Micromechanical sensors for vehicle dynamics control systems

ATZ worldwide ◽  
2005 ◽  
Vol 107 (11) ◽  
pp. 16-19
Author(s):  
Johannes Schier ◽  
Rainer Willig ◽  
Klaus Miekley
Keyword(s):  
Control Systems ◽  
Vehicle Dynamics ◽  
Micromechanical Sensors ◽  
Vehicle Dynamics Control

Direct Longitudinal Force Feedback for High-Performance Vehicle Dynamics Control Systems

2021 ◽  
Author(s):  
Giorgio Riva ◽  
Luca Mozzarelli ◽  
Matteo Corno ◽  
Simone Formentin ◽  
Sergio M. Savaresi
Keyword(s):  
Model Predictive Control ◽  
Control Systems ◽  
Predictive Control ◽  
Vehicle Dynamics ◽  
High Performance ◽  
Force Feedback ◽  
Longitudinal Force ◽  
Spiral Path ◽  
Comparable Performance ◽  
Vehicle Dynamics Control

Abstract State of the art vehicle dynamics control systems do not exploit tire road forces information, even though the vehicle behaviour is ultimately determined by the tire road interaction. Recent technological improvements allow to accurately measure and estimate these variables, making it possible to introduce such knowledge inside a control system. In this paper, a vehicle dynamics control architecture based on a direct longitudinal tire force feedback is proposed. The scheme is made by a nested architecture composed by an outer Model Predictive Control algorithm, written in spatial coordinates, and an inner longitudinal force feedback controller. The latter is composed by four classical Proportional-Integral controllers in anti-windup configuration, endowed with a suitably designed gain switching logic to cope with possible unfeasible references provided by the outer loop, avoiding instability. The proposed scheme is tested in simulation in a challenging scenario where the tracking of a spiral path on a slippery surface and the timing performance are handled simultaneously by the controller. The performance is compared with that of an inner slip-based controller, sharing the same outer Model Predictive Control loop. The results show comparable performance in presence of unfeasible force references, while higher robustness is achieved with respect to friction curve uncertainties.

A Passivity Based Decentralized Control Design Methodology With Application to Vehicle Dynamics Control

2011 ◽  
Vol 134 (1) ◽  
Author(s):  
Carlos Villegas ◽  
Martin Corless ◽  
Wynita Griggs ◽  
Robert Shorten
Keyword(s):  
Control Systems ◽  
Decentralized Control ◽  
Output Feedback ◽  
Vehicle Dynamics ◽  
Design Methodology ◽  
Basic Problem ◽  
Control Design ◽  
Feedback Controllers ◽  
Structural Uncertainties ◽  
Vehicle Dynamics Control

A basic problem in the design of control systems is the lack of simple effective methods for designing decentralized control systems that are robust with respect to certain types of structural uncertainties. Here, we present one such design methodology that is based upon the Kalman–Yakubovich–Popov Lemma. Advantages of this approach include the ease with which output feedback controllers can be designed, and the fact that the design methodology and uncertainties are expressed using classical frequency domain notions. We use our design technique to obtain an integrated chassis controller for application to automotive dynamics.

scholarly journals Multi-Body Integrated Vehicle-Occupant Models for Collision Mitigation and Vehicle Safety using Dynamics Control Systems

2016 ◽  
Vol 5 (2) ◽  
pp. 80-122 ◽  
Author(s):  
Mustafa Elkady ◽  
Ahmed Elmarakbi ◽  
John MacIntyre ◽  
Mohamed Alhariri
Keyword(s):  
Control Systems ◽  
Vehicle Dynamics ◽  
Vehicle Body ◽  
Occupant Behaviour ◽  
Lumped Mass ◽  
Vehicle Collision ◽  
Kinematic Behaviour ◽  
Collision Mitigation ◽  
Multi Body ◽  
Vehicle Dynamics Control

The aim of this paper is to investigate the effect of vehicle dynamics control systems (VDCS) on both the collision of the vehicle body and the kinematic behaviour of the vehicle's occupant in case of offset frontal vehicle-to-vehicle collision. A unique 6-Degree-of-Freedom (6-DOF) vehicle dynamics/crash mathematical model and a simplified lumped mass occupant model are developed. The first model is used to define the vehicle body crash parameters and it integrates a vehicle dynamics model with a vehicle front-end structure model. The second model aims to predict the effect of VDCS on the kinematics of the occupant. It is shown from the numerical simulations that the vehicle dynamics/crash response and occupant behaviour can be captured and analysed quickly and accurately. Furthermore, it is shown that the VDCS can affect the crash characteristics positively and the occupant behaviour is improved.

