This article describes an attempt for a real-time optimization of thermal and power management to minimize energy consumption of vehicles applying nonlinear model predictive control (NMPC). The main scope of application lies on the shortage management of thermal energy during cold starts regarding the high thermal comfort demand of passengers at low ambient temperatures. NMPC as one method for a real-time optimization of relevant control variables uses a simplified nonlinear mathematical overall vehicle model and information about the actual state of the vehicle as well as the predicted driving condition to compute an optimal course of control variables in real-time. Therefore, a Modelica model library for satisfactorily accurate, fast vehicle models was developed. By means of the developed tool chain, virtual simulation experiments with a parallel hybrid electric vehicle could be realized.
Nonlinear Model Predictive Control for Thermal and Electrical Power Management for Parallel Hybrid Electric Vehicles
2014
22 Seiten, Bilder, Tabellen, 11 Quellen
Conference paper
English
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