TY - JOUR
T1 - Determination of constant current to constant voltage switch-over point for health-aware fast charging using heuristic algorithm
AU - Bose, Bibaswan
AU - Garg, A.
AU - Panigrahi, B. K.
AU - Kim, Jonghoon
N1 - Publisher Copyright:
© 2023
PY - 2023/9/1
Y1 - 2023/9/1
N2 - High charging times for EVs are a hurdle to mainstream adoption since quick charging shortens battery life. The paper proposes a quick charging method that reduces charging time and battery deterioration. The proposed charging method modifies the conventional Constant Current – Constant Voltage (CC-CV) charging approach, where the switching point from CC to CV mode is altered. Sixteen charging techniques with varied CC-CV switchover points have been explored, comprising nine charging strategies with capacity switching and seven with voltage switching. The gathered data is processed using a mathematical relationship to determine the State of Health, capacity deterioration, and Internal Resistance characteristics. In addition, a Fuzzy Logic Controller is employed to determine the two effective switchover points based on the least amount of cyclic capacity deterioration, SoH, and charging time. The optimal CC-CV transition point between these two points is estimated using Genetic Algorithm Optimization. Compared with the traditional CC-CV charging approach, the effectiveness of the resulting switchover point is evaluated. The results indicate that the recommended charging approach costs an additional time of 4.22 %, and it increases the cell's cycle life by 51.77 % compared to CC-CV. Thus, the comparative analysis reveals that the proposed charge technique offers more efficient performance.
AB - High charging times for EVs are a hurdle to mainstream adoption since quick charging shortens battery life. The paper proposes a quick charging method that reduces charging time and battery deterioration. The proposed charging method modifies the conventional Constant Current – Constant Voltage (CC-CV) charging approach, where the switching point from CC to CV mode is altered. Sixteen charging techniques with varied CC-CV switchover points have been explored, comprising nine charging strategies with capacity switching and seven with voltage switching. The gathered data is processed using a mathematical relationship to determine the State of Health, capacity deterioration, and Internal Resistance characteristics. In addition, a Fuzzy Logic Controller is employed to determine the two effective switchover points based on the least amount of cyclic capacity deterioration, SoH, and charging time. The optimal CC-CV transition point between these two points is estimated using Genetic Algorithm Optimization. Compared with the traditional CC-CV charging approach, the effectiveness of the resulting switchover point is evaluated. The results indicate that the recommended charging approach costs an additional time of 4.22 %, and it increases the cell's cycle life by 51.77 % compared to CC-CV. Thus, the comparative analysis reveals that the proposed charge technique offers more efficient performance.
KW - CC-CV
KW - Charging time
KW - Cycle life
KW - Genetic algorithm
UR - http://www.scopus.com/inward/record.url?scp=85154048763&partnerID=8YFLogxK
U2 - 10.1016/j.est.2023.107543
DO - 10.1016/j.est.2023.107543
M3 - Article
AN - SCOPUS:85154048763
SN - 2352-152X
VL - 67
JO - Journal of Energy Storage
JF - Journal of Energy Storage
M1 - 107543
ER -