Abstract An innovative optimal predictive control strategy is proposed in this paper for connected energy management purposes applied to hybrid vehicles, for minimization of energy usage and CO2 emissions during a given trip, according to the driving conditions that can be predicted by intelligent navigation systems with real-time connectivity to the cloud. The theory proposed for such real-time optimal predictive algorithms is based on the mathematical Pontryagin’s maximum principle 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 computational effort 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 emissions are demonstrated, maintaining acceptable performances and drivability.
Optimal Predictive Control for Intelligent Usage of Hybrid Vehicles
2016-01-01
18 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Optimal control , Pontryagin’s maximum principle , Predictive control , Model-based control , Hybrid vehicles , Trajectory optimization , Torque efficiency optimization , Eco-Driving , Electronic horizon (eHorizon) , Human machine interface , Driver assistance , Real-time control , Embedded software Engineering , Automotive Engineering , Transportation , Transportation Technology and Traffic Engineering , Sustainable Development , Circuits and Systems
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