Influence of Current Ripples in Cascaded Multilevel Topologies on the Aging of Lithium Batteries

Chang, Fengqi; Roemer, Felix; Lienkamp, Markus

doi:10.1109/tpel.2020.2989145

Cited by 31 publications

(16 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The influence on the lifetime of Li-ion batteries for MLI comparable applications, with rectangular waveforms up to the kHz range, is investigated in only two publications that are known to us [610,611]. Uno et al [611] tested 24 cells with 2 Ah capacity each and a current of ±1 A for a high-frequency balancer application that is comparable to MLIs.…”

Section: Influence Of Switching On Cell Lifetimementioning

confidence: 99%

“…This was explained by the influence of micro cycles at low frequencies while at higher frequencies only the double layer capacitances of the electrodes are cycled. Chang et al [610] investigate the MLI application explicitly for a CHB at 2 kHz and 10 kHz. The results for five 3 Ah cells show no dependence on frequency and power factor on capacity fade, but a 2 % lower capacity compared to reference cells with the same average C-rate.…”

Section: Influence Of Switching On Cell Lifetimementioning

confidence: 99%

See 1 more Smart Citation

Critical Review of Intelligent Battery Systems: Challenges, Implementation, and Potential for Electric Vehicles

et al. 2021

View full text Add to dashboard Cite

This review provides an overview of new strategies to address the current challenges of automotive battery systems: Intelligent Battery Systems. They have the potential to make battery systems more performant and future-proof for coming generations of electric vehicles. The essential features of Intelligent Battery Systems are the accurate and robust determination of cell individual states and the ability to control the current of each cell by reconfiguration. They enable high-level functions like fault diagnostics, multi-objective balancing strategies, multilevel inverters, and hybrid energy storage systems. State of the art and recent advances in these topics are compiled and critically discussed in this article. A comprising, critical discussion of the implementation aspects of Intelligent Battery Systems complements the review. We touch on sensing, battery topologies and management, switching elements, communication architecture, and impact on the single-cell. This review contributes to transferring the best technologies from research to product development.

show abstract

Section: Influence Of Switching On Cell Lifetimementioning

confidence: 99%

Section: Influence Of Switching On Cell Lifetimementioning

confidence: 99%

Critical Review of Intelligent Battery Systems: Challenges, Implementation, and Potential for Electric Vehicles

et al. 2021

View full text Add to dashboard Cite

show abstract

“…So far, to best of our knowledge, there are only two publications by Uno et al [9] and by Chang et al [10] that investigate the influence of MLI-like profiles on the cell lifetime. Uno et al [9] investigated 24 2 Ah LiCoO 2 /Graphite cells with a square wave current with an amplitude of ±1 A and varying the frequency from 1 Hz to 100 kHz.…”

Section: Introductionmentioning

confidence: 99%

Influence of Switching on the Aging of High Power Lithium-Ion Cells

et al. 2022

View full text Add to dashboard Cite

For intelligent battery systems that are able to control the current flow for each individual cell, the multilevel inverter is an interesting approach to replace the bidirectional AC/DC-converter and improve flexibility of charging system and signal quality in both directions. Therefore, the cells are modulated by switching varying the duty cycle, the current and the frequency up to the kHz-range. This is only beneficial if the switching does not lead to a significant additional aging. The scientific gap to assess and understand the impact of switching is investigated in this paper by testing 22 high-power 18650 lithium-ion cells (Samsung 25R). The cells are tested at 50 Hz and 10 kHz switching frequency during charge, discharge and charge/discharge at 50% duty cycle. The tests are compared to eight reference tests with continuous current flow performed at the average and the maximum current for charge and discharge, respectively. The results are obtained by evaluating the remaining capacity, resistance, electrochemical impedance spectroscopy and dV/dQ analysis. Before reaching rollover, the investigated cells lose homogeneity and cathode capacity but no significant difference for the aging parameters are found. After rollover, the cell-to-cell variation is greater than the aging induced by the different cycling parameters.

show abstract

“…The above studies need to identify the internal parameters of Li-ion battery. Once the impedance parameters of Li-ion battery are obtained, it is difficult to avoid the damage experiment on the battery, and the prediction time is long, which easily leads to the delay of information acquisition [17]. The second type is ampere hour method [18].…”

Section: Introductionmentioning

confidence: 99%

An Improved Rainflow Algorithm Combined with Linear Criterion for the Accurate Li-ion Battery Residual Life Prediction

Huang¹,

Wang²,

Xu³

et al. 2021

International Journal of Electrochemical Science

View full text Add to dashboard Cite

Li-ion battery health assessment has been widely used in electric vehicles, unmanned aerial vehicle and other fields. In this paper, a new linear prediction method is proposed. By weakening the sensitivity of the Rainflow algorithm to the peak data, it can be applied to the field of battery, and can accurately count the number of Li-ion battery cycles, and skip the cumbersome link of parameter identification. Then, a linear criterion is proposed based on the idea of proportion, which makes the life prediction of Li-ion battery linear. Under the verification of multiple sets of data, the prediction error of this method is kept within 2.53%. This method has the advantages of high operation efficiency and simple operation, which provides a new idea for battery life prediction in the field of electric vehicles and aerospace.

show abstract

Influence of Current Ripples in Cascaded Multilevel Topologies on the Aging of Lithium Batteries

Cited by 31 publications

References 59 publications

Critical Review of Intelligent Battery Systems: Challenges, Implementation, and Potential for Electric Vehicles

Critical Review of Intelligent Battery Systems: Challenges, Implementation, and Potential for Electric Vehicles

Influence of Switching on the Aging of High Power Lithium-Ion Cells

An Improved Rainflow Algorithm Combined with Linear Criterion for the Accurate Li-ion Battery Residual Life Prediction

Contact Info

Product

Resources

About