Real-time multi-body formulation for virtual-reality-based design and evaluation of automobile controllers

Abstract Nowadays, modelling and simulation of vehicle dynamics play a great role in the design and evaluation of vehicle control systems, as they reduce costly and time-consuming construction of prototypes and experimentation. Multi-body simulation can be used for controller design, tuning and testing of electronic control units, optimum control, or onboard devices providing driver advice and/or actuation. This article reports on the application of a robust real-time formulation to the development of a low-cost and efficient computational framework for the design and evaluation of automobile motion controllers. The core elements of the tool are the real-time formalism for the dynamics of multi-body systems, a virtual-reality (VR) interface for human-in-the-loop simulation, and Matlab for the controllers. A detailed model of an existing prototype car has been implemented in the Fortran language, and controllers have been designed for several purposes, in order to test the developed framework. It has been demonstrated that the dynamic formalism is fast enough to enable human-in-the-loop simulation, that the VR interface is of great help for both control design and evaluation, and that Matlab algorithms can be efficiently connected to the Fortran computational model of the car.

[1]  T. Kimura,et al.  Driver-compatible steering system for wide speed-range path following , 2004, IEEE/ASME Transactions on Mechatronics.

[2]  D. Casanova,et al.  A Mathematical Model for Driver Steering Control, with Design, Tuning and Performance Results , 2000 .

[3]  Qin Zhang.  A generic fuzzy electrohydraulic steering controller for off-road vehicles , 2003 .

[4]  Ernst D. Dickmanns,et al.  Vehicles Capable of Dynamic Vision , 1997, IJCAI.

[5]  J. Christian Gerdes,et al.  The Use of GPS Based Velocity Measurements for Measurement of Sideslip and Wheel Slip , 2002 .

[6]  David M. Bevly,et al.  Global Positioning System (GPS): A Low-Cost Velocity Sensor for Correcting Inertial Sensor Errors on Ground Vehicles , 2004 .

[7]  Alessandro Saccon,et al.  Smart driver: a research project for closed loop vehicle simulation in MSC.ADAMS , 2004 .

[8]  J. Christian Gerdes,et al.  Integrating Inertial Sensors With Global Positioning System (GPS) for Vehicle Dynamics Control , 2004 .

[9]  Pavel Antos,et al.  A Control Strategy for Vehicle Trajectory Tracking Using Multibody Models , 2004 .

[10]  Michael Valášek,et al.  Overview of Coupling of Multibody and Control Engineering Tools , 2004 .

[11]  Adrian A. Hopgood,et al.  Intelligent Systems for Engineers and Scientists , 2021 .

[12]  Javier García de Jalón,et al.  Kinematic and Dynamic Simulation of Multibody Systems , 1994 .

[13]  Chih-Keng Chen,et al.  Fuzzy control for the anti-lock brake system , 1996, Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium.

[14]  Hans B. Pacejka,et al.  THE MAGIC FORMULA TYRE MODEL , 1991 .

[15]  C. J. Harris,et al.  A neurofuzzy approach to future intelligent driver support systems , 1998 .

[16]  Jürgen Ackermann.  Active Steering for Better Safety, Handling and Comfort , 1998 .

[17]  Ernst D. Dickmanns,et al.  Vehicles Capable of Dynamic Vision: A New Breed of Technical Beings? , 1998, Artif. Intell..

[18]  Lotfi A. Zadeh,et al.  Fuzzy logic = computing with words , 1996, IEEE Trans. Fuzzy Syst..

[19]  Ebrahim H. Mamdani,et al.  An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller , 1999, Int. J. Hum. Comput. Stud..

[20]  Javier Cuadrado,et al.  Intelligent Simulation of Multibody Dynamics: Space-State and Descriptor Methods in Sequential and Parallel Computing Environments , 2000 .

[21]  Javier García de Jalón,et al.  Kinematic and Dynamic Simulation of Multibody Systems: The Real Time Challenge , 1994 .

[22]  Charles C. MacAdam,et al.  Understanding and Modeling the Human Driver , 2003 .

[23]  Kyongsu Yi,et al.  A vehicle control algorithm for stop-and-go cruise control , 2001 .

[24]  T. I. M. Gordon,et al.  Integrated Control Methodologies for Road Vehicles , 2003 .

[25]  M. Tomizuka,et al.  Modeling and control of steering system of heavy vehicles for automated highway systems , 2004, IEEE/ASME Transactions on Mechatronics.

[26]  Christopher Edwards,et al.  Automotive Steering Control in a Split-µ Manoeuvre Using an Observer-Based Sliding Mode Controller , 2004 .

[27]  Javier Cuadrado,et al.  Modeling and Solution Methods for Efficient Real-Time Simulation of Multibody Dynamics , 1997 .

[28]  Ichiro Kageyama,et al.  ON A NEW DRIVER MODEL WITH FUZZY CONTROL , 1992 .

[29]  K Yi,et al.  An investigation of intelligent cruise control laws for passenger vehicles , 2001 .

[30]  Timothy Gordon,et al.  An automated driver based on convergent vector fields , 2002 .

[31]  S. Shladover.  Advanced Vehicle Control Systems (AVCS) , 1990, Vehicle Electronics in the 90's: Proceedings of the International Congress on Transportation Electronics.

[32]  Yuan Shihua,et al.  Electronic-control system of hydromechanical transmission , 1999, Proceedings of the IEEE International Vehicle Electronics Conference (IVEC'99) (Cat. No.99EX257).