scholarly journals Add-On Type Pulse Charger for Quick Charging Li-Ion Batteries

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 227 ◽  
Author(s):  
Bongwoo Kwak ◽  
Myungbok Kim ◽  
Jonghoon Kim
Keyword(s):  
Lithium Ion Battery ◽  
Lithium Ion ◽  
Current Method ◽  
Constant Current ◽  
Experimental Conditions ◽  
Battery Charging ◽  
Long Run ◽  
Pulse Charging ◽  
Pulse Charge ◽  
Battery Packs

In this paper, an add-on type pulse charger is proposed to shorten the charging time of a lithium ion battery. To evaluate the performance of the proposed pulse charge method, an add-on type pulse charger prototype is designed and implemented. Pulse charging is applied to 18650 cylindrical lithium ion battery packs with 10 series and 2 parallel structures. The proposed pulse charger is controlled by pulse duty, frequency and magnitude. Various experimental conditions are applied to optimize the charging parameters of the pulse charging technique. Battery charging data are analyzed according to the current magnitude and duty at 500 Hz and 1000 Hz and 2000 Hz frequency conditions. The proposed system is similar to the charging speed of the constant current method under new battery conditions. However, it was confirmed that as the battery performance is degraded, the charging speed due to pulse charging increases. Thus, in applications where battery charging/discharging occurs frequently, the proposed pulse charger has the advantage of fast charging in the long run over conventional constant current (CC) chargers.

scholarly journals Improved Performance of Li-ion Polymer Batteries Through Improved Pulse Charging Algorithm

2020 ◽  
Vol 10 (3) ◽  
pp. 895 ◽  
Author(s):  
Judy M. Amanor-Boadu ◽  
Anthony Guiseppi-Elie
Keyword(s):  
Duty Cycle ◽  
Electronic Device ◽  
Lithium Ion ◽  
Cycle Life ◽  
Constant Current ◽  
Battery Charge ◽  
Charge Current ◽  
Pulse Charging ◽  
Pulse Charge ◽  
Improved Performance

Pulse charging of lithium-ion polymer batteries (LiPo), when properly implemented, offers increased battery charge and energy efficiencies and improved safety for electronic device consumers. Investigations of the combined impact of pulse charge duty cycle and frequency of the pulse charge current on the performance of lithium-ion polymer (LiPo) batteries used the Taguchi orthogonal arrays (OA) to identify optimal and robust pulse charging parameters that maximize battery charge and energy efficiencies while decreasing charge time. These were confirmed by direct comparison with the commonly applied benchmark constant current-constant voltage (CC–CV) charging method. The operation of a pulse charger using identified optimal parameters resulted in charge time reduction by 49% and increased charge and energy efficiencies of 2% and 12% respectively. Furthermore, when pulse charge current factors, such as frequency and duty cycle were considered, it was found that the duty cycle of the pulse charge current had the most impact on the cycle life of the LiPo battery and that the cycle life could be increased by as much as 100 cycles. Finally, the charging temperature was found to have the most statistically significant impact on the temporarily evolving LiPo battery impedance, a measure of its degradation.

scholarly journals The Impact of Pulse Charging Parameters on the Life Cycle of Lithium-Ion Polymer Batteries

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2162 ◽  
Author(s):  
J. Amanor-Boadu ◽  
A. Guiseppi-Elie ◽  
E. Sánchez-Sinencio
Keyword(s):  
Life Cycle ◽  
Duty Cycle ◽  
Lithium Ion ◽  
Cycle Life ◽  
Constant Current ◽  
Charge Current ◽  
Pulse Charging ◽  
Pulse Charge ◽  
Impedance Parameters ◽  
The Impact

The pulse charging algorithm is seen as a promising battery charging technique to satisfy the needs of electronic device consumers to have fast charging and increased battery charge and energy efficiencies. However, to get the benefits of pulse charging, the pulse charge current parameters have to be chosen carefully to ensure optimal battery performance and also extend the life cycle of the battery. The impact of pulse charge current factors on the life cycle and battery characteristics are seldom investigated. This paper seeks to evaluate the impact of pulse charge current factors, such as frequency and duty cycle, on the life cycle and impedance parameters of lithium-ion polymer batteries (LiPo) while using a design of experiments approach, Taguchi orthogonal arrays. The results are compared with the benchmark constant current-constant voltage (CC-CV) charging algorithm and it is observed that by using a pulse charger at optimal parameters, the cycle life of a LiPo battery can be increased by as much as 100 cycles. It is also determined that the duty cycle of the pulse charge current has the most impact on the cycle life of the battery. The battery impedance characteristics were also examined by using non-destructive techniques, such as electrochemical impedance spectroscopy, and it was determined that the ambient temperature at which the battery was charged had the most effect on the battery impedance parameters.

Enhancing thermal safety in lithium-ion battery packs through parallel cell ‘current dumping’ mitigation

2021 ◽  
Vol 286 ◽  
pp. 116495
Author(s):  
Samuel T. Plunkett ◽  
Chengxiu Chen ◽  
Ramin Rojaee ◽  
Patrick Doherty ◽  
Yun Sik Oh ◽  
...  
Keyword(s):  
Lithium Ion Battery ◽  
Lithium Ion ◽  
Thermal Safety ◽  
Battery Packs ◽  
Cell Current

Optimization of an air-based thermal management system for lithium-ion battery packs

2021 ◽  
Vol 44 ◽  
pp. 103314
Author(s):  
Yusong Wang ◽  
Bin Liu ◽  
Peng Han ◽  
Changsheng Hao ◽  
Shaohua Li ◽  
...  
Keyword(s):  
Lithium Ion Battery ◽  
Thermal Management ◽  
Management System ◽  
Lithium Ion ◽  
Thermal Management System ◽  
Battery Packs

scholarly journals State-of-Health Estimate for the Lithium-Ion Battery Using Chi-Square and ELM-LSTM

2021 ◽  
Vol 12 (4) ◽  
pp. 228
Author(s):  
Jianfeng Jiang ◽  
Shaishai Zhao ◽  
Chaolong Zhang
Keyword(s):  
Neural Network ◽  
Lithium Ion Battery ◽  
Short Term Memory ◽  
Lithium Ion ◽  
Constant Current ◽  
State Of Health ◽  
Chi Square ◽  
Mean Temperature ◽  
Battery Capacity ◽  
Learning Machine

The state-of-health (SOH) estimation is of extreme importance for the performance maximization and upgrading of lithium-ion battery. This paper is concerned with neural-network-enabled battery SOH indication and estimation. The insight that motivates this work is that the chi-square of battery voltages of each constant current-constant voltage phrase and mean temperature could reflect the battery capacity loss effectively. An ensemble algorithm composed of extreme learning machine (ELM) and long short-term memory (LSTM) neural network is utilized to capture the underlying correspondence between the SOH, mean temperature and chi-square of battery voltages. NASA battery data and battery pack data are used to demonstrate the estimation procedures and performance of the proposed approach. The results show that the proposed approach can estimate the battery SOH accurately. Meanwhile, comparative experiments are designed to compare the proposed approach with the separate used method, and the proposed approach shows better estimation performance in the comparisons.

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