Online extremum seeking-based optimized energy management strategy for hybrid electric tram considering fuel cell degradation

In order to realize optimal power distribution between proton exchange membrane fuel cell and supercapacitor in hybrid electric tram, an online extremum seeking-based optimized energy management strategy is proposed this work. Considering that the a complex nonlinear system, its performance will vary as external parameters change, so it necessary consider state of stack. An seeking algorithm investigated work seek maximum efficiency points by searching variation performance. Besides, also updates “safe operating zone” based on results seeking. This process achieved adaptive recursive least square algorithm. Furthermore, limit dynamic cell, degradation stack considered study. To guarantee stable continued operation charge fluctuation range limited. The effectiveness presented method successfully verified under scaled-down condition tram reduced-scale test platform. compared with machine control equivalent consumption minimization further demonstrate has advantages hydrogen consumption, fluctuation, efficiency, output dynamics.