Abstract
An accurate model for State of Health estimation in Li-ion batteries is presented. This algorithm can address the state of health estimation at cell, module and battery pack level. An embeddable easy to implement algorithm has been verified and validated in a 79 different scenarios. The algorithm is based on detecting some features, which are easily measured from voltage measurements. The use of the algorithm is suitable to be implemented in different promising applications. Consequently, the algorhithm is also evaluated on this regard. In adittion, some modifications are suggested so to run the estimator quicker.
| Original language | English |
|---|---|
| Title of host publication | EVS31 |
| Publisher | The World Electric Vehicle Association (WEVA) |
| Number of pages | 6 |
| Publication status | Published - 1 Oct 2018 |
| Event | Electric Vehicle Symposium 31 - Kobe, Japan Duration: 30 Sep 2018 → 3 Oct 2018 |
Conference
| Conference | Electric Vehicle Symposium 31 |
|---|---|
| Abbreviated title | EVS31 |
| Country/Territory | Japan |
| City | Kobe |
| Period | 30/09/18 → 3/10/18 |
Keywords
- Lithium-ion
- Battery Management System
- Real applications
- State of Health
- Incremental capacity