Skip to main content

User-Involved Battery Charging Control with Economic Cost Optimization

  • Chapter
  • First Online:
Advanced Model-Based Charging Control for Lithium-Ion Batteries
  • 371 Accesses

Abstract

Most of the existing charging control methods focus on fast charging to accelerate the charging speed with guaranteeing the batterys safety. When the charging demand is urgent, a large current is inevitable to be used to achieve fast charging. However, it is not uncommon to encounter scenarios where charging times are sufficient in practice, such as batteries being charged overnight at home. For these cases, it is better to provide a low but healthy charging current for the battery rather than a high but harmful charging current. Considering the user’s charging demand in the charging control method, the charging current can be self-adjusted according to user specifications and battery dynamics, which not only makes the charger smarter, but also reduces the capacity loss of the battery. Based on this idea, it is valuable to consider the user’s charging demand in the battery charging method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Q. Ouyang, R. Fang, G. Xu, and Y. Liu, “User-involved charging control for EV lithium-ion batteries with economic cost optimization,” Applied Energy, vol. 314, pp. 118878, 2022.

    Google Scholar 

  2. C. Zou, X. Hu, Z. Wei, and X. Tang, “Electrothermal dynamics-conscious lithium-ion battery cell-level charging management via state-monitored predictive control,” Energy, vol. 141, pp. 250–259, 2017.

    Google Scholar 

  3. C. Chung, S. Jangra, Q. Lai, and X. Lin, “Optimization of electric vehicle charging for battery maintenance and degradation management,” IEEE Transactions on Transportation Electrification, vol. 6, no. 3, pp. 958–969, 2020.

    Google Scholar 

  4. S. Su, H. Li, and D. W. Gao, “Optimal planning of charging for plug-in electric vehicles focusing on users’ benefits,” Energies, vol. 10, no. 7, pp. 952, 2017.

    Google Scholar 

  5. H. Min, W. Sun, X. Li, D. Guo, Y. Yu, T. Zhu, and Z. Zhao, “Research on the optimal charging strategy for Li-Ion batteries based on multi-objective optimization,” Energies, vol. 10, no. 5, pp. 1–15, 2017.

    Google Scholar 

  6. S. Boyd, L. Vandenberghe, Convex Optimization, Cambridge University Press, New York, NY, USA, 2004.

    Book  MATH  Google Scholar 

  7. X. Lin, H. E. Perez, S. Mohan, J. B. Siegel, A. G. Stefanopoulou, Y. Ding, and M. P. Castanier, “A lumped-parameter electro-thermal model for cylindrical batteries,” Journal of Power Sources, vol. 257, pp. 1–11, 2014.

    Google Scholar 

  8. Y. Cao, S. Tang, C. Li, P. Zhang, Y. Tan, Z. Zhang, and J. Li, “An optimized EV charging model considering TOU price and SOC curve,” IEEE Transactions on Smart Grid, vol. 3, no. 1, pp. 388–393, 2012.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Quan Ouyang .

Rights and permissions

Reprints and permissions

Copyright information

© 2023 Huazhong University of Science and Technology Press

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ouyang, Q., Chen, J. (2023). User-Involved Battery Charging Control with Economic Cost Optimization. In: Advanced Model-Based Charging Control for Lithium-Ion Batteries. Springer, Singapore. https://doi.org/10.1007/978-981-19-7059-7_6

Download citation

  • DOI: https://doi.org/10.1007/978-981-19-7059-7_6

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-7058-0

  • Online ISBN: 978-981-19-7059-7

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics