An iterative algorithm for the global optimal predictive control of hybrid electric vehicles

Increasing energy storage capacities, especially in plug-in hybrid vehicles, lead to high computational burden using conventional methods like dynamic programming (DP) for globally solving the control problem. DP with its high calculation times may be acceptable for offline simulations, but used as a predictive adaption algorithm for the main decision criterion of a real-time ECMS (equivalent consumption minimization strategy) a more feasible solution has to be found [1]. Hence, in this paper an approach replacing the originally implemented predictive dynamic programming (PDP) by a fast iterative algorithm is presented and compared to the results gained by DP with respect to computational effort and optimality.