Adaptive online energy management considering lifespan decay synergy for fuel cell-battery system

To reduce maintenance costs and extend the service life of fuel cell hybrid electric vehicles (FCHEVs), it is essential to achieve consistent degradation between the fuel cell and battery. However, existing energy management strategies (EMSs) often minimize the degradation of each power source independently, overlooking their synergistic decay potential. This paper proposes a novel online model predictive control (MPC)-based EMS with adaptive weighting factors to address this issue. The method incorporates two objectives: 1) minimizing total operating cost, which includes hydrogen consumption, state of charge (SOC) deviation, and component degradation. 2) Reducing the degradation disparity between the fuel cell and battery. To achieve both objectives, a modified momentum gradient descent algorithm is employed to adaptively update the weighting factors based on real-time degradation states. These updated weights are then applied to the cost function of the primary objective, allowing the EMS to balance cost minimization and degradation consistency. Real-time simulations under standard driving cycles demonstrate the method's ability to synchronize degradation trajectories. Compared to conventional EMS approaches, the proposed strategy reduces overall degradation and achieves up to 91.52 % consistency improvement between the fuel cell and battery, enhancing system durability and economic efficiency. The main contributions of this article are explained as follows. ➢ MPC-based EMS minimizes cost and ensures balanced degradation of fuel cell and battery. ➢ Adaptive weighting enables online EMS and considers fuel cell-battery degradation synergy. ➢ An adaptive gradient descent algorithm is proposed to tune weights and speed convergence.