Optimization of solder joints in embedded mechatronic systems via Kriging-assisted CMA-ES algorithm

In power electronics applications, embedded mechatronic systems (MSs) must meet the severe operating conditions and high levels of thermomechanical stress. The thermal fatigue of the solder joints remains the main mechanism leading to the rupture and a malfunction of the complete MS. It is the main failure to which the lifetime of embedded MS is often linked. Consequently, robust and inexpensive design optimization is needed to increase the number of life cycles of solder joints. This paper proposes an application of metamodel-assisted evolution strategy (MA-ES) which significantly reduces the computational cost of ES induced by the expensive finite element simulation, which is the objective function in optimization problems. The proposed method aims to couple the Kriging metamodel with the covariance matrix adaptation evolution strategy (CMA-ES). Kriging metamodel is used to replace the finite element simulation in order to overcome the computational cost of fitness function evaluations (finite element model). Kriging is used together with CMA-ES and sequentially updated and its fidelity (quality) is measured according to its ability in ranking of the population through approximate ranking procedure (ARP). The application of this method in the optimization of MS proves its efficiency and ability to avoid the problem of computational cost.