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PROJECT TITLE :

Predictive Control of a Battery/Ultracapacitor Hybrid EnergyStorage System in Electric Vehicles - 2016

ABSTRACT:

This manuscript presents a predictive control strategy for a battery/ultracapacitor (UC) hybrid energy storage system (HESS) in an electric vehicle (EV). This predictive control strategy is intended to optimize the ability split between the battery pack and the UC pack so as to increase the battery lifetime and improve the HESS operation efficiency. The real-time implementation feasibility of this predictive management strategy has been validated in a very closed-loop system through both simulation and the hardware-in-the-loop (HIL) testing. A combination of fast control prototyping and HIL testing is implemented using an xPC Target real-time experimental platform. The controller and therefore the plant within the closed-loop system are interfaced with I/O ports, that facilitate the exchange of analog and digital signals. The HIL testing results and therefore the simulation results are presented and compared.


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