Integrated model-based approach for the optimisation of vehicle ride comfort and handling characteristics: integrated vehicle dynamics model design

2016 ◽  
Vol 71 (1/2/3/4) ◽  
pp. 154 ◽  
Author(s):  
Ferdi Pir ◽  
Emre Albak ◽  
Ferruh Öztürk ◽  
Necmettin Kaya ◽  
N.A. �° ◽  
...  
Keyword(s):  
Vehicle Dynamics ◽  
Ride Comfort ◽  
Integrated Model ◽  
Model Design ◽  
Dynamics Model ◽  
Model Based ◽  
Handling Characteristics

scholarly journals Vehicle Dynamics Model and Tire Filer for Ride Comfort Analysis

2020 ◽  
Vol 28 (12) ◽  
pp. 859-864
Author(s):  
Jae-hun Jo ◽  
Won-yul Kang ◽  
Dae-oh Kang ◽  
Gwang-woo Lee ◽  
Seung-Jin Heo
Keyword(s):  
Vehicle Dynamics ◽  
Ride Comfort ◽  
Dynamics Model

Vehicle Dynamics Modeling Based on Vortex

2014 ◽  
Vol 624 ◽  
pp. 289-292
Author(s):  
Ting Jin ◽  
Yun Qiu Gong ◽  
Chun Yu Wei
Keyword(s):  
Vehicle Dynamics ◽  
Degrees Of Freedom ◽  
Ride Comfort ◽  
Dynamics Modeling ◽  
Dynamics Model ◽  
Six Degrees Of Freedom ◽  
Calculation Results ◽  
Vehicle Motion ◽  
Vehicle Suspension System ◽  
Vehicle Dynamics Modeling

The six degrees of freedom platform in vehicle driving simiulator simulates vehicle motion based on the calculation results of the dynamics model, so good dynamics model is the basis and prerequisite of simulator’s good performance. This paper describes the process of applying the Vortex software to establish vehicle dynamics model and focuses on the problem of damping matching in the vehicle suspension system based on the ride comfort and stability.

Semi-Active Suspension Suboptimal Control Using Dynamic Programming of a Quarter Car Suspension System

2016 ◽  
Author(s):  
John Dye ◽  
Nathan BuchMueller ◽  
Hamid Lankarani
Keyword(s):  
Cost Function ◽  
Vehicle Dynamics ◽  
Ride Comfort ◽  
Active Suspension ◽  
Suboptimal Control ◽  
Damping Coefficient ◽  
Handling Characteristics ◽  
Car Suspension ◽  
Quarter Car ◽  
The Cost

Many modern vehicle control systems utilize automatic braking and torque control to enhance driver inputs for improved stability and deceleration performance of passenger cars. A semi-active suspension approach may allow changes to the suspension characteristics under various conditions or driver inputs during vehicle operation. Suspensions are increasingly using semi active components to enhance handling characteristics by electronically adjusting vehicle dynamics. The active style of adjustment includes modifying suspension parameters directly such as electronic damping rates. The type of controller is important to react or adjust dynamically to the nonlinear nature of suspension systems. An optimal controller is introduced in attempt to improve ride comfort or road handling capability by manipulating the damping coefficient for a given trajectory. A suboptimal approach is given by utilizing a type of receding horizon control. The cost function, as used by Savaresi, contains a bias parameter to shift focus between road holding and passenger comfort. A dynamic quarter car suspension model is presented for simulation of nonlinear vehicle dynamics. During simulation at a given time step, various control inputs are simulated for finite steps into the future. The control input that minimizes the cost function is selected and the simulation time is allowed to advance with that input. The model is simulated using parameters for a typical passenger car and a 100 millisecond update rate from the suboptimal controller. A road profile with a bump is simulated and its transients are analyzed. The suboptimal controller is compared to its purely mechanical realization with a fixed damping coefficient. It is shown when manipulating the cost function ride comfort is desired chassis accelerations are minimized and when maximum road holding is desired tire deflection is minimized.

scholarly journals Central Non-Linear Model-Based Predictive Vehicle Dynamics Control

