Simulation of PEMFC Voltage Stabilization System for Underwater Unmanned Power Platform Based on Fuzzy Control
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摘要: 针对水下无人动力平台对高效、稳定能源系统的需求, 文中聚焦质子交换膜燃料电池(PEMFC)输出电压强非线性、易波动的难题, 提出一种基于模糊比例-积分-微分(PID)自适应控制的DC-DC变换器稳压策略。PEMFC输出电压因强非线性特性且易波动, 传统控制方法在动态响应与鲁棒性上存在局限。为此, 建立了PEMFC数学模型(含能斯特电压及活化、欧姆、浓差损失)及Boost升压电路模型, 剖析其电压波动机理。设计了一种模糊PID控制器, 其规则库深度耦合PID控制原则与PEMFC非线性特性, 实现了比例、积分、微分参数的在线动态自整定, 从而实时优化DC-DC变换器占空比。结果表明: 相较于传统PID, 模糊PID控制可将系统调节时间缩短, 稳态误差趋近于零, 在电流突变工况下输出电压波动范围缩小至±0.5 V以内, 且占空比响应更精准。该模糊PID自适应策略显著增强了系统的动态响应速度与鲁棒性, 为水下无人平台能源心脏的高效、稳定波动提供了可靠的理论基石与解决方案。Abstract: Aiming at the demand of underwater unmanned power platform for efficient and stable energy system, this paper focuses on the problem of strong nonlinearity and easy fluctuation of the output voltage of proton exchange membrane fuel cell (PEMFC), and proposes a DC-DC converter voltage stabilization strategy based on the fuzzy PID adaptive control.Due to the strong nonlinear characteristics of the output voltage of the PEMFC and its easy to fluctuate, the traditional control methods have limitations in the dynamic response and robustness. limitations of traditional control methods in terms of dynamic response and robustness. In this study, a mathematical model of PEMFC (including Nernst voltage and activation, ohmic, and concentration loss) and a Boost boost circuit model are established to analyze the voltage fluctuation mechanism. The core innovation lies in the design of a fuzzy PID controller with a rule base that deeply couples the PID control principle with the nonlinear characteristics of PEMFC, which realizes the online dynamic self-tuning of proportional, integral, and differential parameters to optimize the DC-DC converter duty cycle in real time. The results show that compared with the traditional PID, the fuzzy PID control can shorten the system regulation time , the steady-state error tends to be close to zero, the output voltage fluctuation range is narrowed to within ±0.5V under the sudden current change condition, and the duty cycle response is more accurate. The fuzzy PID adaptive strategy significantly enhances the dynamic response speed and robustness of the system, providing a reliable theoretical cornerstone and solution for the efficient and stable fluctuation of the energy heart of the underwater unmanned platform.
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图 6 Boost升压电路Simulink仿真结果
Figure 6. Simulink simulation results of Boost boost circuit
图 8 模糊PID控制PEMFC稳压系统的原理
Figure 8. Principle of fuzzy PID control PEMFC voltage stabilization system
图 14 基于模糊PID的PEMFC稳压系统的仿真图
Figure 14. Simulation of fuzzy PID based PEMFC voltage stabilization system
图 19 不同控制器下系统偏差变化率
Figure 19. Rate of change of system deviation with different controllers
表 1 PEMFC主要参数
Table 1. Main parameters of PEMFC
参数 值 参数 值 n/个 35 l/cm 0.04 T工作温度/K 323 A/cm2 60 PH2/atm 0.5 λ 20 PO2/atm 0.3 B 0.016 I工作电流/A 16 imax/ (A/cm2) 1.5 尺寸/mm 104×67×120 Cst/kJ/(kg·K) 0.71 Mst/kg 1.08 理想工作温度/K 318.15~327.15 注: T工作温度为PEMFC的工作温度; I工作电流为工作电流; Mst为PEMFC的质量; Cst为PEMFC。 
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表 3 Boost升压电路参数表
Table 3. Parameter list of Boost boost circuit
参数 值 参数 值 η 1(仿真时) d 0.46 P/W 416 L/μH 100 Fs/Hz 25 000 C/μF 330
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表 4 模糊控制器的模糊规则表Kp
Table 4. Fuzzy rule table for fuzzy controller Kp
E Ec NB NM NS Z PS PM PB NB Z Z Z Z PS PS PS NM Z Z Z Z PS PS PS NS PS PS PS PS PS PM PM Z PS PS PS PS PS PM PM PS PM PM PM PM PM PB PB PM PM PM PM PM PM PB PB PB PM PM PM PM PM PB PB
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表 5 模糊控制器的模糊规则表Ki
Table 5. Table of fuzzy rules for fuzzy controller Ki
E Ec NB NM NS Z PS PM PB NB NB NB NM Z NM NM Z NM NB NB NM NS NS Z Z NS NB NM Z Z Z PS Z Z NM NM NS Z PS PM PM PS Z NS Z PS PS PM PB PM Z Z PS PM PM PB PB PB Z Z PS PM PM PB PB
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表 6 模糊控制器的模糊规则表Kd
Table 6. Table of fuzzy rules for fuzzy controller Kd
E Ec NB NM NS Z PS PM PB NB NS NS NS NS NS PS PS NM NS NS NS NS NS PS PM NS NS NS NS Z Z PS PM Z NS NS NS Z Z PS PM PS NS NS Z Z Z PS PM PM NS NS Z PS PS PS PB PB NS NS Z PS PS PS PM
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