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Mingzhen Guo,Jiang He,Shuang Ma,Xiaohan Sun,Mingda Zheng 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2017 NANO Vol.12 No.4
In this paper, a novel colorimetric biosensor for Hg2+ is presented based on Hg2+ stimulated peroxidase-like activity of hollow porous gold nanoparticles (HPGNPs). Under mild conditions, HPGNPs show high catalytic activity toward the oxidation of 3, 3' , 5, 5' -tetramethylbenzidine (TMB) using H2O2 as an oxidant. The peroxidase-like activity of HPGNPs is "switched-on" selectively in the presence of Hg2+, which permitted a novel and facile colorimetric sensor for Hg2+. This method exhibits many merits like high selectivity and sensitivity. As low as 18.5 nM Hg2+ could be determined at a linear range from 0.5 x 10 -6 M to 50 x 10 -6 M. This method is successfully applied for the determination of total mercury content in tap water and Yellow River which indicates that the method has a great potential for the routine determination of Hg2+ in environmental samples.
Electro-thermal model for lithium-ion battery simulations
Cai, Yibin,Che, Yanbo,Li, Hongfeng,Jiang, Mingda,Qin, Peijun The Korean Institute of Power Electronics 2021 JOURNAL OF POWER ELECTRONICS Vol.21 No.10
With the extensive application of lithium batteries and the continuous improvements in battery management systems and other related technologies, the requirements for fast and accurate modeling of lithium batteries are gradually increasing. Temperature plays a vital role in the dynamics and transmission of electrochemical systems. The thermal effect must be considered in battery models. In this paper, a simulation model of a lithium battery with thermal characteristics is established. This thermal model is coupled with a temperature-dependent 2-RC equivalent circuit model to form an electro-thermal model for lithium-ion batteries. The hybrid pulse power characterization test is used to estimate the equivalent circuit parameters. Finally, under NEDC and DST conditions, battery voltage and temperature estimation results of the electro-thermal model are analyzed to verify the correctness and accuracy of the model. The voltage error is within - 0.16~0.20 V under the NEDC condition. Moreover, under the DST condition, the maximum relative error in the electro-thermal model is within 5%.
Peijun Qin,Yanbo Che,Hongfeng Li,Yibin Cai,Mingda Jiang 전력전자학회 2022 JOURNAL OF POWER ELECTRONICS Vol.22 No.3
Accurate estimations of the state of charge (SOC) and the state of power (SOP) are required to ensure efficient and reliable utilization of Li-ion batteries. A new joint estimation method of SOC–SOP based on the electro-thermal model and multi-parameter constraints is proposed in this paper. The proposed method introduces temperature as one of the important constraints for SOP and considers the intrinsic relationship between SOC and SOP as well as the influence of voltage, temperature, and SOC on SOP estimation. First, an electro-thermal model is developed to describe the electric and thermal dynamic characteristics of a battery. Second, the battery SOC is accurately estimated by the unscented Kalman filter method. Then the state of power of the battery is predicted under the condition of multi-parameter constraints. Finally, experiments are conducted to verify the effectiveness of the proposed method. Simulation and experimental results show that this method has a high degree of estimation accuracy and is very simple to calculate. Under the DST condition, the maximum relative voltage error within the electro-thermal model is about 5%. The maximum estimation error of the peak discharge power does not exceed 5 W, and the overall average estimation error is about 1.2 W.