Frédéric Gillot

A dynamic-reliable multiple model adaptive controller for active vehicle suspension under uncertainties

The inherent uncertainties of vehicle suspension systems challenge not only the capability of ride comfort and handling performance, but also the reliability requirement. In this research, a dynamic-reliable multiple model adaptive (MMA) controller is developed to overcome the difficulty of suspension uncertainties while considering performance and reliability at the same time. The MMA system consists of a finite number of optimal sub-controllers and employs a continuous-time based Markov chain to guide the jumping among the sub-controllers. The failure mode considered is the bottoming and topping of suspension components. A limitation on the failure probability is imposed to penalize the performance of the sub-controllers and a gradient-based genetic algorithm yields their optimal feedback gains. Finally, the dynamic reliability of the MMA controller is approximated by using the integration of state covariances and a judging condition is induced to assert that the MMA system is dynamic-reliable. In numerical simulation, a long scheme with piecewise time-invariant parameters is employed to examine the performance and reliability under the uncertainties of sprung mass, road condition and driving velocity. It is shown that the dynamic-reliable MMA controller is able to trade a small amount of model performance for extra reliability.

Integrated workflow for multi-objective evolutionary optimization of the vehicle tyre parameters:

An integrated workflow based on a multi-objective evolutionary optimization algorithm combined with an automatic post-treatment of optimal solutions is presented. This workflow enables a fast pre-design of the vehicle tyre and suspension parameters to be achieved. Such optimization involves usually more than five objective functions. In this case, classical multi-objective approaches are not very successful in providing the designer automatically and quickly with a limited set of Pareto-optimal solutions. In this paper, the proposed workflow is applied to help during the pre-design of the tyre dimensions. Tyres have to fulfil about ten different specifications from road handling to rolling resistance. The results are given as a limited set of solutions, hence providing very powerful decision support for the designer.

Shape Optimization Under Vibroacoustic Criteria in the Mid-High Frequency Range

This paper deals with shape optimization issues under vibroacoustic criteria. The aim of the conducted research is to minimize the energy density in the cavity by changing its geometry parameters. The energy density is obtained through an energy method called simplified energy method (MES). The optimization method is based on a transformation function mapping 3D cavity surface on a 2D domain. The optimization process directly relies on this function and thus avoids remeshing of the geometry. The proposed method allows to describe the geometry through Bezier, Bspline and NURBS parametrization. To illustrate the method, we process a shape optimization on a simple acoustic cavity.

Modal Synthesis with the Isogeometric Kirchhoff–Love Shell Elements

The modal synthesis method is frequently used for the analysis of large structures composed of multiple parts concerning dynamic aspects. In this paper, we extended the modal synthesis method under the isogeometric analysis framework. The isogeometric Kirchhoff–Love shell elements are used for the analysis of the substructures, the Craig–Bampton method is used for the modal synthesis and the bending-strip method is used for the substructures coupling. We give examples on the modal analysis and the harmonic response analysis. The results show the effectiveness of the method.

Boosting the optimization process of perovskite solar cells by partial sampling and kriging method

Lead halide perovskite solar cells (PVSCs) have been exhibiting high efficiency by using abundant materials and availability on flexible substrates with easy fabrication process. However, achieving the high-efficiency PVSCs is not easy due to multi-layered structure, difficulty to control the surface uniformity and crossover effects of controlling parameters, so the fast optimization process is very important for improving them. Here, we report the way for improving the optimum condition of perovskite layer by using a combination of the design of experiment (DoE), the interpolation prediction method and genetic algorithm (GA) optimization, which can reduce the cost and time consumed for experiments. To understand the effect of parameters we also characterized the property of materials such as crystalline structure. After the optimization and the characterization, we found the important factor to increase the efficiency of PVSCs and obtained efficiency at 8.87% through only 12 experimental samplings.

