  Among the auxiliary loads in light-duty vehicles, the air conditioning system
is the single largest energy consumer. For electrified vehicles, the impact of
heating and cooling loads becomes even more significant, as they compete with
the powertrain for battery energy use and can significantly reduce the range or
performance. While considerable work has been made in the field of optimal
energy management for electrified vehicles and optimization of vehicle velocity
for eco-driving, few contributions have addressed the application of
energy-optimal control for heating and cooling loads.
  This paper proposes an energy management strategy for the thermal management
system of an electrified powertrain, based on Model Predictive Control.
Starting from a nonlinear model of the vapor compression refrigeration system
that captures the dynamics of the refrigerant in the heat exchangers and the
power consumption of the system, a constrained multi-objective optimal control
problem is formulated to reduce energy consumption while tracking a desired
thermal set point. An efficient implementation of MPC is proposed for real-time
applications by introducing a terminal cost obtained from the approximation of
the global optimal solution.
