Abstract:
Plug-in hybrid electric vehicles (PHEVs) provide a good alternative in achieving better
performance and in the reduction of harmful gas emissions. The hybrid energy storage
system (HESS) and the integrated charging unit constitute the PHEV under consider ation. To meet the load demands, the proposed HESS is a coupled system comprising
a fuel cell, high energy density battery, and high-power density super-capacitor. On board charging involves the utilization of a DC–DC buck converter and an uncontrolled
rectifier and two buck-boost converters are utilized to facilitate a smooth transfer of
energy. A rule-based supervisory controller has been implemented, which takes into
account the state of charge of energy sources and also the total power inflow of the
power sources. A model predictive control (MPC) technique is implemented to ensure
that PHEVs function smoothly in terms of regulation of DC bus voltage and tracking
of current. Unit prediction horizon i.e. only one step ahead looking into the future is
considered for the MPC to make it computationally less expensive. MPC is designed in
such a way that its performance is close to our favorite linear controller which in our case
is the H∞ controller. The inverse optimal control technique is used for determining the
weight matrices for MPC. The proposed controller has been simulated using MATLAB
and performance is compared with linear matrix inequality based H∞ optimal control
to prove that its performance is similar to that of H∞ controller. Also, the performance
comparison is made between the designed MPC and the non-linear control approach i.e.
sliding mode control to show that it achieves comparable or superior performance to the
non-linear controller. The real-time performance of H∞ based MPC is verified using
controller hardware in the loop experimental setup.
