Plant and Controller Optimization for Power and Energy Systems With Model Predictive Control

Abstract This article explores the optimization of plant characteristics and controller parameters for electrified mobility. Electrification mobile transportation systems, such as automobiles aircraft, presents ability to improve key performance metrics efficiency cost. However, strong bidirectional coupling between electrical thermal dynamics within new components creates integration challenges, increasing component degradation, reducing performance. Diminishing these issues requires novel designs control strategies. The mobility literature provides prior studies on optimization, known co-design (CCD). A void is lack model predictive (MPC), recognized manage multi-domain CCD frameworks. addresses this through three contributions. First, a thermo-electromechanical hybrid electric vehicle (HEV) powertrain developed that suitable both MPC. Second, simultaneous performed system. Third, MPC integrated framework using candidate HEV model. Results indicate optimizing simultaneously can reduce physical sizes by over 60% metric errors 50%.