A Two‐Layer Multiobjective Optimal Energy Management Strategy Considering Fuel Cell/Battery Lifetime

ABSTRACT To optimize the operating efficiency and extend the lifespan of the multistack fuel cell hybrid system (MFCHS), this paper proposes a two‐layer multiobjective optimal energy management strategy that considers the degradation of the fuel cell and the battery. Regarding the issues that power fluctuations damage the fuel cells' lifespan and high‐current charging and discharging lead to battery capacity decay, the first layer of the strategy adopts locally weighted scatterplot smoothing (LOWESS) to smooth the output power of the fuel cells and prevent the battery from operating under high‐current conditions. The second layer considers the uneven degree of degradation among the fuel cells and employs the dandelion optimizer (DO) algorithm to solve the objective function with an aging adaptive factor, optimizing the efficiency and lifespan. Meanwhile, the DO algorithm is enhanced by tent chaotic mapping and differential variation to improve the convergence speed and accuracy. Compared with the equivalent hydrogen consumption minimization strategy (ECMS) and the equal distribution strategy, the proposed strategy improves the average operating efficiency of the fuel cells, effectively reduces the degradation of the fuel cells and the capacity degradation of the battery, and maintains the performance consistency among the fuel cells.