Adaptive suspension strategy for a double wishbone suspension through camber and toe optimization

A suspension system is responsible for the safety of vehicle during its manoeuvre. It serves the dual purpose of providing stability to the vehicle while providing a comfortable ride quality to the occupants. Recent trends in suspension system have focused on improving comfort and handling of vehicles while keeping the cost, space and feasibility of manufacturing in the constraint. This paper proposes a method for improving handling characteristics of a vehicle by controlling camber and toe angle using variable length arms in an adaptive manner. In order to study the effect of dynamic characteristics of the suspension system, a simulation study has been done in this work. A quarter car physical model with double wishbone suspension geometry is modelled in SolidWorks. It is then imported and simulated using SimMechanics platform in MATLAB. The output characteristics of the passive system (without variable length arms) were validated on MSC ADAMS software. The adaptive system intends to improve vehicle handling characteristics by controlling the camber and toe angles. This is accomplished by two telescopic arms with an actuator which changes the camber and toe angle of the wheel dynamically to deliver best possible traction and manoeuvrability. Two PID controllers are employed to trigger the actuators based on the camber and toe angle from the sensors for reducing the error existing between the actual and desired value. The arms are driven by actuators in a closed loop feedback manner with help of a separate control system. Comparison between active and passive systems is carried out by analysing graphs of various parameters obtained from MATLAB simulation. From the results, it is observed that there is a reduction of 58% in the camber and 96% in toe gain. Hence, the system provides the scope of considerable adaptive strategy in controlling dynamic characteristics of the suspension system

Design and Implementation of ANFIS Algorithm Using VHDL for Vechicular System

In this review paper Field Programmable Gate Array (FPGA) is proposed to build an Adaptive Neuro Fuzzy Inference System (ANFIS) algorithm for non linear behavior of the system. In the application of designing the algorithm for controlling a full vehicle nonlinear active suspension system. The algorithm for neural was Back propagation and for fuzzy takagi- sugeno-kang active suspension systems is very important for guaranteeing the riding comfort for passengers and road handling quality for a vehicle. It is shown that the ANFIS can modelize a nonlinear system very accurately by means of data taken from mathematical model. Firstly the MATLAB SIMULINK toolboxes are used to simulate the proposed controllers with the controlled model and to display the responses of the controlled model under different types of disturbance. But in this paper the implementation of the adaptive neuro fuzzy inference system algorithm using FPGA boards has been try to investigated in this work. The Xilinx ISE software is employed to synthesis the VHDL codes used to program the FPGA. DOI: 10.17762/ijritcc2321-8169.15028

An observer design for active suspension system

The purpose of this paper is to construct an active suspension for a quarter car model with observer design. The proportional-integral sliding mode is chosen as a control strategy, and the road profile is estimated by using an observer design. The performance of the proposed controller will be compared with the linear quadratic regulator by performing extensive computer simulation

Sliding mode control of active suspension system

The purpose of this paper is to present a new approach in controlling an active suspension system. This approach utilized the proportional integral sliding mode control scheme. Using this type of sliding surface, the asymptotic stability of the system during sliding mode is assured compared to the conventional sliding surface. The proposed control scheme is applied in designing an automotive active suspension system for a quarter-car model and its performance is compared with the existing passive suspension system. A simulation study is performed to prove the effectiveness of this control design

