Design optimization of quarter-car models with passive and semi-active suspensions under random road excitation

A methodology is presented for optimizing the suspension damping and stiffness parameters of nonlinear quarter-car models subjected to random road excitation. The investigation starts with car models involving passive damping with constant or dual-rate characteristics. Then, we also examine car models where the damping coefficient of the suspension is selected so that the resulting system approximates the performance of an active suspension system with sky-hook damping. For the models with semi-active or passive dual-rate dampers, the value of the equivalent suspension damping coefficient is a function of the relative velocity of the sprung mass with respect to the wheel subsystem. As a consequence, the resulting equations of motion are strongly nonlinear. For these models, appropriate methodologies are first employed for obtaining the second moment characteristics of motions resulting from roads with a random profile. This information is next utilized in the definition of a vehicle performance index, which is optimized to yield representative numerical results for the most important suspension parameters. Special attention is paid to investigating the effect of road quality as well as on examining effects related to wheel hop. Finally, a critical comparison is performed between the results obtained for vehicles with passive linear or bilinear suspension dampers and those obtained for cars with semi-active shock absorbers

Estimation of diffusion coefficients in acetone - Cellulose acetate solutions

The mutual and the self-diffusion coefficients of the acetone-cellulose acetate system are determined by using established gravimetric measurements of the acetone evaporation rate. The process is studied as a one-dimensional numerical experiment utilizing the Galerkin finite element method. The numerical technique provides simultaneous solution of the model equations and yields by comparison with gravimetric data the diffusion coefficients of acetone in cellulose acetate for a wide range of temperatures and compositions. The estimated diffusion coefficients based on free volume theory are in satisfactory agreement with the available experimental data. It is believed that this method can be applied to other systems of interest. The mutual and the self-diffusion coefficients of the acetone-cellulose acetate system are determined by using established gravimetric measurements of the acetone evaporation rate. The process is studied as a one-dimensional numerical experiment utilizing the Galerkin finite element method. The numerical technique provides simultaneous solution of the model equations and yields by comparison with gravimetric data the diffusion coefficients of acetone in cellulose acetate for a wide range of temperatures and compositions. The estimated diffusion coefficients based on free volume theory are in satisfactory agreement with the available experimental data. It is believed that this method can be applied to other systems of interest

Finite element analysis of polymeric membrane and coating formation by solvent evaporation

The solvent evaporation process from acetone-cellulose acetate solutions is studied as a numerical experiment. The process is modeled as a coupled heat and mass transfer problem with a moving boundary. The resulting non-linear system of governing equations is solved with the Galerkin finite element method. A parametric analysis is carried out and it is discussed in detail how the process conditions affect the evaporation rate, the temperature at the surface of the solution and the resulting morphology of the final product. This analysis may be applied in the modeling of polymeric membrane formation and in the drying of coatings

Computer-aided estimation of diffusion coefficients in non-solvent/polymer systems

Full Paper: A novel method for estimating the mutual and self-diffusion coefficients of a non-solvent/polymer system is proposed in this work. The idea is to stud the evaporation process from non-solvent/solvent/polymer systems as a one-dimensional numerical experiment and to use polymer solution weight versus time data to fit the unknown parameters of the diffusion-coefficient correlations based on free-volume theory. For this purpose, the evaporation process is modeled as a coupled heat- and mass-transfer problem with a moving boundary, and the Galerkin finite-element method is used to solve simultaneously the non-linear governing equations. This method is successfully applied to the estimation of water-cellulose acetate diffusion coefficients and is valid over the whole range of temperatures and concentrations for practical applications in membrane technology. Additionally there is a detailed discussion on if water affects the morphology of the final cellulosic membrane by studying the concentration profiles of the constituents of the casting solution

Parametric identification and fault detection in vehicle models with nonlinear suspension

Systematic methodologies are applied for performing parametric identification and fault detection in nonlinear vehicle systems. The dynamic response of the vehicle models examined is caused by road excitation. In these models, the nonlinearities arise due to the function of the suspension dampers, which assume a different damping coefficient in tension and in compression. This leads to oscillator models with parameter discontinuities. First, emphasis is put on investigating some issues of fundamental importance, by employing a classical two degree of freedom quarter-car model. Since the dominant nonlinearities are due to switches between constant damping coefficients, appropriate methodologies are applied for obtaining exact motions of these models. Moreover, a statistically based methodology is applied for parametric identification and fault detection in vehicle suspensions with nonlinear characteristics, using dynamic test data. This methodology is then extended and applied to more involved and complete vehicle models. The numerical results presented demonstrate that this methodology provides an effective and practical way of detecting the type, location and severity of faults in vehicle suspensions

Multi-objective optimization of quarter car models with passive and semi-active suspensions

A methodology is presented for optimising the suspension damping and stiffness parameters of quarter car models, subjected to road excitation. First, models involving passive damping with constant or dual rate characteristics are considered. Then, models where the damping coefficient of the suspension is selected so that the resulting system approximates the performance of an active suspension system with sky-hook damping are also examined. For all these models, appropriate methodologies are first employed for obtaining the second moment characteristics of motions resulting from roads with random profile. This information is next utilized in the definition of a composite vehicle performance index, which is optimised to yield representative numerical results for the most important suspension parameters. Finally, results obtained by applying a suitable multi-objective optimization methodology are also presented in the form of classical Pareto fronts

Fault detection and optimal sensor location in vehicle suspensions

A statistical system identification methodology is applied for performing parametric identification and fault detection studies in nonlinear vehicle systems. The vehicle nonlinearities arise due to the function of the suspension dampers, which assume a different damping coefficient in tension than in compression. The suspension springs may also possess piecewise linear characteristics. These lead to models with parameter discontinuities. Emphasis is put on investigating issues of unidentifiability arising in the system identification of nonlinear systems and the importance of sensor configuration and excitation characteristics in the reliable estimation of the model parameters. A methodology is proposed for designing the optimal sensor configuration (number and location of sensors) so that the corresponding measured data are most informative about the condition of the vehicle. The effects of excitation characteristics on the quality of the measured data are systematically explored. The effectiveness of the system identification and the optimal sensor configuration design methodologies is confirmed using simulated test data from a classical two-degree-of-freedom quarter-car model as well as from more involved and complete vehicle models, including four-wheel vehicles with flexible body