TY - GEN
T1 - Electric vehicle operation scheduling optimization considering electrochemical characteristics of Li-ion batteries
AU - Lyu, Mingyu
AU - Han, Bing
AU - Lu, Shaofeng
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/16
Y1 - 2020/10/16
N2 - Ahstract-With the development of Electric Vehicles (EVs), charging and discharging scheduling for the EV fleet becomes an interesting topic with its large impact on economic costs and power systems. In many recent studies, the adopted models ignore the special electrochemical characteristics of Li-ion batteries, i.e. the correlation between the charging power limit and battery's state of energy and this has led to an inaccurate presentation of the charging and discharging scheduling of the EV fleet. This paper proposes a Li-ion battery charging dynamic model to incorporate this correlation to more accurately approximate the real-life battery charging characteristics. The proposed dynamic model is compared to the static model used in some papers, in which the charging power limit is considered constant regardless of battery state of energy. The differences in cost and time are observed. The result shows in the dynamic model, charging time is longer and the cost is higher than that of in the static model. Increment rate of charging time and cost have been observed in 0.2C (slow charging) and 1C (fast charging) cases for 1000 EVs respectively. These differences can be well attributed to the decreasing charging power limit caused by the increase of SOE.
AB - Ahstract-With the development of Electric Vehicles (EVs), charging and discharging scheduling for the EV fleet becomes an interesting topic with its large impact on economic costs and power systems. In many recent studies, the adopted models ignore the special electrochemical characteristics of Li-ion batteries, i.e. the correlation between the charging power limit and battery's state of energy and this has led to an inaccurate presentation of the charging and discharging scheduling of the EV fleet. This paper proposes a Li-ion battery charging dynamic model to incorporate this correlation to more accurately approximate the real-life battery charging characteristics. The proposed dynamic model is compared to the static model used in some papers, in which the charging power limit is considered constant regardless of battery state of energy. The differences in cost and time are observed. The result shows in the dynamic model, charging time is longer and the cost is higher than that of in the static model. Increment rate of charging time and cost have been observed in 0.2C (slow charging) and 1C (fast charging) cases for 1000 EVs respectively. These differences can be well attributed to the decreasing charging power limit caused by the increase of SOE.
KW - Charging Strategy
KW - Electric vehicle
KW - Li-ion Battery
KW - Optimization
UR - http://www.scopus.com/inward/record.url?scp=85101152353&partnerID=8YFLogxK
U2 - 10.1109/YAC51587.2020.9337681
DO - 10.1109/YAC51587.2020.9337681
M3 - Conference Proceeding
AN - SCOPUS:85101152353
T3 - Proceedings - 2020 35th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2020
SP - 89
EP - 94
BT - Proceedings - 2020 35th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2020
Y2 - 16 October 2020 through 18 October 2020
ER -