Extending Energy Management in Hybrid Electric Vehicles with explicit control of gear shifting and start-stop

The Energy Management System (EMS) in Hybrid Electric Vehicles (HEV) determines the optimal use of the available power resources to reduce the total fuel energy over a drive cycle. A real-time EMS that includes start-stop and gear selection in an optimal control framework, could not be found in literature. In this paper, a model-based controller is designed that solves the optimal control problem for a given equivalency between the energy sources, including the discrete control of start-stop and shifting. By approximating a validated vehicle model with piecewise affine functions, the controller converts to a Mixed-Integer Linear Program (MILP), which can be explicitly solved and stored on a real-time controller. In simulation the controller is able to outperform an EMS with heuristic control of start-stop and shifting: on a proprietary drive cycle, the number of gear shift events is reduced by 42%, the number of start-stop events is reduced by 6%, while at the same time fuel economy is improved by 0.3%.