Investigation of the Distribution of the Mass Transport and Reaction Rates in a Fuel Cell By the Integrated Fuel Cell System Simulator Including the Dynamics of Air, H2, and Cooling Systems

Abstract

:A model to estimate the distribution of the current density, pressure, flowrate, temperature, and gas composition in the through-plane and along-channel (1+1D) directions of a fuel cell (FC) was developed. The developed model was integrated to the FC system model of the 2nd-Generation MIRAI, state-of-the-art fuel cell electric vehicle (FCEV), and the controllers of the system components. The impacts of the dynamic operating conditions of the FC system components on the 1+1D distribution in a fuel cell were investigated with the developed model. Modeling method: The modeling method of the distribution in a fuel cell is depicted in Fig. 1. In this study, the distribution in the through-plane and along-channel (1+1D) directions is considered and the distribution in the across-channel direction (2D) is assumed to be uniform to ensure acceptable computational time. The anode and cathode channels are divided into 20 nodes in the along-the-channel direction, respectively. The mass, momentum, and energy balance between the adjacent nodes of the channels were expressed by the similar methods as the model developed in the authors’ past research [1]. The models of the mass transport and reactions in the through-plane direction of MEA developed in the authors’ past research [2] were connected to each node of the cathode and anode channels. The in-house numerical solvers which calculate the distribution of current density, flowrate, total pressure, partial pressure of each gas component, and temperature in 1+1D direction were implemented. This model was integrated to the FC system models of the 2nd-Generation MIRAI [1], state-of-the-art fuel cell electric vehicle (FCEV) [3], and controllers for H2, air, and cooling systems developed in the authors’ past research [4] as shown in Fig. 2 to investigate the interactions among the dynamics behaviors of the system components, controller specification, and distribution in a fuel cell. Results and discussion: The impacts of operating conditions of the fuel cell system components on the distribution in a fuel cell were investigated as shown in Table 1. In case 2 in Table 1, rotational speed of the hydrogen pump (HP) is increased and other variables changed accordingly. The dynamic target power shown in Fig. 3 was given to the system model as the input and simulation was done for 700 s. Figs. 4(a)–4(e) show the simulation results at 480 s. In case1, current density was lower due to the high cell resistance in the region of the nodes 1–12 as shown in Figs. 4(a) and 4(b). In this region, the PEM was intensively dried and the H2O activity in PEM was below 0.2 as shown in Fig. 4(c) due to the no-humidifier configuration in air system. The H2O flowrate in through-plane and along-channel direction at the anode channel became almost 0 as shown in Figs. 4(d) and 4(e), suggesting that H2O cannot be delivered on both the cathode and anode sides on this region. In case 2, where the gas flowrate of anode inlet was increased by accelerating hydrogen circulation pump, the current density was higher and the resistance was lower in the region of the nodes 4-12 as shown in Figs. 4(a) and 4(b). The H2O activity at PEM in this region excesses 0.2 following the increased H2O flowrate in along-channel direction at the anode channel as shown in Figs. 4(c)ｰ4(e). The mechanism of the interactions between the system operating condition and the distribution in a fuel cell was depicted in Fig. 5. The increase in HP rotational speed enlarged the humidity difference between anode and cathode, thus, the through-plane H2O transported from the cathode to the anode side around the cathode outlet region. It also enlarged the H2O transport in along-channel direction from the anode inlet to outlet by increasing the volumetric flowrate in the anode channel. Despite of the improvement of the distribution, HP power consumption increased from 125.9 W to 806.5 W following the acceleration of HP speed from 3009 rpm to 7200 rpm as shown in Table 1. It was demonstrated that the complicated relationships among the distribution of reaction and mass transport, the specifications of the system components, and controllers can be investigated with the proposed model. References : [1] S. Hasegawa, et al., ECS Trans., 109(15), 15–70 (2022).[2] S. Hasegawa, et al., ECS Trans., 104(8), 3–26 (2021).[3] T. Takahashi and Y. Kakeno, EVTEC 2021 Proceeding, No. B1.1 (2021).[4] S. Hasegawa, et al., Comput. Aided Chem. Eng, 49, 1123–1128 (2022). Figure 1