Sensitivity of Shape Parameters of Brake Systems Under Squeal Noise Criteria

We propose in this paper to deal with squeal noise reduction of brake systems through their shape optimization during the design step. We first expose the FEM model used to generate the stability diagram representing the squeal noise behavior of a given brake system shape. We then propose an objective function able to be included in a minimization problem and based on the stability diagram. We use then a parallel code to browse the objective function response surface through a Latin Hypercube Sampling design of experiment. A Self Organizing Map is then generated to expose the sensibility of our objective function to seven shape parameters of the FEM brake system. We present and analysis the SOM results for further optimization steps.

Shape Optimization for Natural Frequency with Isogeometric Kirchhoff-Love Shell and Sensitivity Mapping

A fast shape optimization strategy for free form shell structure design with structural dynamics criteria is proposed in this paper. The structures are modelled with Non-Uniform Rational B-Spline based isogeometric Kirchhoff-Love shell elements. The substitution of the traditional finite elements not only makes the mesh model geometrically exact but also avoids the laborious mesh regeneration during the design update. As for the structural response evaluation, the modal synthesis method is adopted to avoid a repeated evaluation of some substructures where there are no designed variables attached; thus, the model reanalysis is speeded up. A bottom-up strategy for the analytical design sensitivity evaluation is also proposed here; the element-level analytical sensitivity with respect to the inherent shape parameters is firstly calculated from which the design sensitivity is then extracted with the help of a sensitivity map. Finally, gradient based algorithm is used to solve the optimization problem. Several examples show that our approach is flexible and efficient for fast free form shell structure optimization.

An isogeometric Reissner–Mindlin shell element based on mixed grid:

We propose in this article a new isogeometric Reissner–Mindlin degenerated shell element for linear analysis. It is based on the mixed use of non-uniform rational basis spline and Lagrange basis functions in the same domain. The mid-surface of the shell is represented and discretized using non-uniform rational basis spline and the directors of the shell are discretized using Lagrange polynomials. The interpolatory property of Lagrange polynomials gives a natural choice of fiber vectors, thus removing the difficulties in the definition of directors that is seen in most isogeometric Reissner–Mindlin shell elements. The non-uniform rational basis spline representation of the mid-surface allows us to maintain the exact geometry representation characteristic of the isogeometric approach. The independent expressions of displacements and rotations also give users the possibility to use different numbers of degrees of freedom in an element for both kinematic variables. Several numerical examples show that our method is simple, robust, and efficient.

Methodology for the Design of the Geometry of a Cavity and Its Absorption Coefficients as Random Design Variables Under Vibroacoustic Criteria

Reducing the noise level in the acoustic cavities is the important problem when treating inflight conditions of commercial planes or boats. Shape optimization of the acoustic cavity that will take into account the geometrical and material uncertainties, arising during the manufacturing process, is presented in this paper. The noise level is controlled by minimizing the energy density in the cavity, obtained through an energy method called Simplified Energy Method. Such formulation is based on our previous published work where transformation function mapping 3D cavity surface on a 2D domain was proposed. The optimization process directly relies on this function and thus avoids remeshing of the geometry. Robust optimization is performed using the nondominated sorting genetic algorithm (NSGA-II) together with the Kriging surrogate model. Influence of geometrical and material characteristics on the optimal solution is identified.

Surrogate models for efficient stability analysis of brake systems

This study assesses capacities of the global sensitivity analysis combined together with the kriging formalism to be useful in the robust stability analysis of brake systems, which is too costly when performed with the classical complex eigenvalues analysis (CEA) based on finite element models (FEMs). By considering a simplified brake system, the global sensitivity analysis is first shown very helpful for understanding the effects of design parameters on the brake systems stability. This is allowed by the so-called Sobol indices which discriminate design parameters with respect to their influence on the stability. Consequently, only uncertainty of influent parameters is taken into account in the following step, namely, the surrogate modelling based on kriging. The latter is then demonstrated to be an interesting alternative to FEMs since it allowed, with a lower cost, an accurate estimation of the systems proportions of instability corresponding to the influent parameters.