Thermal Analysis and Fabrication of Split Shoe Drum Brake

2017 ◽  
Vol 867 ◽  
pp. 239-244
Author(s):  
Sivam Duraisivam ◽  
E. Jamuna
Keyword(s):  
Thermal Analysis ◽  
Control Systems ◽  
Active Control ◽  
Vehicle Dynamics ◽  
Brake Shoe ◽  
Drum Brake ◽  
Braking Force ◽  
Solid Works ◽  
Air Brake System ◽  
Vehicle Dynamics Control

Active control of vehicle dynamics has become one of the top competitive features in today’s automobiles. Vehicle dynamics control systems include effective brakes and the number of life loss has been increased due to the in effective brakes. To reduce the crashing of vehicles caused by the braking disability by overcoming the drawbacks of the conventional braking system.Brakes are employed to stop or slow down the speed of the vehicle depending upon the driving needs. When brake applied, each wheel of the vehicle builds-up a certain braking force. For this reason, greater the number of wheels braked, greater will be the braking effect, and sooner the vehicle comes to halt. With this in mind the existing air brake system of a 6 wheeler is studied and analyzed. Brake shoe assembly is completely modeled using solid works and the analysis of the brake shoe assembly is carried out in Ansys .The results are analyzed . Then redesigned brake shoe assembly is modeled in solid works and analyzed with certain changes as required.

ADVANCED MODEL-BASED DIAGNOSIS OF SENSOR FAULTS IN VEHICLE DYNAMICS CONTROL SYSTEMS

2005 ◽  
Vol 38 (1) ◽  
pp. 508-515 ◽  
Author(s):  
S.X. Ding ◽  
S. Schneider ◽  
E.L. Ding ◽  
A. Rehm
Keyword(s):  
Control Systems ◽  
Vehicle Dynamics ◽  
Sensor Faults ◽  
Model Based ◽  
Vehicle Dynamics Control ◽  
Advanced Model

Comprehensive prediction method of road friction for vehicle dynamics control

2009 ◽  
Vol 223 (8) ◽  
pp. 987-1002 ◽  
Author(s):  
L Li ◽  
J Song ◽  
H-Z Li ◽  
D-S Shan ◽  
L Kong ◽  
...  
Keyword(s):  
Friction Coefficient ◽  
Control Systems ◽  
Vehicle Dynamics ◽  
Control Mode ◽  
Fusion Method ◽  
The Road ◽  
Comprehensive Method ◽  
Road Friction ◽  
Vehicle Dynamics Control ◽  
Road Friction Coefficient

The contact friction characteristic between a tyre and the road is a key factor that dominates the dynamics performance of a vehicle under critical conditions. Vehicle dynamics control systems, such as anti-lock braking systems, traction control systems, and electronic stability control systems (e.g. Elektronisches Stabilitäts Programm (ESP)), need an accurate road friction coefficient to adjust the control mode. No time delay in the estimation of road friction should be allowed, thereby avoiding the disappearance of the optimal control point. A comprehensive method to predict the road friction is suggested on the basis of the sensor fusion method, which is suitable for variations in the vehicle dynamics characteristics and the control modes. The multi-sensor signal fusion method is used to predict the road friction coefficient for a steering manoeuvre without braking; if active braking is involved, simplified models of the braking pressure and tyre force are adopted to predict the road friction coefficient and, when high-intensity braking is being considered, the neural network based on the optimal distribution method of the decay power is applied to predict the road friction coefficient. The method is validated through a ground test under complicated manoeuvre conditions. It was verified that the comprehensive method predicts the road friction coefficient promptly and accurately.

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.

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