Compliance Effect Consideration for Real-Time Multibody Vehicle Dynamics Using Quasi-Static Analysis

2007 ◽  
Author(s):  
Sung-Soo Kim ◽  
Wan Hee Jeong ◽  
Seonghoon Kim
Keyword(s):  
Real Time ◽  
Static Analysis ◽  
Vehicle Dynamics ◽  
Synthesis Method ◽  
Field Tests ◽  
Intelligent Vehicles ◽  
Dynamics Model ◽  
Vehicle Model ◽  
The Real ◽  
Reaction Forces

HILS (Hardware-in-the Loop Simulation) vehicle simulator is one of the most effective tools to develop control subsystems for the intelligent vehicles, since expensive vehicle field tests can be replaced with virtual tests in the HILS simulator. In the HILS simulator, the software vehicle dynamics model must be solved in real-time, and it must also reproduce the real vehicle motions. Compliance effects from suspension bush elements significantly influences the vehicle behavior. In order to include such compliance effects to the vehicle model, normally the spring-damper model of the bush elements is used. However, high stiffness of the bush elements hinders real-time simulations. Thus, it is necessary to have an efficient method to include compliance effects for the real-time multibody vehicle dynamics model. In this paper, compliance model for real-time multibody vehicle dynamics is proposed using quasi-static analysis. The multibody vehicle model without bush elements is used based on the subsystem synthesis method which provides real-time computation on the multibody vehicle model. Reaction forces are computed in the suspension subsystem. According to deformation from the quasi-static analysis using reaction forces and bush stiffness, suspension hardpoint locations and suspension linkage orientation are changed. To validate the proposed method, quarter car simulations and full car bump run simulations are carried out comparing with the ADAMS vehicle model with bush elements. CPU times are also measured to see the real-time capabilities of the proposed method.

A Real-Time Multibody Vehicle Dynamics Model Using a Subsystem Synthesis Method

2001 ◽  
Author(s):  
Sung-Soo Kim ◽  
Young-Seok Oh
Keyword(s):  
Real Time ◽  
Vehicle Dynamics ◽  
Equations Of Motion ◽  
Synthesis Method ◽  
Dynamics Model ◽  
Vehicle Model ◽  
Recursive Formulation ◽  
The Real ◽  
Stop And Go ◽  
Time Simulation

Abstract A real-time multibody vehicle dynamics model has been developed using a subsystem synthesis method in a PC-based workstation. The subsystem synthesis method produces 6 × 6 matrix form of equations of motion for the chassis and small size each of suspension subsystem equations of motion separately. Simulations such as, bump-run, stop-and-go, and brake-in-turn have been carried out. Solutions have been validated to compare with those from the model with the conventional recursive formulation. CPU times taken for simulations have been also measured to verify the real-time simulation capability of the proposed vehicle model.

The Research on the Embedded Vehicle Dynamics Simulation Method

2013 ◽  
Vol 380-384 ◽  
pp. 1746-1749
Author(s):  
Jun Zhan ◽  
Jiang Li Lu ◽  
Liang Xu ◽  
Wei Zhang
Keyword(s):  
Real Time ◽  
Vehicle Dynamics ◽  
Subjective Evaluation ◽  
Simulation Method ◽  
Dynamics Simulation ◽  
Dynamics Model ◽  
The Real ◽  
Online Simulation ◽  
Preliminary Study ◽  
And Control

At present, the performance of the vehicle dynamics model is mainly evaluated objectively through offline simulation. In this paper, a vehicle dynamics model was implemented in dSPACE, which was applied to the Automotive Performance Simulator and the preliminary study was made for the realization of the subjective evaluation of the performance of vehicle dynamics model through the real-time closed-loop online simulation. The dSPACE interface library was used to write a Clib program to operate and control the Carsim RT model running on the dSPACE platform, which realized the communication between the external hardware and the real-time hardware of dSPACE.

Road-Vehicles Control Logic Integrating Real Time Multibody Model Follower

2015 ◽  
Author(s):  
Isabel Ramirez Ruiz ◽  
Edoardo Sabbioni ◽  
Francesco Braghin ◽  
Federico Cheli
Keyword(s):  
Real Time ◽  
Vehicle Dynamics ◽  
Vehicle Model ◽  
Control Logic ◽  
Active Systems ◽  
The Real ◽  
Multibody Model ◽  
Drive Control ◽  
Primary Model ◽  
Real Vehicle

The challenge to enhance the vehicle driving and handling with a state estimation and prediction system is presented by fusing a primary real time multibody vehicle model capable of providing a good indication of vehicle stability and control, and a secondary model able to estimate the vehicle state from vehicle real and virtual sensors to correct the indications of the primary model. A mathematical algorithm combines these two models in the drive control system improving the behavior of the active systems of the vehicle. A Multibody vehicle model has been used to achieve a high fidelity simulation of vehicle dynamics. The selected software is LMS.Virtual.Lab Motion with Real-Time Solver which complements the AMESim Real-Time Solver to handle complex real-time 3D-1D mechatronic systems without any simplified conceptual models. A Sensor Signal Processing Model has been developed to estimate the vehicle states and calculating tire-road contact forces and vehicle sideslip angle. The methodological approach uses the equations of motion of the chassis applying the fundamental principles of classical physics: Newtonian method and Euler angles. The control logic is based on the continuous updating of the preview multibody vehicle model by the controller sensors information network, which makes the model forecast behavior closer to the real one and improve comfort and linearity of the vehicle response. The driver inputs (throttle, steer angle and torque, brake, gear) are the same for the MBS real time model and for the real vehicle. A first training logic updates the MBS model based on the real vehicle behavior calculated by the sensor network, where the logic has to update in the MBS model just the factors depending on the vehicle itself (for example car weight, tire temperature, shock absorber damping forces, tires characteristics) and to understand and keep into account different environment variation (wet / dry surface). If the real vehicle is equipped with active control systems to improve handling and stability, as active camber control, drive by wire, ESP, Body movement active controls, the real time multibody model will interact with the models 1D or 3D of these vehicle dynamics controls and will improve their performance with a very high accuracy prediction of their influence on vehicle dynamic response. In conclusion with the help of the preview multibody vehicle model the drive control logic will increase the performance and drive ability of the vehicle with smart logic interacting with all the active systems.

