Research on PTC Auxiliary Heating Starting Strategy Based on One-dimensional Multiphase Cold Start Stack Model

被引:0
|
作者
Lin, Shaofang [1 ]
Su, Jianbin [1 ,2 ]
Shi, Lei [2 ]
机构
[1] Fuzhou Polytech, 8 Lianrong Rd, Fuzhou 350108, Fujian, Peoples R China
[2] Tongji Univ, Sch Automot Studies, 4800 Caoan Rd, Shanghai 201804, Peoples R China
关键词
Fuel Cell; Cold Start; Auxiliary Heating Strategy; Bipolar Plate Material; Positive Temperature Coefficient Heating Power; FUEL-CELL STACK; PERFORMANCE; PARALLEL; CHANNEL; VOLTAGE; CATHODE; HYBRID;
D O I
10.5796/electrochemistry.24-00112
中图分类号
O646 [电化学、电解、磁化学];
学科分类号
081704 ;
摘要
The study investigates the optimization of auxiliary heating strategies during the cold start of fuel cells, analyzing the effects of factors such as bipolar plate materials, coolant types, positive temperature coefficient (PTC) heating power, initial current density, and coolant flow rate on cold start performance. The findings indicate that metal bipolar plates, due to their lower thermal mass, heat up faster than graphite bipolar plates, facilitating a quicker cold start. While coolant circulation enhances temperature distribution uniformity, it also increases the system's thermal mass. Increasing PTC heating power can accelerate the heating process, but it offers limited improvements in cold start performance and increases energy consumption. Under conditions of -20 degrees C, by optimizing parameters such as current density and coolant flow rate, the fuel cell stack can achieve a cold start in approximately 55 s, significantly improving cold start performance and reducing energy consumption. This research provides optimized strategies for the application of fuel cells in cold environments.
引用
收藏
页数:13
相关论文
共 3 条
  • [1] One-dimensional thermal model of cold-start in a polymer electrolyte fuel cell stack
    Khandelwal, Manish
    Lee, Sungho
    Mench, M. M.
    JOURNAL OF POWER SOURCES, 2007, 172 (02) : 816 - 830
  • [2] Identification of the cold start boundaries of proton exchange membrane fuel cells based on one dimensional multi-phase model
    Shi, Lei
    Du, Chang
    Liu, Ze
    Yi, Yahui
    Li, Ruitao
    Tang, Xingwang
    Su, Jianbin
    Qian, Liqin
    Ma, Tiancai
    RENEWABLE ENERGY, 2025, 240
  • [3] Research on the Application of the Radiative Transfer Model Based on Deep Neural Network in One-dimensional Variational Algorithm
    He, Qiu-rui
    Zhang, Rui-ling
    Li, Jiao-yang
    Wang, Zhen-zhan
    JOURNAL OF TROPICAL METEOROLOGY, 2022, 28 (03) : 326 - 342