Search

Your search keyword '"Cai, Hongchang"' showing total 10 results
Start Over Author "Cai, Hongchang"
10 results on '"Cai, Hongchang"'

2. Research on Quantitative Diagnosis of Dendrites Based on Titration Gas Chromatography Technology.

Author

Yang, Kai, Cai, Hongchang, Li, Suran, Wang, Yu, Zhang, Xue, Wu, Zhenxuan, Lai, Yilin, Bezha, Minella, Bezha, Klara, Nagaoka, Naoto, Zheng, Yuejiu, and Feng, Xuning

Subjects
*DENDRITIC crystals, *GAS chromatography, *BATTERY storage plants, *NUCLEAR magnetic resonance, *NEGATIVE electrode, *CARBON nanofibers
Abstract

Lithium plating can cause capacity fade and thermal runaway safety issues in lithium-ion batteries. Therefore, accurately detecting the amount of lithium plating on the surface of the battery's negative electrode is crucial for battery safety. This is especially crucial in high-energy-density applications such as battery energy storage systems or in electric vehicles (EVs). Early detection of lithium plating is crucial for evaluation of reliability and longevity. It also serves as a method for early diagnostics in practical industrial applications or infrastructure, such as EV transportation. This can enhance its impact on customers. This study validates the effectiveness of titration gas chromatography (TGC) technology in quantitatively detecting lithium plating on graphite negative electrodes in lithium-ion batteries. The results show that it can detect a minimum of 2.4 μmol of metallic lithium. Compared with the heating direct current resistance and reference electrode methods, which can be used to perform only qualitative dendrite detection, TGC has a wider range of detection. Compared with the nuclear magnetic resonance (NMR) method with higher quantitative detection accuracy, the maximum difference between the detection results of the two methods was only 7.2%, but the TGC method had lower cost and higher implementation convenience. In summary, among various dendrite detection methods, the TGC method can not only realize the effective quantitative detection of lithium plating, but also comprehensively consider its detection range, implementation convenience, cost, and detection accuracy, indicating that it is suitable for engineering applications and has the prospect of realizing large-scale quantitative detection of lithium plating in lithium-ion batteries. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

3. Degradation Evaluation of Lithium-Ion Batteries in Plug-In Hybrid Electric Vehicles: An Empirical Calibration.

Author

Cai, Hongchang, Hao, Xu, Jiang, Yong, Wang, Yanan, Han, Xuebing, Yuan, Yuebo, Zheng, Yuejiu, Wang, Hewu, and Ouyang, Minggao

Subjects
PLUG-in hybrid electric vehicles, LITHIUM-ion batteries, ELECTRIC batteries, STANDARD deviations, CALIBRATION
Abstract

Battery life management is critical for plug-in hybrid electric vehicles (PHEVs) to prevent dangerous situations such as overcharging and over-discharging, which could cause thermal runaway. PHEVs have more complex operating conditions than EVs due to their dual energy sources. Therefore, the SOH estimation for PHEV vehicles needs to consider the specific operating characteristics of the PHEV and make calibrations accordingly. Firstly, we estimated the initial SOH by combining data-driven and empirical models. The data-driven method used was the incremental state of charge (SOC)-capacity method, and the empirical model was the Arrhenius model. This method can obtain the battery degradation trend and predict the SOH well in realistic applications. Then, according to the multiple characteristics of PHEV, we conducted a correlation analysis and selected the UF as the calibration factor because the UF has the highest correlation with SOH. Finally, we calibrated the parameters of the Arrhenius model using the UF in a fuzzy logic way, so that the calibrated fitting degradation trends could be closer to the true SOH. The proposed calibration method was verified by a PHEV dataset that included 11 vehicles. The experiment results show that the root mean square error (RMSE) of the SOH fitting after UF calibration can be decreased by 0.2–14% and that the coefficient of determination ( R 2 ) for the calibrated fitting trends can be improved by 0.5–32%. This provides more reliable guidance for the safe management and operation of PHEV batteries. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

6. A prediction method of geomagnetic disturbances based on IPS observations—dynamics—fuzzy mathematics

Author

Feng Xueshang, Wei Fengsi, Cai Hongchang, and Shi Jiankui

Subjects
Solar storm of 1859, Geomagnetic storm, Atmospheric Science, Disturbance (geology), Aerospace Engineering, Magnitude (mathematics), Astronomy and Astrophysics, Atmospheric sciences, Geophysics, Earth's magnetic field, Interplanetary scintillation, Space and Planetary Science, Approximation error, General Earth and Planetary Sciences, Interplanetary spaceflight, Mathematics
Abstract

A prediction method for geomagnetic disturbances, based on the interplanetary scintillation (IPS) observations, dynamics of interplanetary disturbance propagation and fuzzy mathematics, is suggested. The membership functions are established by using observational data on the solar storm, interplanetary and geomagnetic disturbance data in 1966–1982. Prediction tests are performed on 37 geomagnetic disturbance events caused by the solar storm-associated interplanetary disturbances, which are identified by the IPS observations during the descending solar activity phase 1984–1985. The relative error of the magnetic disturbance onset time ( δT T=7.4% ) is less than 10% for 50% of all the events and less than 20% for 70% of all the events. The relative error of the predicted magnetic disturbance magnitude ( δΔK p ΔK p ) is less than 30% for 80% of all events and greater than 60% for only 15% of all the events. In addition, the prediction test of April-May 1998 event gives the relative errors δT T=7.4% and δΔK p ΔK p = 15.3% . hese results show that the method suggested in this paper has proential prospects for improving the accuracy of the geomagnetic disturbance prediction made from IPS observations.

