RIM) as a method to bridge the discrepancy in frequency requirements between haptic devices and virtual environment simulators. The method offers a model-based approach to approximate the environment behaviour between integration time steps, without relying on time history extrapolations of the environment state with no physical basis. Using a vehicle dynamics simulation interfacing with a haptic steering wheel, we show that the proposed method results in a drastic reduction in the computation time required for numerical integration and updates to the virtual environment compared to the common zero-order-hold method. T-tests on numerical ratings by participants in a multi-user study also confirm that the RIM yields better uncoupled stability and haptic rendering smoothness compared to a common time-history-based multi-rate sampling method.

Performance evaluation and optimization of design parameters for electric vehicle-sharing platforms by considering vehicle dynamics

Global adoption of electric vehicles (EVs) faces many challenges such as range anxiety, high cost of EVs, and inadequate charging infrastructure. EV-sharing platforms resolve such concerns by setting up an optimal configuration for charging infrastructure and optimizing the charging decisions for depleted EVs. These platforms manage the vehicles’ flow to different charging stations and decide when and to what energy level the depleted vehicles should be recharged. Station-based platforms are one of the mainstream vehicle sharing systems where the customer picks-up and drops-off the vehicle at the designated stations. If a vehicle’s battery energy level falls below a threshold after completing the customer trip, it is charged either partially or fully at the charging station. This study addresses various operational and strategic decisions (such as the number of chargers, vehicle repositioning, and partial charging policy) for a one-way station-based EV-sharing platform using a stylized three-stage analytical framework. We use vehicle dynamics to model the EV powertrain and regenerative braking under different traffic conditions and simulate them using AVL CRUISE™. We model the platform operations using an open queuing network and provide a mixed-integer non-linear optimization program using inputs from the queuing network and vehicle dynamics simulation. We also provide a bound-based heuristic to solve this NP-hard optimization problem. We generate various managerial insights for an efficient implementation of the partial charging policy for EV-sharing platforms. The increase in the partial charging probability (the fraction of depleted vehicles charged partially) reduces the effective charging demand, resulting in fewer chargers and a higher profit. On the other hand, if we increase the target battery energy level for partial charging, the platform’s profit decreases due to higher effective charging demand dominating the benefits of lower charging frequency of vehicles.

Study on Vehicle–Road Interaction for Autonomous Driving

Autonomous vehicles (AVs) are becoming increasingly popular, and this can potentially affect road performance. Road performance also influences driving comfort and safety for AVs. In this study, the influence of changes in traffic volume and wheel track distribution caused by AVs on the rutting distress of asphalt pavement was investigated through finite element simulations. A vehicle-mounted three-dimensional laser profiler was used to obtain pavement roughness and texture information. The vehicle vibration acceleration was obtained through vehicle dynamics simulations, and the skid resistance indexes of 20 rutting specimens were collected. The results showed that an increase in traffic volume caused by the increasing AV traffic accelerated the occurrence of rutting distress; however, the uniform distribution of vehicles at both ends of the transverse direction could prolong the maintenance life of flexible and semi-rigid pavements by 0.041 and 0.530 years, respectively. According to Carsim and Trucksim vehicle simulations and multiple linear regression fitting, the relationship models of three factors, namely speed, road roughness, and comfort, showed high fitting accuracies; however, there were some differences among the models. Among the texture indexes, the arithmetic mean’s height (Ra) had the greatest influence on the tire–road friction coefficient; Ra greatly influenced the safe driving of AVs. The findings of this study were used to present a speed control strategy for AVs based on the roughness and texture index for ensuring comfort and safety during automatic driving.

Comparison of the dynamic response and environmental impact between traditional and innovative railway track systems

ABSTRACT Railways employ a range of different railway track forms. Here, a ballasted track design is compared to three different slab track solutions. The track designs are compared using both a life cycle analysis (LCA) and a methodology for simulation of three-dimensional vertical dynamic vehicle–track interaction, which has been verified versus field measurements. The interaction between vehicle and track is simulated in the time domain using an extended state-space vector approach. For the investigated load cases involving representative wheel and track irregularities, it is concluded that the maximum stress in the concrete parts is, for all designs, below the maximum flexural tensile strength. From the LCA, it is concluded that the production of steel and concrete cause most CO2 emissions, while the CO2 emissions due to maintenance activities such as tamping and rail grinding are only a small part of the overall emissions.

Assessing the fast non-Hertzian methods for wheel-rail rolling contact integrated in the vehicle dynamics simulation

An accurate and high-efficiency contact model is essential for vehicle-track dynamic simulation and wear prediction. The paper attempts to assess the influence of different contact models on the offline and online simulation, as well as wear depth distribution. Taking CONTACT as the reference model, the computational accuracies of contact model combinations (i.e. Hertz + FASTSIM, Kik–Piotrowski (KP) + FASTSIM, modified Kik–Piotrowski (MKP) + FASTSIM and MKP + FaStrip) are evaluated. Typical wheel-rail contact cases and two dynamic simulation cases (track irregularity and curve track) have been studied. Results show that MKP + FaStrip achieves the best computational accuracy in calculating the typical wheel-rail contact situation, besides, the yaw angle has a significant influence on the contact patch shape and pressure distribution, especially when the wheel flange contacts with a rail corner. With regard to the vehicle passing the track with the lateral irregularity, both KP + FASTSIM and MKP + FaStrip models can achieve relatively good agreement on dynamic results and wear prediction with CONTACT. In terms of the curve track, MKP + FaStrip has better accuracy on dynamic results and wear due to a larger yaw angle.

