Prognostics of Battery Health and Faults
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D2: Electrochem: Batteries, Fuel Cells, Capacitors".
Deadline for manuscript submissions: 15 September 2024 | Viewed by 5828
Special Issue Editors
Interests: battery modeling; battery control; battery health prognostics and fault diagnosis
Special Issues, Collections and Topics in MDPI journals
Interests: battery modeling; lifetime prediction; battery control
Special Issue Information
Dear Colleagues,
Lithium-ion batteries have become one of the most promising energy storage devices due to fast charge capability, high densities, and long cycle life. However, a lithium-ion battery is a complex electrochemical system; therefore, its performance and life gradually deteriorate during use. Battery degradation is caused by many different aspects, including physical (e.g., thermal and mechanical stress) and chemical (e.g., side reactions) mechanisms. Due to the complexity of battery degradation, battery health prediction is an extremely challenging task. Moreover, the faults in the battery system can accelerate battery degradation. These faults can be generally divided into battery faults, sensor faults, and actuator faults. Various fault detection and isolation methods have been proposed, but fault prognosis is not fully understood. Both battery degradation and battery system faults can cause battery failure. As one of the most expensive and essential components in electrified transportation systems and smart grids, battery failures can cause safety issues. Certain severe failures, such as thermal runaway, can lead to fire or even explosion. Therefore, the development of accurate health and fault prognostic technologies is becoming increasingly critical for safe and efficient battery management.
For this Special Issue on “Prognostics of Battery Health and Faults”, we warmly welcome the submission of comprehensive reviews and original research articles.
Dr. Zhongwei Deng
Dr. Le Xu
Dr. Bo Jiang
Guest Editors
Manuscript Submission Information
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Keywords
- energy storage system
- electric vehicle
- lithium-ion battery
- health estimation/prediction
- remaining useful life
- degradation/failure mechanism
- degradation trajectory prediction
- remaining value assessment
- fault diagnosis
- early safety warning
- internal short circuit
- thermal runaway warning
Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Advancing Urban Transport: Integration of Electric Buses with a Particular Focus on Energy Management and Battery Optimization
Authors: Szabolcs Kocsis Szürke; István Lakatos
Affiliation: Central Campus Győr, Széchenyi István University, H-9026 Győr, Hungary
Abstract: A critical aspect of local emission reduction is the electrification of local public transport. The introduction of electric buses for urban transport can significantly facilitate this. However, introducing new vehicles brings new problems: electric charging, new consumption standards, the relationship between distance traveled -temperatures and number of passengers, battery system status, etc. One of the aspects presented in this article was to collect and examine the factors affecting energy efficiency. The main aspects used to determine the actual consumption are external temperature factors, bus conditions, road conditions, the driver's ability, and driving style. By combining these values, a baseline of actual consumption can be established, and an energy balance can be calculated to identify energy-wasting locations and events. Facilitating selecting and assessing different routes, stopping points, and charging times. Furthermore, the approach helps to scale the bus battery system and select the correct local route (line). The second approach is to study and assess the battery systems of electric buses. An essential element of this approach is the cell-by-cell examination and analysis of the battery system, observing cells that appear to be weak. This is because, currently, even in electric vehicles, in most cases, the whole system is replaced (in the best case, only the faulty module) in case of a cell failure. In the case of a bus, where there are many more batteries in the system than in a road electric vehicle, such a replacement can be very costly and polluting. Therefore, a critical aspect was adopting a procedure to detect and localize possible faults.
