An adaptive sub-optimal energy management strategy for hybrid drive trains

Typically the energy management problem of a hybrid vehicle is formulated as anoptimization problem, where the optimal power split between the prime mover and the secondarypower converter is calculated o line based on a given driving cycle and solved numericallywith dynamic programming techniques. An important constraint is that the energy level ofthe secondary power source at the end is the same as in the beginning. In real live the futuredriving cycle is not known a priori, making it di cult to calculate the exact optimal powersplit beforehand. To arrive at a practical real time control algorithm, a sub-optimal controllaw can be applied, where the end-point constraint is replaced by a term in the cost functionthat accounts for the change in energy; in case of a hybrid electric vehicle it represents thefuel equivalence of the stored reversible energy. In this paper it is reasoned that the reversibleenergy contains also kinetic and potential energy of the vehicle as well as energ