Abderahman Makhloufi

7 – Optimizing Reliability of Electronic Systems

The deterministic optimization of embedded electronic systems does not take uncertainties into account and does not guarantee a reliable design. This chapter provides a probabilistic approach for the design optimization of embedded mechatronic systems. This approach takes into account the inherent nature of uncertainties which are due to insufficient knowledge of the material properties of the materials, the geometric dimensions and the load fluctuations. The rational approach for optimizing embedded systems consists of considering the propagation of uncertainties in multi-physical behavior (electrical, thermal, mechanic, etc.) by using a probabilistic modeling of uncertainties of the input parameters. The reliability-based optimization approach aims to find the best design with a compromise between reducing the objective function (cost, weight, etc.) and ensuring reliability.

5 – Electro-Thermo-Mechanical Modeling

Abstract The main aim of this chapter is to demonstrate the use of the finite element method (FEM) to model electronic boards subjected to electrical, thermal and vibratory stresses. The study of electrical, thermal and mechanical behavior of a mechatronic device is presented. Two types of coupling of physical phenomena are described. The first is strong coupling: it uses finite elements with all degrees of freedom necessary for an electro-thermo-mechanical study. The second is weak coupling which consists of decoupling the three physical phenomena by using a sequential calculation. This method is applied in two scenarios. The first is an electronic board of an engine control unit. The second is a radar power amplifier. To understand the mechanical behavior of the electronic board, it is necessary to model several physical phenomena. A multiphysical model is presented which takes into account the interdependencies and interactions between the various physical phenomena: electrical, thermal and vibratory.

10 – Study on the Thermomechanical Fatigue of Electronic Power Modules for Traction Applications in Electric and Hybrid Vehicles (IGBT)

Abstract: The reliability of the power module is mainly related to that of its electronic components (IGBT power chips and diodes). These components undergo severe and varied stresses. Indeed, the electrical pulses due to the internal operations of these components cause thermal loadings inducing mechanical deformations which can go beyond the thresholds desired. Furthermore, these electronic components are subjected to vibrations which can affect the state the solder joints and the electrical wire connections, causing damage by thermomechanical fatigue. To this end, knowledge of the mechanical response of the power module is vital for the electronics industry as these modules fulfill strategic functions, as is the case for electric and hybrid vehicles. Knowledge of the mechanical behavior of this power module requires the modeling of several physical phenomena. Multi-physical modeling aims at considering the interdependencies and interactions between different physical phenomena such as electrical, thermal and mechanical. In this study, multi-physical coupling is performed using ANSYS software.

Reliability-Based Design Optimization and Its Applications to Interaction Fluid Structure Problems

The objectives of this work are to quantify the influence of material and operational uncertainties on the performance of structures coupled with fluid, and to develop a reliability-based design and optimization (RBDO) methodology for this type of the structures. Such a problem requires a very high computation cost, which is mainly due to the calculation of gradients, especially when a finite element model is used. To simplify the optimization problem and to find at least a local optimum solution, two new methods based on semi-numerical solution are proposed in this chapter. The results demonstrate the viability of the proposed reliability-based design and optimization methodology relative to the classical methods, and demonstrate that a probabilistic approach is more appropriate than a deterministic approach for the design and optimization of structures coupled with fluid.