Dynamics of Tire Blowout Events and Driver Assist System for Controlling Them

2015 ◽  
Author(s):  
Dan T. Horak ◽  
Shane K. Lack
Keyword(s):  
Real Time ◽  
Vehicle Dynamics ◽  
Driving Simulator ◽  
Driver Model ◽  
Dynamics Model ◽  
Vehicle Model ◽  
Human Driver ◽  
Driver Analysis ◽  
The One ◽  
Rear Tire

Dynamics of a pickup truck undergoing a rear tire blowout are analyzed as a system controlled by a human driver. Analysis is based on a large nonlinear vehicle dynamics model combined with a human driver model. The main reason why some tire blowouts result in accidents is identified. Insight is generated in experiments with human drivers in a driving simulator that runs the same vehicle model as the one used for analysis. A driver assist system for controlling tire blowouts is developed and validated in real time in the driving simulator.

Construction of a Rational Tire Model for High Fidelity Vehicle Dynamics Simulation Under Extreme Driving and Environmental Conditions

2010 ◽  
Author(s):  
S. C¸ag˘lar Bas¸lamıs¸lı ◽  
Selim Solmaz
Keyword(s):  
Vehicle Dynamics ◽  
Dynamics Simulation ◽  
High Fidelity ◽  
Tire Model ◽  
Dynamics Model ◽  
Vehicle Model ◽  
Prospective Design ◽  
Magic Formula ◽  
Rational Models ◽  
Simulation Results

In this paper, a control oriented rational tire model is developed and incorporated in a two-track vehicle dynamics model for the prospective design of vehicle dynamics controllers. The tire model proposed in this paper is an enhancement over previous rational models which have taken into account only the peaking and saturation behavior disregarding all other force generation characteristics. Simulation results have been conducted to compare the dynamics of a vehicle model equipped with a Magic Formula tire model, a rational tire model available in the literature and the present rational tire model. It has been observed that the proposed tire model results in vehicle responses that closely follow those obtained with the Magic Formula even for extreme driving scenarios conducted on roads with low adhesion coefficient.

Real-Time Multibody Vehicle Dynamics Software for Virtual Handling Tests

2007 ◽  
Author(s):  
Sung-Soo Kim ◽  
Kyoungnam Ha ◽  
Dohyun Kim ◽  
Taeoh Tak ◽  
Seung-Eon Shin
Keyword(s):  
Virtual Reality ◽  
Real Time ◽  
Vehicle Dynamics ◽  
Equations Of Motion ◽  
Synthesis Method ◽  
Hardware In The Loop ◽  
Vehicle Modeling ◽  
Time Dynamics ◽  
Point Data ◽  
Suspension Model

Real-time multibody vehicle dynamics software has been developed for virtual handling tests. The software can be utilized for hardware in the loop simulations and consists of three modules such as a graphical vehicle modeling preprocessor, real time dynamics solver, and virtual reality graphic postprocessor for virtual handling tests. In the graphical vehicle modeling preprocessor, vehicle hard point data for a suspension model are automatically converted into multibody vehicle model. In the real time dynamics solver, efficient subsystem synthesis method is used to create multibody equations of motion a subsystem by a subsystem. In the virtual reality graphic postprocessor, virtual proving ground environment has been also developed by using OpenGL for virtual handling tests. This software is written C and can be converted to the S-function as a plant model in the RT-LAB real time environment for HILS application.

scholarly journals Zero-Shot Pipeline Detection for Sub-Bottom Profiler Data Based on Imaging Principles

2021 ◽  
Vol 13 (21) ◽  
pp. 4401
Author(s):  
Gen Zheng ◽  
Jianhu Zhao ◽  
Shaobo Li ◽  
Jie Feng
Keyword(s):  
Standard Deviation ◽  
Object Detection ◽  
Real Time ◽  
Synthesis Method ◽  
Vertical Direction ◽  
Mean Deviation ◽  
The Real ◽  
Detection Algorithms ◽  
Underwater Pipeline ◽  
Time Requirements

With the increasing number of underwater pipeline investigation activities, the research on automatic pipeline detection is of great significance. At this stage, object detection algorithms based on Deep Learning (DL) are widely used due to their abilities to deal with various complex scenarios. However, DL algorithms require massive representative samples, which are difficult to obtain for pipeline detection with sub-bottom profiler (SBP) data. In this paper, a zero-shot pipeline detection method is proposed. First, an efficient sample synthesis method based on SBP imaging principles is proposed to generate samples. Then, the generated samples are used to train the YOLOv5s network and a pipeline detection strategy is developed to meet the real-time requirements. Finally, the trained model is tested with the measured data. In the experiment, the trained model achieved a [email protected] of 0.962, and the mean deviation of the predicted pipeline position is 0.23 pixels with a standard deviation of 1.94 pixels in the horizontal direction and 0.34 pixels with a standard deviation of 2.69 pixels in the vertical direction. In addition, the object detection speed also met the real-time requirements. The above results show that the proposed method has the potential to completely replace the manual interpretation and has very high application value.

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