  In this paper, a multi-horizon model predictive controller (MH-MPC) is
developed for integrated power and thermal management (iPTM) of a power-split
hybrid electric vehicle (HEV). The proposed MH-MPC leverages an accurate
short-horizon vehicle speed preview and an approximate forecast over a longer
shrinking horizon till the end of the driving cycle. This multiple-horizon
scheme is developed to cope with fast and slow dynamics associated with power
and thermal responses. The main objective of the proposed MH-MPC is to minimize
fuel consumption and enforce the power and thermal constraints on the battery
state-of-charge and engine coolant temperature, while meeting the driving
(traction) and cabin air conditioning (heating) demands. The proposed MH-MPC
allows for exploiting the engine coolant as thermal energy storage, providing
more flexibility for the HEV energy flow optimization. The simulation results
show that the proposed MH-MPC provides near-optimal results in reference to the
Dynamic Programming (DP) solution with an affordable computational cost.
Moreover, compared with a more conventional MPC strategy, the MH-MPC can
leverage the speed previews with different resolutions effectively to achieve
the desired performance with satisfactory robustness.
