Description
Accurate on board State of Health (SoH) estimation is a crucial parameter that needs to be calculated in order to keep the battery pack safe and under control. The Battery Management System (BMS) takes charge of many functionalities: among others, it diagnoses the different states of the battery, monitors the measurable parameters and manages the battery pack electrically and thermally. All these functionalities are integrated into algorithms or estimating techniques and have to be implemented in a microcontroller. This device is required to be powerful enough for performing all the computational effort for the algorithms at the lowest possible cost, in order to make cost-effective and versatile BMS’s. The objective of this work is to develop a SoH estimation technique which covers all these requirements. Nevertheless, highly accurate results have been achieved with a method based on the study of the incremental capacity curves. As a result, an implementable and accurate online algorithm has been developed for NMC/Graphite battery packs estimating the SoH within an error less than 2%.| Period | 9 Oct 2017 → 11 Oct 2017 |
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| Event title | 30th International Electric Vehicle Symposium and Exhibition, EVS 2017 |
| Event type | Conference |
| Location | Stuttgart, GermanyShow on map |