Real-Time Anticipatory Suspension Control for Single Event Disturbances

Most commercial vehicles currently on the market are still equipped with a passive suspension system, while some luxury brands may already use an adaptive suspension. Active suspension systems on the other hand are rarely found, however, they offer great opportunities to close the gap of the well-known trade-off between ride comfort and handling. Besides that, they can also be used to mitigate single event disturbances, an objective of the USA army as announced in a solicitation which initiated and motivated this research. In addition to that, several studies were found stating the impact and danger of potholes and their impact on the vehicle and passenger. Reviewing the literature, several control strategies for controlling active suspension systems were found. However, most of these approaches used feedback control and did not try to mitigate single event disturbances. Since literature also suggested making use of look ahead preview, research at the Performance Engineering Research Lab at Virginia Tech was started in 2015 combining look ahead preview and an adaptive system to generate optimal force profiles. This introductory research succeeded and proved the used approach to be very promising. However, the used adaptive system was not designed to operate in real-time and did not show any correlation between different road profiles. Therefore, the main objective of this research project is to evaluate and analyze each of the adaptive systems by searching for correlations in their solutions. The results then should be used in order to design a control law which emulates the adaptive system and can be used in a real-time environment. First, an overall research methodology was derived. According to this a software application was developed which extracts ideal force profiles from single event disturbance signals in order to miti- gate their impact to the vehicle. The application uses a quarter car model with a partially loaded active suspension system, a set of predefined road profiles, a road profile preprocessor, and an adaptive algorithm. The preprocessing includes geometric filtering using a Tandem-Cam Model and the adaptive processor used an iterative version of the Filtered-X Last-Mean-Square algorithm. During evaluation and analysis of several generated data sets, high correlations in the generated and adjusted adaptive systems were discovered. From these an empirical and theoretical universal filter model was derived, which was then used to design an open-loop control law named Optimal Force Control. The original control law and an adjusted version designed for a real-time environment were tested for all predefined road profiles over all considered vehicle velocities and prove to perform much better than the offline solution using the adaptive system. In summary, a control law named Optimal Force Control was designed which can be used and implemented in a vehicle to extract an analytical and ideal force profile given a road profile input. Implementing an active suspension system with tracking controller, this approach can be used in order to mitigate single event disturbance signals by reducing the vertical vehicle acceleration

Levitation chassis dynamic analysis and robust position control for maglev vehicles under nonlinear periodic disturbance

In this paper, an experiment for decoupling the dynamic behavior of the levitation chassis of maglev vehicle with four electromagnetic suspension (EMS) modules is implemented, which validated that the stable suspension of maglev vehicle can be achieved by controlling individual EMS modules. Then, a dynamic model for single EMS module is established. A PD controller is designed to control the vertical position of the maglev vehicle. Simulations illustrate that the robustness of the controller is weak against the periodic disturbance. To improve the robustness of the controller, a nonlinear control law for disturbance rejection is applied by combining with a periodic disturbance estimator with an adaptive notch filter, which is capable of compensating exogenous nonlinear periodic disturbance. Different from using the existing control laws, the structure, parameters and period of the disturbance is not required. Moreover, the controller designed in this work satisfies the requirement of unidirectional force input. Simulation results are presented to demonstrate the excellent dynamic performance with the proposed robust controller

Modelling and Validation of a Regenerative Shock Absorber System

Abstract— For effective energy regeneration and vibration dampening, energy regenerative suspension systems have received more studies recently. This paper presents the dynamic modeling and a test system of a regenerative shock absorber system which converts vibration motion into rotary motion through the adjustment of hydraulic flow. Hydraulic circuit configuration achieves the one way flow and energy regeneration during both compression and extension strokes. The dynamic modeling is performed for the evaluation of design concept and the feasibility studies of regenerative shock absorber system theoretically. Based on simulated results, the efficiency of hydraulic transmission is optimized and validated in test system. The results show that the performance of hydraulic fluid, the features of rotary motion and the capability of energy regeneration are verified and compared between dynamic modeling and experiments. Meanwhile, the average power of 118.2W and 201.7W with the total energy conversion of 26.86% and 18.49% can be obtained based on experiments under sinusoidal inputs with 0.07854m/s and 0.1256m/s respectively

Adaptive Output Feedback Apparatuses And Methods Capable Of Controlling A Non-minimum Phase System

The invention comprises apparatuses and methods for providing the capability to stabilize and control a non-minimum phase, nonlinear plant with unmodeled dynamics and/or parametric uncertainty through the use of adaptive output feedback. A disclosed apparatus can comprise a reference model unit for generating a reference model output signal ym. The apparatus can comprise a combining unit that combines and differences a plant output signal y of a non-minimum phase plant for which not all of the states can be sensed, and a plant output signal y, to generate an output error signal ỹ. The apparatus can further comprise an adaptive control unit for generating an adaptive control signal uad used to control the plant.Georgia Tech Research Corporatio