Published
2003

7. Global structure of solar mass output and magnetic fields

Author

Cai Hongchang, Zhou Qingjun, Feng Xueshang, Yao Jiusheng, and Wei Fengsi

Subjects
Physics, Atmospheric Science, Sunspot, Aerospace Engineering, Coronal hole, Astronomy, Astronomy and Astrophysics, Coronal loop, Corona, Computational physics, Nanoflares, Solar cycle, Geophysics, Space and Planetary Science, Physics::Space Physics, Coronal mass ejection, Astrophysics::Solar and Stellar Astrophysics, General Earth and Planetary Sciences, Astrophysics::Earth and Planetary Astrophysics, Interplanetary magnetic field
Abstract

The global structure of solar plasma mass output on the source surface near the Sun is investigated in this paper. We use data from observations of the K-corona brightness, interplanetary scintillations (IPS) and photospheric magnetic fields during the descending (1983) and ascending solar activity phases (1976) to show that there exists a global structure in the output of solar plasma mass flux, F-m, on the source surface (2.5R(s), R-s -->solar radius). The magnitude of F. is controlled by the magnetic field structures, i.e., the highest output of F. is from the magnetic neutral line region while the lowest comes from the polar corona regions; the ratio of highest to lowest is about 2; The dependence of F. on the solar wind speed is different for different magnetic field structures. In the polar coronal region (>550km/s), the mass flux F. is independent of the speed; however, in the magnetic neutral line region it first-increases (

Published
2003

10. Freezing of Palletized Food and Time-to-freeze Prediction

Author

Cai, Hongchang

Subjects
Food Science
Abstract

Food freezing is one of the more important food preservation methods and extends the shelf-life of food products as well as the safety of food. Efficient and effective way to freeze the food products keeps ice crystals small during freezing and maintain the high quality of food. The need for prediction of time-to-freeze is important to ensuring uniformity of frozen food quality. There are several methods to predict the time-to-freeze of food products in the previous research, but none of them consider the freezing of food products on a larger scale. In the commercial situation, the food products may be packaged as palletized food products in the warehouse during freezing and some modifications might need to be made on the previous methods. The overall objective of this research was to compare and analyze different methods of predicting time-to-freeze with the real experimental data.The initial freezing temperature and thermo-physical properties of products are predicted by the food composition from USDA Composition Data Base. The freezing of food products after being placed on a pallet is influenced by several process parameters. The time-to-freeze is a function of dimensions of the containers holding the product, the vertical space between layers of product packages and the velocity of cold air within the space between layers of product containers. The unique parameters are in addition the typical parameters such as initial product temperature, cold air temperature, and the thermo-physical properties of the food product. Time-to-freeze was predicted based on the computation of convective heat transfer coefficients and four different expressions of estimation: Pham’s equation, modified Pham’s equation, Cleland and Earle’s equation, and numerical method. Then comparing the results from all methods against the experimental results.In the experiment, the pallet (132 x 107 x 114 cm) filled with gel packs which had an initial freezing temperature at -0.5˚C was frozen in the warehouse with the help of a blast cell inhaling air passing through it. When considering the freezing process, the pallet experienced 3 different freezing conditions and 21 temperatures thermocouples were used to record the temperature history in the pallet during freezing. Due to the characteristics of gel packs, they were stable under repeatable freezing process. The results indicated that Pham’s and Modified Pham’s methods provided relatively accurate time-to-freeze comparing to the numerical simulation and experimental results. During freezing, the different positions in the pallet experienced freezing in different rates and the time-to-freeze for the geometric center was longest. The results from application of the prediction models to a food product indicated that a decrease in cold medium temperature from -18˚C to -40˚C decreased the time-to-freeze by one-third. to the time-to-freeze decreased slightly as the cold medium temperature decreased. As for the impact of convective heat transfer coefficient, an increase in the convective heat transfer coefficient from 10-50W/m2K caused a decrease in time-to-freeze by one-third and reached plateau when the convective heat transfer coefficient became higher than 50W/m2K.When the vertical height of the container on the pallet with spacer increased 10 times, the time-to-freeze increased 15 times. Time-to-freeze increased as the volume fraction of air within the container holding the product being frozen on a pallet increased and it increased dramatically when the volume fraction of air was 80% or higher. The conclusions from this research could be helpful for the warehouse to predict the time-to-freeze more precisely and reach higher efficiency in freezing of palletized food products.

Published
2019

Catalog

Books, media, physical & digital resources
See catalog results