Fuzzy logic approach for failure analysis of Li-ion battery pack in
An analysis of battery pack functions, failure modes, causes, and effects concerning their severity, occurrences, and detection ranks.
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lithium ion secondary batteries using FMEA. (ICBP) in an electri c vehicle . The primary during vehicle op eration based on histo rical data. effects on the batter y. Potential fa ilure modes are the accident data. The paper also ad dresses the risks of fire and smo ke in relation to the battery. system in electri c vehicles.
In order to design and manufacture a battery pack, engineering skills are required in various fields. For this reason, FMEA has been formulated with the help of several experts. Each of these people has significant experience in electric vehicle battery packs. Fuzzy RPNs were created using Matlab fuzzy interface toolbox.
The considered battery pack includes three main subsystems: mechanical subsystem, BMS and High voltage protection circuits and devices, and the Thermal management subsystem, which are explained in the following sections: 4.2.1. Mechanical subsystem:
Pahuja and Singh utilized FMEA to assess the risk priority number (RPN) of electric vehicle inverters and put forth protective measures. Similarly, Prasad conducted a qualitative risk analysis of failure modes across cell, module, and battery pack levels using FMEA.
An analysis of battery pack functions, failure modes, causes, and effects concerning their severity, occurrences, and detection ranks.
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Incidents involving battery fires have raised safety concerns, necessitating a thorough assessment of potential failure modes during the design phase. A reference degradation and aging mechanism
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This paper seeks to identify potential failures in retired lithium-ion battery at different levels (i.e. pack, module and cell) and assessing their impact and severity. First, adaptive Failure Modes
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