Abstract
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 16th International Conference on Condition Monitoring and Asset Management, BINDT 2019 |
| Number of pages | 13 |
| Publication status | Published - 27 Jun 2019 |
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Time series analysis of high energy density lithium-ion batteries for electric vehicles applications. / Almadni, Hani Mustafataher M; Alkali, Babakalli; Lak, Gyorgy Balint; Ansell, Ray.
Proceedings of the 16th International Conference on Condition Monitoring and Asset Management, BINDT 2019. 2019.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Time series analysis of high energy density lithium-ion batteries for electric vehicles applications
AU - Almadni, Hani Mustafataher M
AU - Alkali, Babakalli
AU - Lak, Gyorgy Balint
AU - Ansell, Ray
N1 - Event: 25-27 June 2019, Principal Grand Central Hotel, Glasgow, UK. CM-MFPT-0048-2019. R1 Pub date: used last date of conference. Acceptance in SAN Publisher policy unknown - made file open and contacted event contact. ET 16/7/19
PY - 2019/6/27
Y1 - 2019/6/27
N2 - The use of lithium-ion secondary batteries in electric vehicles has now become a key component of high-performance energy storage systems. There are various factors that contribute significantly to the reduction in battery performance and subsequent damage of battery cells. The factors associated with battery degradation as a result of the charge and discharge rate is not new and has been investigated widely by many researchers. The maximum amount of electrical charge that a battery can store and deliver normally decreases over time. This capacity fade phenomenon is a result of various degradation mechanisms within the battery. The degradation mechanisms are random in nature and, in this paper, the degradation mechanisms associated with changes in the electrical impedance, capacity and the lifecycle of the battery cells are explored. 18650 battery cells are tested for 23 cycles on a trickle charge and the designated samples from each battery is subjected to different set temperatures, ranging from 20°C to 55°C at a constant time per experiment. Statistical analysis of the data is conducted using a time series approach and a reliability model is proposed in an attempt to predict the degradation or failure and hence improve the battery performance.
AB - The use of lithium-ion secondary batteries in electric vehicles has now become a key component of high-performance energy storage systems. There are various factors that contribute significantly to the reduction in battery performance and subsequent damage of battery cells. The factors associated with battery degradation as a result of the charge and discharge rate is not new and has been investigated widely by many researchers. The maximum amount of electrical charge that a battery can store and deliver normally decreases over time. This capacity fade phenomenon is a result of various degradation mechanisms within the battery. The degradation mechanisms are random in nature and, in this paper, the degradation mechanisms associated with changes in the electrical impedance, capacity and the lifecycle of the battery cells are explored. 18650 battery cells are tested for 23 cycles on a trickle charge and the designated samples from each battery is subjected to different set temperatures, ranging from 20°C to 55°C at a constant time per experiment. Statistical analysis of the data is conducted using a time series approach and a reliability model is proposed in an attempt to predict the degradation or failure and hence improve the battery performance.
M3 - Conference contribution
BT - Proceedings of the 16th International Conference on Condition Monitoring and Asset Management, BINDT 2019
ER -