Connected Optimal Predictive Control for Hybrid Vehicles

An innovative Connected Optimal Predictive Control is proposed in this paper for Connected Energy Management purposes applied to Hybrid Vehicles, for minimization of energy and CO2 during a given trip, according to the driving conditions that can be predicted by intelligent navigation systems with real-time connectivity to the Cloud [3]. The theory proposed for such real-time optimal predictive algorithms is based on the mathematical Pontryagin's Maximum Principle ("PMP") [1] [2], that provides general solutions for optimization of dynamic systems with integral criteria, under given constraints. Several technical approaches are presented to get feasible real-time solving computation for this dynamic optimization. The calculation of a "trip planning" becomes then possible in embedded controllers synchronized to more powerful servers and computers connected to the Vehicle. Significant gains of more than -10% of CO2 are demonstrated, maintaining acceptable perfoi lances and drivability.