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For urban rail transit (URT) operating companies, short-time passenger flow forecasting is a complex and critical task that determines the formulation and arrangement of operation plans and timetables. The automatic fare collection (AFC) system of URT provides detailed passenger flow data, which supports short-time passenger flow forecasting. This study proposes a combined model of Chaotic Sparrow Search Algorithm and Long Short-term memory artificial neural network (CSSA-LSTM) based on station classification. The model classifies stations based on various indicators such as point of interest (POI) data in the radiation area of Hangzhou, utilizes complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to denoise and smooth passenger flow data. It also conducts short-time passenger flow prediction and cross-validation for different stations by using the proposed model. To demonstrate the accuracy of the model, evaluation metrics such as R-squared and RMSE are introduced, and the results of the CSSA-LSTM model are compared with those of the LSTM, PSO-LSTM, and SSA-LSTM models. The experimental results show that the CSSA-LSTM model can effectively improve prediction accuracy, with R-squared increasing by 14.80%, 8.60%, and 6.82% compared to the other three algorithms, respectively. In addition, the cross-validation results of different stations prove the wide applicability of the CSSA-LSTM model, and this study have practical significance for URT planning and management. [ABSTRACT FROM AUTHOR]

To accurately estimate the effect of driving conditions on vehicle emissions, an on-road light-duty vehicle emission platform was established based on OEM-2100TM, and each second data of mass emission rate corresponding to the driving conditions were obtained through an on-road test. The mass emission rate was closely related to the velocity and acceleration in real-world driving. This study shows that a high velocity and acceleration led to high real-world emissions. The vehicle emissions were the minimum when the velocity ranged from 30 to 50 km/h and the acceleration was less than 0.5 m/s². Microscopic emission models were established based the on-road test, and single regression models were constructed based on velocity and acceleration separately. Binary regression and neural network models were established based on the joint distribution of velocity and acceleration. Comparative analysis of the accuracy of prediction and evaluation under different emission models, total error, second-based error, related coefficient, and sum of squared error were considered as evaluation indexes to validate different models. The results show that the three established emission models can be used to make relatively accurate prediction of vehicle emission on actual roads. The velocity regression model can be easily combined with traffic simulation models because of its simple parameters. However, the application of neural network model is limited by a complex coefficient matrix. [ABSTRACT FROM AUTHOR]

In this work, the ceramic coating separator (CCS-CS) prepared with polyethylene (PE) separator, Al2O3 inorganic particles, carboxymethyl cellulose sodium (CMC) and styrene-butadiene rubber (SBR) mix binders is further modified by coating with a thin polydopamine (PDA) layer through a simple chemical deposition method. Compared with the bare ceramic coating separator, the PDA-modified CCS-CS (CCS-CS-PDA) exhibits excellent thermal stability, which shows no thermal shrinkage after storing at 200 °C for 30 min. Compared with the PE separator, both the uptake and wettability with the electrolyte and water of CCS-CS-PDA are improved significantly. Meanwhile, when saturated with liquid electrolyte, the CCS-CS-PDA also shows enabled high ionic conductance. Furthermore, the test of the electrochemical impedances changing with the temperatures suggests that only the PE separator exhibits no thermal shutdown behaviors and the CCS-CS separator only has a shutdown temperature range from 138 to 160 °C, while the CCS-CS-PDA shows a shutdown temperature range from 138 to more than 200 °C. The cells prepared with the CCS-CS-PDA also show stable repeated cycling performance and good rate capacity at room temperature. [ABSTRACT FROM AUTHOR]

A high throughput electrospinning process, directly from flat polymer solution surfaces induced by a moving insulating rod, has been proposed and demonstrated. Different rods made of either phenolic resin or paper with a diameter of 1–3 cm and a resistance of about 100–500 MΩ, has been successfully utilized in the process. The rod is placed approximately 10 mm above the flat polymer solution surface with a moving speed of 0.005–0.4 m s−1; this causes the solution to generate multiple liquid jets under an applied voltage of 15–60 kV for the tip-less electrospinning process. The local electric field induced by the rod can boost electrohydrodynamic instability in order to generate Taylor cones and liquid jets. Experimentally, it is found that a large rod diameter and a small solution-to-rod distance can enhance the local electrical field to reduce the magnitude of the applied voltage. In the prototype setup with poly (ethylene oxide) polymer solution, an area of 5 cm  ×  10 cm and under an applied voltage of 60 kV, the maximum throughput of nanofibers is recorded to be approximately144 g m−2 h−1. [ABSTRACT FROM AUTHOR]

Electrospun nanofiber membranes have been proved to enhance performances of Li-ion batteries, but their poor mechanical strength hinders their industrial application. This paper combines meltblown polyethylene terephthalate (PET) nonwoven and electrospun poly (vinylidene fluoride) (PVDF) membrane together to improve the mechanical property via hot-pressing, wherein a dried 3 wt% PVDF solution coating on PET nonwoven is used as a binder. The hot-pressing temperature is optimized to be 145 °C and the composite PET/PVDF separator exhibits an excellent mechanical property, whose transverse and longitudinal tensile strength could reach 13.70 and 34.85 MPa respectively. Compared with a commercial PP separator, the hot-pressed PET/PVDF membrane separator shows better wettability, higher thermal shrinkage and improved electrochemical performance as well. [ABSTRACT FROM AUTHOR]