A New Optimal Power and Energy Management Approach Applied to a Fuel Cell/Supercap-Based Hybrid Powertrain System

In this contribution a new developed load profile prediction and control optimization approach is applied for a fuel cell/supercap-based hybrid powertrain, whose electrical components are arranged in a Range extender topology. The load profile prediction is based upon past track information. Dependent on the prediction performance, using a variable horizon length, this algorithm can be adapted. The prediction algorithm is combined with a control optimization approach, which is based on a Hamiltonian problem. Hereby the nonlinear dynamic models of the powertrain and the criteria for the optimization of different system properties for a considered time interval are included. The approach is applied both as Model Predictive Controller (MPC) and Dynamic Programming (DP) algorithm. The results show that using this approch a significant improvement of the performance with respect to efficiency, availability, and component lifetime can be obtained in relation to other approaches and also to previous results of the authors.