The multi-stack fuel cell system based on proton exchange membrane fuel cell has gained increasing attraction in high-power transportation applications. However, the real-time coordinated optimization among multiple fuel cell systems still remains a promising problem. To achieve the online collaborative performance enhancement between fuel economy and durability for the parallel multi-stack architecture, an increment-oriented power distribution strategy is proposed in this paper. It is inspired by the quadratic polynomial formulation derived from the hydrogen consumption analysis of integrated fuel cell system. The quantitative correlation between the fuel economy and durability is obtained with analytical power increments. To improve the strategy applicability with fault tolerance, iterative high-order sliding-mode differentiation procedure is utilized in the initial condition determination. Besides, performance-dominated power limits are considered in the global switching sequence calculation. The effectiveness and practicability of the proposed strategy are verified by two designed scenario cases with one-cycle short-term and life-cycle long-term evaluations. Detailed simulation results demonstrate that the proposed strategy can guarantee fault tolerance operation and collaborative performance enhancement for multi-stack fuel cell systems with minimum hydrogen consumption and maximum service life compared with other advanced strategies.

基于质子交换膜燃料电池的多堆燃料电池系统在大功率运输应用中越来越受到关注。然而，多个燃料电池系统之间的实时协调优化仍然是一个有前途的问题。为了实现并行多堆架构的燃油经济性和耐久性之间的在线协同性能提升，本文提出了一种面向增量的配电策略。它的灵感来自于集成燃料电池系统的氢消耗分析的二次多项式公式。燃油经济性和耐久性之间的定量相关性是通过分析功率增量获得的。为了提高具有容错性的策略适用性，在初始条件确定中使用迭代高阶滑模微分程序。此外，在全局开关序列计算中考虑了性能主导的功率限制。所提出策略的有效性和实用性通过两个设计场景案例进行了验证，这些案例具有单周期短期评估和生命周期长期评估。详细的仿真结果表明，与其他先进策略相比，所提出的策略能够以最小的氢消耗和最长的使用寿命保证多堆燃料电池系统的容错运行和协同性能增强。所提出策略的有效性和实用性通过两个设计场景案例进行了验证，这些案例具有单周期短期评估和生命周期长期评估。详细的仿真结果表明，与其他先进策略相比，所提出的策略能够以最小的氢消耗和最长的使用寿命保证多堆燃料电池系统的容错运行和协同性能增强。所提出策略的有效性和实用性通过两个设计场景案例进行了验证，这些案例具有单周期短期评估和生命周期长期评估。详细的仿真结果表明，与其他先进策略相比，所提出的策略能够以最小的氢消耗和最长的使用寿命保证多堆燃料电池系统的容错运行和协同性能增强。