http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
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.
Genome-wide association study for loin muscle area of commercial crossbred pigs
Luan Menghao,Ruan Donglin,Qiu Yibin,Ye Yong,Zhou Shenping,Yang Jifei,Sun Ying,Ma Fucai,Wu Zhenfang,Yang Jie,Yang Ming,Zheng Enqin,Cai Gengyuan,Huang Sixiu 아세아·태평양축산학회 2023 Animal Bioscience Vol.36 No.6
Objective: Loin muscle area (LMA) is an important target trait of pig breeding. This study aimed to identify single nucleotide polymorphisms (SNPs) and genes associated with LMA in the Duroc×(Landrace×Yorkshire) crossbred pigs (DLY). Methods: A genome-wide association study was performed using the Illumina 50K chip to map the genetic marker and genes associated with LMA in 511 DLY pigs (255 boars and 256 sows). Results: After quality control, we detected 35,426 SNPs, including six SNPs significantly associated with LMA in pigs, with MARC0094338 and ASGA0072817 being the two key SNPs responsible for 1.77% and 2.48% of the phenotypic variance of LMA, respectively. Based on previous research, we determined two candidate genes (growth hormone receptor [GHR] and 3-oxoacid Co A-transferase 1 [OXCT1]) that are associated with fat deposition and muscle growth and found further additional genes (MYOCD, ARHGAP44, ELAC2, MAP2K4, FBXO4, FBLL1, RARS1, SLIT3, and RANK3) that are presumed to have an effect on LMA. Conclusion: This study contributes to the identification of the mutation that underlies quantitative trait loci associated with LMA and to future pig breeding programs based on marker-assisted selection. Further studies are needed to elucidate the role of the identified candidate genes in the physiological processes involved in LMA regulation.