Abstract
Due to increasing system complexity new applications and new challenges in powertrain calibration arise and the often used convex optimization algorithms might no longer be sufficient. Therefore advanced global optimization algorithms become necessary. In this paper the Particle Swarm Optimization (PSO) with some adaptions to real-world problems (e.g. a new update rule) is treated. By the example of two frequently found calibration issues, namely boost pressure calibration and supervisory control of hybrid vehicles, the use of the PSO is described, showing that this algorithm is a robust tool suitable for automotive model-based calibration tasks.
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