2021 ◽  
Vol 11 (10) ◽  
pp. 4687
Author(s):  
Philipp Maximilian Sieberg ◽  
Dieter Schramm
Keyword(s):  
Control Systems ◽  
Linear Model ◽  
Predictive Control ◽  
Vehicle Dynamics ◽  
Influence Factor ◽  
Ride Comfort ◽  
Automated Driving ◽  
Model Based ◽  
Non Linear ◽  
Vehicle Dynamics Control

Considering automated driving, vehicle dynamics control systems are also a crucial aspect. Vehicle dynamics control systems serve as an important influence factor on safety and ride comfort. By reducing the driver’s responsibility through partially or fully automated driving functions, the occupants’ perception of safety and ride comfort changes. Both aspects are focused even more and have to be enhanced. In general, research on vehicle dynamics control systems is a field that has already been well researched. With regard to the mentioned aspects, however, a central control structure features sufficient potential by exploiting synergies. Furthermore, a predictive mode of operation can contribute to achieve these objectives, since the vehicle can act in a predictive manner instead of merely reacting. Consequently, this contribution presents a central predictive control system by means of a non-linear model-based predictive control algorithm. In this context, roll, self-steering and pitch behavior are considered as control objectives. The active roll stabilization demonstrates an excellent control quality with a root mean squared error of 7.6953×10−3 rad averaged over both validation maneuvers. Compared to a vehicle utilizing a conventional control approach combined with a skyhook damping, pitching movements are reduced by 19.75%. Furthermore, an understeering behavior is maintained, which corresponds to the self-steering behavior of the passive vehicle. In general, the central predictive control, thus, increases both ride comfort and safety in a holistic way.

scholarly journals Development of Tuning Jounce Bumper and Verification of Ride Comfort Performance Using the Vehicle Dynamics Model

2019 ◽  
Vol 27 (10) ◽  
pp. 803-809
Author(s):  
ChulHyung Lee ◽  
MyeongJae Han ◽  
TaeWon Park ◽  
SukJin Lee ◽  
JeongSik Park
Keyword(s):  
Vehicle Dynamics ◽  
Ride Comfort ◽  
Dynamics Model

Simulation of Active Suspension System Based on Optimal Control

2013 ◽  
Vol 765-767 ◽  
pp. 382-386
Author(s):  
Jian Kun Peng ◽  
Hong Wen He ◽  
Bing Lu
Keyword(s):  
Optimal Control ◽  
Vehicle Dynamics ◽  
Ride Comfort ◽  
Simulation Models ◽  
Active Suspension ◽  
Suspension System ◽  
Dynamics Model ◽  
Vertical Roll ◽  
Lqr Controller ◽  
Passive Suspension System

A 7-DOFs vehicle dynamics model which includes active suspension system (ASS) is established, and a LQR controller for active suspension system was designed based on optimal control theory. The simulation models for active suspension system and passive suspension system were built, and a simulation experiment was carried out with MATLAB/Simulink Software. The simulation results show that the optimal control of active suspension system can reduce vertical, roll and pitch accelerations of sprung mass, and the vehicle ride comfort and handling stability were improved effectively.

A Modified Dugoff Tire Model for Combined-slip Forces

2010 ◽  
Vol 38 (3) ◽  
pp. 228-244 ◽  
Author(s):  
Nenggen Ding ◽  
Saied Taheri
Keyword(s):  
Vehicle Dynamics ◽  
Tire Model ◽  
Magic Formula ◽  
Model Based ◽  
Proposed Model ◽  
Road Friction ◽  
On Line ◽  
Double Lane Change ◽  
Tire Forces ◽  
Tire Models

Abstract Easy-to-use tire models for vehicle dynamics have been persistently studied for such applications as control design and model-based on-line estimation. This paper proposes a modified combined-slip tire model based on Dugoff tire. The proposed model takes emphasis on less time consumption for calculation and uses a minimum set of parameters to express tire forces. Modification of Dugoff tire model is made on two aspects: one is taking different tire/road friction coefficients for different magnitudes of slip and the other is employing the concept of friction ellipse. The proposed model is evaluated by comparison with the LuGre tire model. Although there are some discrepancies between the two models, the proposed combined-slip model is generally acceptable due to its simplicity and easiness to use. Extracting parameters from the coefficients of a Magic Formula tire model based on measured tire data, the proposed model is further evaluated by conducting a double lane change maneuver, and simulation results show that the trajectory using the proposed tire model is closer to that using the Magic Formula tire model than Dugoff tire model.

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