Abstract:
Plugin hybrid electric vehicles (PHEVs) solve major issue of fossil fuel de-
pendency, carbon gases emission and have far-reaching effects on the electric
transportation business. We assemble them from an on-board smart charger
to transfer the energy from grid to vehicle and a hybrid energy storage sys-
tem (HESS). In this study HESS is composed of the battery as the primary
power source and ultracapacitor (UC) as a secondary power source, con-
joined with two DC-DC bidirectional buck-boost converters. The on-board
charging unit comprises an AC-DC boost rectifier and DC-DC buck con-
verter. The state model of the system has been taken into account. The
control objectives are ensuring unitary power factor at the grid side, tight
voltage regulation of charger and DC bus, adapting varying parameters and
currents tracking despite the variation in load profile. To achieve the con-
trol objectives, adaptive supertwisting sliding mode controller (AST-SMC)
has been proposed. For optimizing the cost function of controller gains, we
have applied a genetic algorithm. For driving mode the switching between
dynamic and static behavior and for parking mode, vehicle to grid (V2G)
and grid to vehicle (G2V) operations are proposed. In order to make our
nonlinear control intelligent for performing the V2G and G2V functionality,
enhanced performance, and battery life the state of charge based high-level
controller has been proposed. A standard Lyapunov stability criteria has
been verified for the system to ensure asymptotic stability. The compari-
son of the proposed controller has been presented considering sliding mode
controller (SMC) and finite time synergetic controller (FTSC) as comparison
controllers using MATLAB/Simulink. Also, the hardware in loop setup has
been used to validate the performance in real-time.
