Online State-of-Health Estimation for Li-Ion Battery Using Partial Charging Segment Based on Support Vector Machine
Tsinghua University · University of Michigan
Abstract
The online estimation of battery state-of-health (SOH) is an ever significant issue for the intelligent energy management of the autonomous electric vehicles. Machine-learning based approaches are promising for the online SOH estimation. This paper proposes a machine-learning based algorithm for the online SOH estimation of Li-ion battery. A predictive diagnosis model used in the algorithm is established based on support vector machine (SVM). The support vectors, which reflects the intrinsic characteristics of the Li-ion battery, are determined from the charging data of fresh cells. Furthermore, the coefficients of the SVMs for cells at different SOH are identified once the support vectors are determined. The…
Citation impact
- FWCI
- 21.81
- Percentile
- 100%
- References
- 40
Authors
7Topics & keywords
- Support vector machine
- Battery (electricity)
- State of health
- State of charge
- Battery pack
- Electric vehicle
- Computer science
- Engineering
- Affordable and clean energy