  Technology advancement for on-road vehicles has gained significant momentum
in the past decades, particularly in the field of vehicle automation and
powertrain electrification. The optimization of powertrain controls for
autonomous vehicles typically involves a separated consideration of the
vehicle's external dynamics and powertrain dynamics, with one key aspect often
overlooked. This aspect, known as flexible power demand, recognizes that the
powertrain control system does not necessarily have to precisely match the
power requested by the vehicle motion controller at all times. Leveraging this
feature can lead to control designs achieving improved fuel economy by adding
an extra degree of freedom to the powertrain control. The present research
investigates the use of an Approximate Dynamic Programming (ADP) approach to
develop a powertrain controller, which takes into account the flexibility in
power demand within the ADP framework. The formulation is based on an
autonomous hybrid electric vehicle (HEV), while the methodology can also be
applied to other types of vehicles. It is also found that necessary
customization of the ADP algorithm is needed for this particular control
problem to prevent convergence issues. Finally, a case study is presented to
evaluate the effectiveness of the investigated method.
