Optimization of Harvester System in embedded vehicle systems via Bond Graph modeling algorithm

In the vehicles field, suspension components like non-linear springs are widely used to develop car ride and handling performance. This paper proposes an application of a mechatronic modeling evolution strategy using the bond graph methodology (BGM) which significantly reduces the computational cost of ES induced by the 20-sim simulation connected to MATLAB-Simulink, which is the objective function in optimization problems. The proposed method aims to couple the Bond Graph modeling of the harvester system with the covariance matrix adaptation evolution strategy. The application of this Bond Graph methodology to replace the classical analysis in order to overcome the computational cost of fitness function evaluations (Analytic model), and improve the proposed harvester system which proves its efficiency and ability to avoid the problem of computational cost using together MATLAB-Simulink and 20-Sim and sequentially updated its fidelity (quality) is measured according to its ability in electrical power approximate ranking procedure.