Journal of Jilin University(Engineering and Technology Edition) ›› 2024, Vol. 54 ›› Issue (9): 2401-2413.doi: 10.13229/j.cnki.jdxbgxb.20231068

   

Temperature control of proton exchange membrane fuel cell thermal management system based on APSO-BP-PID control strategy

Lei SHANG1(),Ping YANG2,Xiang-guo YANG1(),Jian-xin PAN3,Jun YANG3,Meng-ru ZHANG1   

  1. 1.School of Naval Architecture，Ocean and Energy Power Engineering，Wuhan University of Technology，Wuhan 430063，China
    2.School of Transportation and Logistics Engineering，Wuhan University of Technology，Wuhan 430063，China
    3.Technology R&D Center，Wuhan Institute of Hydrogen and Fuel Cell Industrial Technology Co. ，Ltd. ，Wuhan 430064，China
  • Received:2023-10-09 Online:2024-09-01 Published:2024-10-28
  • Contact: Xiang-guo YANG E-mail:shanglei@whut.edu.cn;yangxiangguo123@163.com

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Abstract:

Aiming at solving the issues of slow response， system oscillation， large temperature fluctuation and strong coupling of the proton exchange membrane fuel cell thermal management system， this paper proposes a coolant flow following the current control， optimizes the PID control strategy of neural network based on adaptive particle swarm algorithm， and constructs a 125 kW proton exchange membrane fuel cell thermal management system on the Matlab/Simulink platform to analyze the flow distribution and heat exchange between components. Compared with PID control strategy optimized by neural network and traditional PID control strategy under different working conditions. -The simulation results show that the control strategy proposed in this paper can realize the decoupling of cooling fan and circulating water pump under different working conditions； Under the step signal test， the flow rate of the circulating water pump follows the current and responds quickly； Under the dynamic performance test， the air volume control of the cooling fan is achieved without overshoot and stable within 30 s， reducing the oscillation of the system， and both the temperature difference between the inlet and outlet coolant of the fuel cell stack and the fluctuation degree of the fuel cell stack voltage is decreased. The results indicate that the proposed control strategy achieves satisfying control performance.

Key words: power mechanical engineering, fuel cell, neural network, thermal management system, control strategy

CLC Number: 

  • TM911.4

Fig.1

Schematic diagram of thermal management system"

Fig.2

Fuel cell stack voltage model"

Table 1

Fuel cell related parameters"

参数数值
膜电极数量340片
双极板类型金属板
质子交换膜反应面积/cm2304
质子交换膜厚度/mm0.012 5
散热方式水冷
燃料电池堆温度/℃75

Fig.3

Polarization curve and power curve of 125 kW fuel cell stack at different temperatures"

Table 2

Rated work conditions parameters of 125 kW fuel cell stack"

参数数值参数数值
λ/［W·（m·K）-1］0.023Ist/A534
A/m21.972Ncells340
δ/m0.05σ/［W·（m2·K）-1］5.67×10-8
Δt/K50Tst/K348

Table 3

EPH1500H-00 fuel cell water pump parameter"

参数数值
使用介质温度/℃-40~95
额定流量/（L·min-1）210
额定扬程/m22
额定转速（r·min-1）6 950

Fig.4

Control strategy schematic"

Fig.5

APSO-BP-PID control strategy"

Fig.6

Schematic diagram of BP neural network structure"

Fig.7

Iteration curve and KP、KI and KD optimization curve"

Fig.8

APSO-BP-PID control strategy algorithm flowchart"

Fig.9

Comparison of polarization curve of 125 kW fuel cell"

Fig.10

Thermal management system validation diagram"

Fig.11

Step test comparison diagram"

Fig.12

Dynamic performance test comparison diagram"

Fig.13

Temperature difference fluctuation of the fuel cell stack inlet and outlet cooling water"

Fig.14

Degree of fluctuation in the voltage of fuel cell stack"

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