Powertrain Energy Management for Autonomous Hybrid Electric Vehicles With Flexible Driveline Power Demand

The need for less fuel consumption and the trend of more autonomous vehicles together urge the power optimization in autonomous hybrid vehicles (HVs). However, in most existing research, the vehicle level control and the hybrid powertrain level energy management are treated as separate subjects, and the powertrain management control always follows the required power demand from the vehicle level controller. This fact significantly restricts achieving full fuel saving potential enabled by powertrain hybridization and vehicle autonomy. In this brief, we introduce a flexible power demand architecture, where we give flexibility to the driveline power demand so the powertrain control does not need to exactly track the power demand from the vehicle level. This can give an extra degree of freedom in the powertrain energy management so that better fuel economy can potentially be achieved. The focus of this brief is on a new powertrain management method that can effectively leverage this flexibility. First, the trajectory and power demand are obtained from the vehicle level control and are used as a baseline for hybrid powertrain energy management. Next, the powertrain management with flexible power demand problem is formulated by incorporating the baseline optimal trajectory. Finally, the optimization problem is solved using the Pontryagin's minimum principle. By approximating the optimal instantaneous fuel consumption rate as a polynomial of the engine speed, the optimal conditions can be converted into a set of algebraic equations. To verify the efficacy of the proposed methodology, a motivating numerical example of multiple connected HVs in pursuit of a leader vehicle is considered.