STUDY ON VEHICULAR PEMFC HUMIDITY ESTIMATE BASED ON SOFT SENSING TECHNOLOGY

Automotive proton exchange membrane fuel cell humidity has a significant impact on its output performance, and which will strongly affect the performance of vehicle power-driven. This paper analyzes the main parameters which impact the proton exchange membrane fuel cell water content, improves orthogonal least squares algorithm, and establishes RBF neural network model based on the relationship among water content in proton exchange membrane fuel cell and internal resistance, temperature and Current density, etc. By taking the proton exchange membrane fuel cell runtime data in a 50 KW experimental Vehicle, the simulation results show that the model output humidity value reaches the preset moisture estimation accuracy.