Modeling and Robust Control of Integrated Ride and Handling of Passenger Cars

Vehicle industries in the last decade have focused on improving ride quality and safety of passenger cars. To achieve this goal, modeling and simulation of dynamic behaviour of vehicles have been widely studied to design model based and robust control strategies. This PhD work presents a new integrated vehicle model and a nonlinear robust controller. The thesis is divided into two main sections: dynamic modeling and controller design. A new fourteen Degrees of Freedom integrated ride and handling vehicle model is proposed using Lagrangian method in terms of quasi-coordinates. The governing equations are derived considering the interaction between the ride and handling systems, Euler motion of the frames attached to the wheels and body, the load transfer among the wheels, acceleration and braking. A non-dimensional factor called coupling factor is introduced to study the coupling among different DOFs of the dynamic system for a defined vehicle maneuver. The coupling factor is considered as an indicator parameter to demonstrate the advantages of the developed model over the existing dynamic models. The improved model is validated using ADAMS/Car for different manoeuvres. The simulation results confirm the accuracy of the improved dynamic model in comparison with the ADAMS/Car simulations and the models available in the literature. Considering the proposed nonlinear integrated ride and handling vehicle model, a nonlinear robust controller is designed for an intermediate passenger car. The H∞ robust control strategy is designed based on the Hamiltonian-Jacobi-Isaacs (HJI) function, Linear Matrix Inequality and State Feedback techniques. In order to improve the ride and handling quality of the vehicle, a Magneto-rheological (MR) damper and a differential braking system are used as control devices. A frequency dependent MR damper model is proposed based on the Spencer MR damper model. The parameters of the model are identified using a combination of Genetic algorithms and Sequential Quadratic Programming approaches based on the experimental data. A mathematical model is validated using the experimental results which confirm the improvement in the accuracy of the model and consistency in the variation of damping with frequency. Based on the proposed MR damper model, an inverse model for the MR damper is designed. A differential braking system is designed to assign desired braking action. The dynamic behavior of the controlled vehicle is simulated for single lane change and bump input, considering three different road conditions: dry, rainy and snowy. The robustness of the designed controller is investigated when the vehicle is under these road conditions. The simulation results confirm the interactive nature of the ride and handling systems and the robustness of the designed control strategy

Optimizing the Pole Properties in Pole Vaulting by Using Genetic Algorithm Based on Frequency Analysis

Abstract. The pole vaulting is a sport with a long history involving complex dynamic motion. The aim of pole vaulting for the athlete is to achieve maximum height. The dynamic behavior of the pole-athlete system is identical to an inverted pendulum system with the buckling pole acting as a spring. The purpose of this paper is to study the influence of factors on the pole vaulting performance such as the initial velocity of the athlete, pole stiffness and length. The best results are obtained when all the stored potential energy in the pole is released with the pole reaching the 90 degrees condition for success. The natural frequency of the poleathlete system is obtained by Fast Fourier Transform (FFT). The storing and releasing time of potential energy should be equal to half the natural period. Based on this condition the pole length and stiffness are determined by using Genetic Algorithm (GA) so as to achieve maximum height. This paper presents an optimization procedure to design a flexible pole based on the frequency analysis. The result of this research can be utilized in sport industries to design optimum poles

Frequency Dependent Spencer Modeling of Magnetorheological Damper Using Hybrid Optimization Approach

Magnetorheological dampers have been widely used in civil and automotive industries. The nonlinear behavior of MR fluid makes MR damper modeling a challenging problem. In this paper, a frequency dependent MR damper model is proposed based on Spencer MR damper model. The parameters of the model are identified using an experimental data based hybrid optimization approach which is a combination of Genetic Algorithm and Sequential Quadratic Programming approach. The frequency in the proposed model is calculated using measured relative velocity and relative displacement between MR damper ends. Therefore, the MR damper model will be function of frequency. The mathematical model is validated using the experimental results which confirm the improvement in the accuracy of the model and consistency in the variation damping with the frequency