Design of multi-sensor fusion water state observer for proton exchange membrane fuel cell based on particle filter

Inadequate water management undermines the reliability and durability of proton exchange membrane fuel cells (PEMFCs). Thus, it is necessary to identify the internal water state of the PEMFC accurately and control it within a reasonable range. The internal state of the PEMFC can be estimated online by simplifying the mechanism model. However, existing models neglect critical factors like water distribution across flow channels, gas diffusion layers, and catalyst layers, as well as the water content in the ionomer, liquid saturation, and vapor pressure within the membrane. Thus, in this work, a simplified mechanism model of PEM containing water content in ionomer, liquid water, and water vapor is established. Then, the influence of measurement noise and process noise set values on the performance of the observer is analyzed. The observer can exhibit the best performance when the noise variance is set as 10⁻⁴ and the process noise is set as 10⁻⁸ to match the actual noise variance. Finally, an internal state observer based on the model and the particle filter algorithm is developed. Based on the simulation, the internal water state trend of the PEMFC is analyzed, and the performance of the state observer based on voltage, high frequency resistance, and sensor signal fusion is compared. The results show that the observer based on sensor signal fusion is good at observing the water state.