【摘要】 质子交换膜燃料电池（PEMFC）的空气流量和压力之间耦合性强，导致电池系统输出稳定性差、响应速度慢等，针对此问题，基于空气供给系统前馈补偿解耦结构，提出采用蛇优化（SO）算法和模糊控制改进的自抗扰控制策略。基于前馈补偿解耦结构建立空气供给系统状态空间方程，推导流量、压力耦合矩阵，设计解耦矩阵消除二者的耦合性。设计改进自抗扰控制，将自抗扰控制中反馈控制律增益分为2部分，采用模糊控制对第1部分进行粗调；采用改进SO算法对自抗扰控制中状态观测器增益与反馈控制律增益第2部分参数精确整定。其中，改进SO算法融合了基于序列的正弦分段混沌映射（SPM）策略初始化种群，增强种群多样性；动态惯性权重和三角形游走策略解决了勘探阶段前期寻优速度慢等缺陷；透镜成像和贪婪组合策略扩大搜索范围，防止陷入局部最优解。搭建3 kW燃料电池系统，验证所提出控制策略的正确性和有效性。试验验证了该策略在解耦方面和目标值跟踪方面具有良好的控制效果，系统超调量、调节时间以及系统振荡显著减小，该策略提高了燃料电池系统的响应速度和动态性能。更多还原

【Abstract】 The strong coupling between air flow and pressure in proton exchange membrane fuel cells(PEMFC) results in poor output stability and slow response speed of cell systems. To address these issues, an improved active disturbance rejection control(ADRC) strategy incorporating snake optimization algorithm and fuzzy control was proposed based on the feedforward compensation decoupling structure of the air supply system. The state-space equations of the air supply system were established based on the feedforward compensation decoupling structure. A coupling matrix between flow and pressure was derived which was designed to eliminate the coupling between air flow and pressure. For the improved ADRC design, the feedback control law gain was divided into two parts: the first part was coarsely adjusted using fuzzy control, and the parameters for the second part of state observer gain and feedback control law gain were precisely tuned using the improved snake optimization algorithm. The improved snake optimization algorithm incorporated the chaotic mapping strategy using sequence-based particle swarm optimization method(SPM) for population initialization, enhancing population diversity. Dynamic inertia weights and triangular walk strategy addressed limitations such as slow optimization speed during the early exploration phase. Lens imaging and greedy combination strategies expanded the search range and prevented the algorithm from falling into local optima. A 3 kW fuel cell system was built to verify the correctness and effectiveness of the proposed control strategy. The experimental results showed that the proposed strategy achieved excellent control performance in terms of parameter decoupling and setpoint tracking. The strategy significantly reduced the overshoot, settling time, and oscillations, improving the response speed and dynamic performance of fuel cell system.更多还原