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Proton exchange membrane fuel cells are promising in the application of new energy vehicles and other fields. The performance test and analysis are critical components of the fuel cell research. A general procedure for data processing model and performance analysis method of fuel cell stacks were introduced based on a demonstration project of commercial fuel cell buses in Shanghai. To build the data processing model, the fixed node method was used to extract the effective operating data of fuel cell stack from the vehicle database. After data cleaning and conversion, taking fuel cell reversible recession into account, the processed data can be obtained. Data that had been processed and a semi-empirical model were used to accurately fit the polarization curve. Polarization curve is a pivotal approach to describe the performance of fuel cells.

Real driving emission (RDE) tests are influenced by factors such as data processing methods, driving behaviors, and environmental conditions. Therefore, being able to effectively identify test influence factors is particularly important for RDE emissions-based calibrations. In order to investigate the correlation between data processing methods, driving behaviors and vehicle emissions, the moving average window (MAW) method and cumulative averaging (CA) method were used to compare and analyze the RDE tests data of a light-duty gasoline vehicle under different driving modes in this study. The results showed that in MAW method, carbon monoxide (CO) emissions of urban and total trips calculated by using the front to back window division order were slightly lower compared to the back to front window division order, with an average reduction of 4.68% and 6.33%, respectively. For carbon dioxide (CO2) emissions, the order of window division had the opposite effect as for CO emissions.

A driver steering model for emergency lane change based on the China naturalistic driving data is proposed in this paper. The steering characteristic of three phases is analyzed. Using the steering primitive fitting by Gaussian function, the steering behaviors in collision avoidance and lateral movement phases can be described, and the stabilization steering principle of yaw rate null is found. Based on the steering characteristic, the near and far aim point used in steering phases is analyzed. Using the near and far aim point correction model, a driver steering model for emergency lane change is established. The research results show that the driver emergency steering model proposed in this paper performs well when explaining realistic steering behavior, and this model can be used in developing the ADAS system.