Flexible predictive power-split control for battery-supercapacitor systems of electric vehicles using IVHS

The utilization of traffic information received from intelligent vehicle highway systems (IVHS) to plan velocity and split output power for multi-source vehicles is currently a research hotspot. However, it is an open issue to plan vehicle velocity and distribute output power between different supply units simultaneously due to the strongly coupling characteristic of the velocity planning and the power distribution. To address this issue, a flexible predictive power-split control strategy based on IVHS is proposed for electric vehicles (EVs) equipped with battery-supercapacitor system (BSS). Unlike hierarchical strategies to plan vehicle velocity and distribute output power separately, a monolayer model predictive control (MPC) method is employed to optimize them online at the same time. Firstly, a flexible velocity planning strategy is designed based on the signal phase and time (SPAT) information received from IVHS and then the Pontryagin's minimum principle (PMP) is adopted to formulate the optimal control problem of the BSS. Then, the flexible velocity planning strategy and the optimal control problem of BSS are embedded into an MPC framework, which is online solved using the shooting method in a fashion of receding horizon. Simulation results verify that the proposed strategy achieves a superior performance compared with the hierarchical strategy in terms of transportation efficiency, battery capacity loss, energy consumption and computation time.