scholarly journals Analysis of the Influence of Suspension Actuator Limitations on Ride Comfort in Passenger Cars Using Model Predictive Control

Actuators ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 77 ◽  
Author(s):  
Erik Enders ◽  
Georg Burkhard ◽  
Nathan Munzinger
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Ride Comfort ◽  
Rate Of Change ◽  
High Rate ◽  
Passenger Cars ◽  
Wheel Load ◽  
Country Road ◽  
Necessary Constraints ◽  
Vehicle Dynamics Control

Active suspension systems help to deliver superior ride comfort and can be used to resolve the objective conflict between ride comfort and road-holding. Currently, there exists no method for analyzing the influence of actuator limitations, such as maximum force and maximum rate of change, on the achievable ride comfort. This research paper presents a method that is capable of doing this. It uses model predictive control to eliminate the influence of feedback controller performance and to integrate both actuator limitations and necessary constraints on dynamic wheel-load variation and suspension travel. Various scenarios are simulated, such as driving over a speed bump and inner city driving, as well as driving on a country road and motorway driving, using a state-of-the-art quarter-car model, parameterized for a luxury class vehicle. It is analyzed how comfort, or in one scenario road-holding, can be improved with consideration for the actuator limitations. The results indicate that actuator rate limitation has a strong influence on vertical vehicle dynamics control system performance, and that relatively small maximum forces of around 1000 to 2000 N are sufficient to successfully reject disturbances from road irregularities, provided the actuator is capable of supplying the forces at a sufficiently high rate of change.

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.

Model Predictive Control Application to Flexible-Bodied Railway Vehicles for Vibration Suppression

2013 ◽  
Vol 10 ◽  
pp. 25-35
Author(s):  
P.E. Orukpe
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
High Speed ◽  
Ride Comfort ◽  
The Body ◽  
Ride Quality ◽  
Linear Matrix ◽  
Railway Vehicle ◽  
Railway Vehicles ◽  
Effective Manner

In this paper, we apply model predictive control (MPC) based on mixed H2/H to active vibration control of the flexibility of railway vehicle to improve ride quality. However, the flexibility in the body of high-speed railway vehicles creates difficulties which in practice may result in the body structure being heavier than what it is supposed to be. The use of active suspension helps to model the vehicle and its flexibility in an effective manner. Conventional control approaches are compared with linear matrix inequality MPC technique using flexible-bodied railway vehicle as an example. The result indicates that the MPC technique performs better in improving ride comfort compared to the passive and classical techniques when flexible modes are present.

Model Predictive Control of a pH Maintaining System

2013 ◽  
Vol 11 (1) ◽  
pp. 14-20
Author(s):  
A. Grancharova ◽  
L. Kostov
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Ph Value ◽  
Rate Of Change ◽  
Nonlinear Model Predictive Control ◽  
Box Constraints ◽  
Input Flow ◽  
Flow Rates ◽  
Optimal Regulation ◽  
Output Flow

Abstract In this paper the problem of optimal regulation of a pH maintaining system is considered, where the outputs are the pH value and the liquid level in the system and the control inputs are the flow rates of the base input flow and the output flow. The optimal regulation problem is formulated as a nonlinear model predictive control problem in the presence of constraints. Two cases are considered: 1) presence of box constraints only on the control inputs and 2) considering also constraints on the rate of change of the inputs.

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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