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Comparison of Three Well-known Filters for the Battery State of Health Estimation Application
- Source :
- 2018 4th International Conference on Frontiers of Signal Processing (ICFSP).
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- Battery State of Health (SOH) is a vital parameter to maintain the battery as well. As a matter of fact this is the ability of a battery to store energy. It is needless to say that during the lifetime of a battery, its performance gradually decreases, so by using a suitable Battery Management System (BMS), safety and improvement of the usage lifetime can be guaranteed. The traditional methods for indicating usable capacity are basically based on output voltage measuring in the discharge process with a constant current pulse. However, due to load changes the discharge current of batteries in operation almost always fluctuates, which makes it hard to measure the online capacity measurement for the traditional methods. To overcome the above problems, a filter design approach is proposed in this paper to estimate the SOH. This paper by using a generic second order equivalent circuit, that has been used for both VRLA and Li-ion batteries before, presents comparison of three well-known filters performance in the battery SOH estimation application. Parameter estimation have been applied in order to compare and contrast. To verify the performance of the methods, simulations were built in Matlab and final results show accuracy of filters and claim merits and demerits of them.
- Subjects :
- Battery (electricity)
Filter design
Extended Kalman filter
Computer science
State of health
020208 electrical & electronic engineering
0202 electrical engineering, electronic engineering, information engineering
Constant current
VRLA battery
Equivalent circuit
02 engineering and technology
Reliability engineering
Voltage
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2018 4th International Conference on Frontiers of Signal Processing (ICFSP)
- Accession number :
- edsair.doi...........2b1faa957137d23b93b589b4b697235e
- Full Text :
- https://doi.org/10.1109/icfsp.2018.8552043