Design and Implementation of a Diagnostic System for Lithium Battery Module based on Sinusoidal Loading Technique

Author(s):  
Chang-Hua Lin ◽  
Kuan-Chung Chen ◽  
Yu-Lin Lee
2013 ◽  
Vol 397-400 ◽  
pp. 1169-1173
Author(s):  
Hong Wei Tang ◽  
Xi Kun Chen ◽  
Yan Xia Gao

To adapt to the requirements of the charging and discharging of the lithium battery, the paper presents a three-level based bidirectional energy storage converter topology.It has strong adaptability and can manage the charge and discharge of multi-series and parallel battery module. The mathematical model of the converter is analyzed, and the two operation modes of the converter control strategy are studied; Analysis the feed-forward decoupling control of three-level rectifier, and the variable scale factor is used to control midpoint potential. The simulation results demonstrate the feasibility of the design.


2021 ◽  
Vol 248 ◽  
pp. 01065
Author(s):  
Yu Zhang ◽  
Guixiong Liu ◽  
Daqiang Deng

The thermal runaway of lithium power battery is the key problem of battery safety, according to the standard SAE J2464–2009 single point heating key position, the proposed multi-point trigger based thermal runaway of lithium power battery module simulation method and battery module thermal runaway battery monomer ratio PN, thermal runaway trigger time tn two indicators, the thermal runaway rule of 18650 lithium power battery module under different trigger position, trigger points. The results show that considering the external thermal insulation conditions of the power lithium battery module, the geometric angular position in the module is the most dangerous position, and the number of thermal trigger points is positively correlated with PN.


2021 ◽  
Vol 3 (1) ◽  
pp. 033-040
Author(s):  
I Putu Agus Eka Pratama

As one of the deadliest diseases in the world, heart disease requires serious treatment. The weaknesses of providing services for heart disease in Bali Province are that there is no online diagnostic system to make it easier for people to check their health conditions to find out whether they have heart disease. Based on this research, the design and implementation of a web-based online heart disease diagnosis system are carried out. The diagnostic system uses Artificial Intelligence and inputs data from the user based on several questions posed by the system. This research uses Case-Based Reasoning (CBR) algorithm with Design Science Research Methodology (DSRM) and a case study qualitative research method. The test results show that the system designed and implemented can run well and perform accurate diagnostics according to the design and user needs.


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