Robustness and performance evaluations for simulation-based control and component parameter optimization for a series hydraulic hybrid vehicle

Simulation-based optimization is a useful tool in the design of complex engineering products. Simulation models are used to capture numerous aspects of the design problem for the objective function. Optimization results obtained can be assessed from various perspectives. In this study, component and control optimization of a series hydraulic hybrid vehicle is used as an application, and different robustness and performance aspects are evaluated. Owing to relatively high computational loads, efficient optimization algorithms are important to provide sufficient quality of results at reasonable computational costs. To estimate problem complexity and evaluate optimization algorithm performance, the definitions for information entropy and the related performance index are extended. The insights gained from various simulation-based optimization experiments and their subsequent analysis help characterize the efficiency of the optimization problem formulation and parameterization, as well as optimization algorithm selection with respect to parallel computation capabilities for further development of the model and optimization framework