Experimental Set-up for Sensors Selection for Early Fault Detection in Innovative Modular Li-Ion Battery Systems Related to HELIOS H2020 Project
- Resource Type
- Conference
- Authors
- Marinov, Marin B.; Dimitrov, Dimitar; Ganev, Borislav; Todorov, Georgi; Ivanov, Ivan V.
- Source
- 2022 XXXI International Scientific Conference Electronics (ET) Scientific Conference Electronics (ET), 2022 XXXI International. :1-6 Sep, 2022
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Lithium-ion batteries
Fault diagnosis
Sensitivity
Sensor phenomena and characterization
Sensor fusion
Sensor systems
Battery charge measurement
Battery characterization
BMS
gas sensor
gas analysis
lithium-ion battery
fault diagnosis
monitoring
- Language
Lithium-ion batteries have already become a mainstream energy storage solution for many applications, especially for hybrid and electric vehicles (EV). Various malfunctions in the lithium-ion battery system (LIBS) can cause serious safety problems and significant performance determination. For the safe and efficient operation of LIBS, the development of advanced fault diagnosis technologies is becoming increasingly important. This paper presents an experimental setup for the acquisition of lithium-ion battery condition data. Different approaches for the early diagnosis and prediction of various LIBS faults are investigated. This will allows for investigation of the feasibility of using diverse types of gas sensors in large lithium-ion battery systems in addition to conventionally used battery monitoring tools.