Analysis of Cyclic Degradation of Li-ion batteries

Battery degradation causes several adverse effects including reduced driving range and increased charging time. This affects the scheduling of Electric Vehicles (EVs) and Battery Energy Storage System (BESS) after few cycles of the battery usage in the grid. In this paper, a battery degradation model is adopted and various factors contributing to degradation were analyzed. In this model the effect of starting SoC (State of Charge) is also considered for better accuracy. The Capacity fade of batteries in different type of vehicles (Car, Bus, Truck) and BESS of various capacities is studied for various factors. Also, the optimal factors to reduce the degradation is studied. The temperature of the battery plays a crucial role in degradation. Higher C-rates accelerates the degradation. In addition, the starting SoC when under 50% also reduces the battery life. Simulation of vehicle batteries under various factors shows that higher battery capacity vehicles (bus in this case) degrades in less number of cycles. This can significantly impact the scheduling of EVs. The adopted model is compared with a data-fitting model of the same type. Results shows that there is 1% difference in lower and 2% higher C-rates respectively.

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Published
2024-12-10
DOI
https://doi.org/10.1109/piicon63519.2024.10995090
Primary Topic
Advanced Battery Technologies Research
Type
article
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Analysis of Cyclic Degradation of Li-ion batteries

Ankur Singh Rana, Narayanan Krishnan, Tomonobu Shah Senjyu, Alexander Águila Téllez et al.
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Advanced Battery Technologies Research
article

Analysis of Cyclic Degradation of Li-ion batteries

Ankur Singh Rana, Narayanan Krishnan, Tomonobu Shah Senjyu, Alexander Águila Téllez, Anurag Sharma, G Aravindhanathan
article en

Abstract

Battery degradation causes several adverse effects including reduced driving range and increased charging time. This affects the scheduling of Electric Vehicles (EVs) and Battery Energy Storage System (BESS) after few cycles of the battery usage in the grid. In this paper, a battery degradation model is adopted and various factors contributing to degradation were analyzed. In this model the effect of starting SoC (State of Charge) is also considered for better accuracy. The Capacity fade of batteries in different type of vehicles (Car, Bus, Truck) and BESS of various capacities is studied for various factors. Also, the optimal factors to reduce the degradation is studied. The temperature of the battery plays a crucial role in degradation. Higher C-rates accelerates the degradation. In addition, the starting SoC when under 50% also reduces the battery life. Simulation of vehicle batteries under various factors shows that higher battery capacity vehicles (bus in this case) degrades in less number of cycles. This can significantly impact the scheduling of EVs. The adopted model is compared with a data-fitting model of the same type. Results shows that there is 1% difference in lower and 2% higher C-rates respectively.

National Institute of Technology Tiruchirappalli (IN), Politecnica Salesiana University (EC), University of the Ryukyus (JP), Newcastle University Singapore (SG), SASTRA University (IN)
Openalex Percentile: Top 68%
Advanced Battery Technologies Research
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