Dynamic Traffic Feedback Data Enabled Energy Management in Plug-in Hybrid Electric Vehicles PROJECT TITLE :Dynamic Traffic Feedback Data Enabled Energy Management in Plug-in Hybrid Electric VehiclesABSTRACT:Recent advances in traffic monitoring systems have made real-time traffic velocity information ubiquitously accessible for drivers. This paper develops a traffic data-enabled predictive energy management framework for a power-split plug-in hybrid electrical vehicle (PHEV). Compared with conventional model predictive management (MPC), an additional supervisory state of charge (SoC) planning level is built based mostly on real-time traffic knowledge. A power balance-primarily based PHEV model is developed for this higher level to rapidly generate battery SoC trajectories that are used as final-state constraints within the MPC level. This PHEV energy management framework is evaluated under three completely different situations: one) while not traffic flow information; a pair of) with static traffic flow info; and three) with dynamic traffic flow info. Numerical results using real-world traffic information illustrate that the proposed strategy successfully incorporates dynamic traffic flow knowledge into the PHEV energy management algorithm to achieve enhanced fuel economy. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Adhesive RFID Sensor Patch for Monitoring of Sweat Electrolytes The Advantages of Forgetery [Lecture Notes]