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The compound axle is a space saving suspension component that is relatively inexpensive and easy to install. Therefore it is used in rear suspension system of most front wheel drive passenger cars. This article present an optimum design algorithm for this component. A typical cross section for this the torsion beam of the axle is selected as a basis design. Using finite element methods, kinematics and elasto-kinematics behaviors of the section in vehicle normal maneuvers have been calculated. The acquired dynamic characteristics of the member was entered into a dynamic simulation program and the effect of geometrical parameters of torsion beam on the vehicle handling was studied. Using DOE method a sensitivity analysis was carried out on the torsion beam cross section to achieve an optimum cross section that could satisfy the objective function.

This article describes the design and implementation of a fuzzy controller developed for improving car stability by controlling car side-slip angle. The strategy has been to estimate the slip angle by a trained neural network and to determine an appropriate force arrangement on the wheels to produce the necessary yaw moment to limit car side slip control. A seven degrees of freedom car model including nonlinear tire behavior is used in design stage. The results were then validated on a full car model in ADAMS having 156 DOF and including elements nonlinearities and flexibilities. The simulations show the capability of the designed controller in improving stability of the car in sever maneuvers.

Design of a fuzzy controller for active suspension of a compact car is the topic of this article. The car dynamic model used for this purpose is very large and completely nonlinear. A large part of this model namely the car basic dynamics is constructed in ADAMS software which in excess of considering the components in their real working conditions, it includes parameters such as flexibility of parts and joints. The hydraulic system of the active suspension system is modeled in Matlab and the two softwares are linked to form the complete car model. Using control methods on the basis of neural network and fuzzy logic, a controller is designed that can eliminate roll over of the car in sever driving conditions.

This paper focuses on design and modeling of anti-roll system for a subcompact passenger car. The system consists of Hydraulic Assisted torsion bars on car suspensions, a hydraulic power unit, and controls. A 158 degrees of freedom model of the car basic dynamics is made in ADAMS software. A bond graph model of the hydraulic anti roll system is contracted and its state equations are entered into MATLAB/Simulink. The two software are linked and a complete model is made for study and controller design. This paper introduces the method as a useful tool for vehicle dynamics studies and discusses the problems and advantages of the method.

A neural network model of a full car has been developed here on the basis of ADAMS simulation results. The model basically intended for roll control studies, is a completely non-liner model and has 104 degrees of freedom. ADAMS software has been used to determine the model behavior to specific steering inputs. The out put of the simulation program was then used to train a neural network constructed to approximate the model for controller design and real time studies of control action. Specific time delayed feedback inputs to the neural network resulted an efficient approximate model with good accuracy for control tasks.