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Technology advancement for on-road vehicles has gained significant momentumin the past decades, particularly in the field of vehicle automation andpowertrain electrification. The optimization of powertrain controls forautonomous vehicles typically involves a separated consideration of thevehicle's external dynamics and powertrain dynamics, with one key aspect oftenoverlooked. This aspect, known as flexible power demand, recognizes that thepowertrain control system does not necessarily have to precisely match thepower requested by the vehicle motion controller at all times. Leveraging thisfeature can lead to control designs achieving improved fuel economy by addingan extra degree of freedom to the powertrain control. The present researchinvestigates the use of an Approximate Dynamic Programming (ADP) approach todevelop a powertrain controller, which takes into account the flexibility inpower demand within the ADP framework. The formulation is based on anautonomous hybrid electric vehicle (HEV), while the methodology can also beapplied to other types of vehicles. It is also found that necessarycustomization of the ADP algorithm is needed for this particular controlproblem to prevent convergence issues. Finally, a case study is presented toevaluate the effectiveness of the investigated method.

Optimization of Power Control for Autonomous Hybrid Electric Vehicles with Flexible Power Demand