Vehicle dynamics response due to the adjustment of K&C parameters with the aid of a dynamic simulator with 9 DOF and a correlated virtual model

Given the increasing use of virtual simulation in automotive vehicle designs, the correlation of virtual models is a fundamental part of the process. The present work seeks to develop a methodology for the development of virtual vehicle dynamics models correlated with kinematics and compliance (K&C) parameters for use in a real-time vehicle dynamics simulator. Aiming this and with the aid of an SPMM 5000e to obtain data from the physical vehicle and from the ADAMS/Car and VI-CarRealTime (VI-CRT) software to the development and simulation and from MATLAB to the correlation, a multibody virtual model correlated in K&C to a hatchback car, with McPherson strut and twist-beam front and rear suspensions, respectively, is developed. At the end of the work, it was observed that the correlation between the virtual model and the test vehicle was found successfully and that, therefore, the virtual simulation allows to find reliable results regarding the vehicle’s suspension and steering system behavior. Subsequently, with the tests carried out with a driver in a VI-Grade DiM 150, a real-time driver-in-the-loop simulator with 9 degrees of freedom (DOF), the model and thus the methodology is validated through the steering ratio analysis: The lateral acceleration analysis in the vehicle’s center of gravity in different maneuvers allowed to observe that the model with higher steering ratio requires greater steering wheel angle values about the model with the lowest steering ratio so that the same maneuver is performed.

Reliability-Based Multivehicle Path Planning Under Uncertainty Using a Bio-Inspired Approach

Abstract Identifying a reliable path in uncertain environments is essential for designing reliable off-road autonomous ground vehicles (AGVs) considering postdesign operations. This article presents a novel bio-inspired approach for model-based multivehicle mission planning under uncertainty for off-road AGVs subjected to mobility reliability constraints in dynamic environments. A physics-based vehicle dynamics simulation model is first employed to predict vehicle mobility (i.e., maximum attainable speed) for any given terrain and soil conditions. Based on physics-based simulations, the vehicle state mobility reliability in operation is then analyzed using an adaptive surrogate modeling method to overcome the computational challenges in mobility reliability analysis by adaptively constructing a surrogate. Subsequently, a bio-inspired approach called Physarum-based algorithm is used in conjunction with a navigation mesh to identify an optimal path satisfying a specific mobility reliability requirement. The developed Physarum-based framework is applied to reliability-based path planning for both a single-vehicle and multiple-vehicle scenarios. A case study is used to demonstrate the efficacy of the proposed methods and algorithms. The results show that the proposed framework can effectively identify optimal paths for both scenarios of single and multiple vehicles. The required computational time is less than the widely used Dijkstra-based method.

DEEP NEURAL NETWORK BASED DATA-DRIVEN VIRTUAL SENSOR IN VEHICLE SEMI-ACTIVE SUSPENSION REAL-TIME CONTROL

This research presents a data-driven Neural Network (NN)-based Virtual Sensor (VS) that estimates vehicles’ Unsprung Mass (UM) vertical velocity in real-time. UM vertical velocity is an input parameter used to control a vehicle’s semi-active suspension. The extensive simulation-based dataset covering 95 scenarios was created and used to obtain training, validation and testing data for Deep Neural Network (DNN). The simulations have been performed with an experimentally validated full vehicle model using software for advanced vehicle dynamics simulation. VS was developed and tested, taking into account the Root Mean Square (RMS) of Sprung Mass (SM) acceleration as a comfort metric. The RMS was calculated for two cases: using actual UM velocity and estimations from the VS as input to the suspension controller. The comparison shows that RMS change is less than the difference threshold that vehicle occupants could perceive. The achieved result indicates the great potential of using the proposed VS in place of the physical sensor in vehicles.

A vision for a lightweight railway wheelset of the future

Rail vehicle lightweighting using fibre reinforced polymer composite materials is essential for the future of rail. This is recognised as a means of reducing carbon dioxide production through lower energy consumption, as well as reducing the impact on track degradation, thus delivering improved rail capacity and performance. This paper presents an overview of the work conducted within work package three of the NEXTGEAR project focused on the ‘wheelset of the future’. Three concepts for a hybrid metallic-composite railway axle are proposed and their strengths and weaknesses are assessed. A finite element analysis on the selected concept was conducted, including a solution for the bonded joints of the metallic collars which provide the interface to the wheels and bearings. An axle mass reduction of over 63% was shown. An overview is also provided regarding the analysis of manufacturability of the axle, non-destructive methods for axle inspection/structural health monitoring and effects of impacts from ballast stones. Finally, a preliminary evaluation of the benefits arising from the reduction of the unsprung masses is provided, based on multibody simulations of vehicle dynamics.