An Efficient Optimum Energy Management Strategy Using Parallel Dynamic Programming for a Hybrid Train Powered by Fuel-Cells and Batteries

A parallel Dynamic Programming algorithm, basing on the matrix calculation, is used to develop the optimum energy management strategy for a fuel cell and lithium-ion battery hybrid train. In this paper, besides the state of charge of the battery, the power from the fuel cell is defined as the other state variable. Then, the control variable is the power change rate in the fuel cell system. With the help of this problem formulation, an efficient parallel Dynamic Programming is easy to implement. The parallel calculation requires only one loop over the time stages. To make the parallel Dynamic Programming basing on the matriculated calculation successful, a semi- physical soft constraints mechanism is developed to initialize the cost function at the end time stage properly. With this parallel Dynamic Programming, the effect of a weighting factor between maximizing the fuel economy and avoiding high dynamic power change of fuel cell, on the total hydrogen consumption is investigated time efficiently.