Matthias Fleckenstein
Matthias Fleckenstein has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- David Henriques
Institute for Materials Science and Engineering (IMaSE), Hochschule Mannheim, Paul-Wittsack-Straße 10, 68163 Mannheim, Germany
2 shared publications - Hanno Winter
BorgWarner Battery Systems Technical Center GmbH, Kleyerstraße 20, 64295 Darmstadt, Germany
2 shared publications - Jan Neunzling
BorgWarner Battery Systems Technical Center GmbH, Kleyerstraße 20, 64295 Darmstadt, Germany
2 shared publications - Torsten Markus
Institute for Materials Science and Engineering (IMaSE), Hochschule Mannheim, Paul-Wittsack-Straße 10, 68163 Mannheim, Germany
2 shared publications - Philipp Hainke
BorgWarner Battery Systems Technical Center GmbH, Kleyerstraße 20, 64295 Darmstadt, Germany
1 shared publication
Latest Publications
- Open Access
Investigation of the Suitability of the DTV Method for the Online SoH Estimation of NMC Lithium-Ion Cells in Battery Management Systems
Investigating the temperature behavior of lithium-ion battery cells has become an important part of today’s research and development. The main reason for this is that the temperature profile of a battery cell changes during aging. By using Differential Thermal Voltammetry (DTV), new possibilities are opened up, especially since this diagnostic method is designed to work in operando by only requiring voltage and temperature readings. In this study, a batch of NMC-21700 cells were aged in calendar and cyclic manners. After a specified aging cycle was complete, a check-up measurement was performed. During this time, the cycler collected the electrical measuring values, while a negative temperature coefficient thermistor, which was located on the cell, was used to record the temperature fluctuations. The data were then evaluated by using the DTV analysis technique. By comparing the characteristic points of DTV, correlations between the changing curve characteristics and the capacity loss, and therefore the aging of the respective cell, were established. Based on these results, a simple model suitable for online State of Health (SoH) is derived and validated, showing an estimation accuracy of %.Open AccessInvestigation of the Suitability of the DTV Method for the Online SoH Estimation of NMC Lithium-Ion Cells in Battery Management Systems
Investigating the temperature behavior of lithium-ion battery cells has become an important part of today’s research and development. The main reason for this is that the temperature profile of a battery cell changes during aging. By using Differential Thermal Voltammetry (DTV), new possibilities are opened up, especially since this diagnostic method is designed to work in operando by only requiring voltage and temperature readings. In this study, a batch of NMC-21700 cells were aged in calendar and cyclic manners. After a specified aging cycle was complete, a check-up measurement was performed. During this time, the cycler collected the electrical measuring values, while a negative temperature coefficient thermistor, which was located on the cell, was used to record the temperature fluctuations. The data were then evaluated by using the DTV analysis technique. By comparing the characteristic points of DTV, correlations between the changing curve characteristics and the capacity loss, and therefore the aging of the respective cell, were established. Based on these results, a simple model suitable for online State of Health (SoH) is derived and validated, showing an estimation accuracy of %. - Open Access
Online State-of-Health Estimation for NMC Lithium-Ion Batteries Using an Observer Structure
State-of-health (SoH) estimation is one of the key tasks of a battery management system, (BMS) as battery aging results in capacity- and power fade that must be accounted for by the BMS to ensure safe operation over the battery’s lifetime. In this study, an online SoH estimator approach for NMC Li-ion batteries is presented which is suitable for implementation in a BMS. It is based on an observer structure in which the difference between a calculated and expected open-circuit voltage (OCV) is used for online SoH estimation. The estimator is parameterized and evaluated using real measurement data. The data were recorded for more than two years on an electrified bus fleet of 10 buses operated in a mild European climate and used regularly in the urban transport sector. Each bus is equipped with four NMC Li-ion batteries. Every battery has an energy of 30.6 kWh. Additionally, two full-capacity checkup measurements were performed for one of the operated batteries: one directly after production and one after two years of operation. Initial validation results demonstrated a SoH estimation accuracy of ±0.5% compared to the last checkup measurement.
Open AccessOnline State-of-Health Estimation for NMC Lithium-Ion Batteries Using an Observer Structure
State-of-health (SoH) estimation is one of the key tasks of a battery management system, (BMS) as battery aging results in capacity- and power fade that must be accounted for by the BMS to ensure safe operation over the battery’s lifetime. In this study, an online SoH estimator approach for NMC Li-ion batteries is presented which is suitable for implementation in a BMS. It is based on an observer structure in which the difference between a calculated and expected open-circuit voltage (OCV) is used for online SoH estimation. The estimator is parameterized and evaluated using real measurement data. The data were recorded for more than two years on an electrified bus fleet of 10 buses operated in a mild European climate and used regularly in the urban transport sector. Each bus is equipped with four NMC Li-ion batteries. Every battery has an energy of 30.6 kWh. Additionally, two full-capacity checkup measurements were performed for one of the operated batteries: one directly after production and one after two years of operation. Initial validation results demonstrated a SoH estimation accuracy of ±0.5% compared to the last checkup measurement.