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.

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 $1.1$%.

Due to its improved capacity compared to graphite, silicon is a promising candidate to handle the demands of high-energy batteries. With the introduction of new materials, further aspects of the battery system must be reconsidered. One of those aspects is the heat generation during the charging and discharging of a cell, which delivers important information for the development of cooling systems, the battery management system and the overall performance of the cell. Since the reversible heat presents an important contribution to the overall heat generation during cycling, the entropy coefficient is the main value that needs to be determined. This study evaluates the entropy coefficient of custom-produced 2032 coin half-cells with lithium counter electrodes, containing 45 wt% nanosilicon and 45 wt% carbon black. The potentiometric method, utilizing VR and self-discharge curves, produced reliable results, yielding entropy coefficient values between 95% SoC and 10% SoC during delithiation. These values of the entropy coefficient are consistently negative. Furthermore, ICA measurements identified two phase transitions during delithiation, with these transitions shifting to lower SoC as SoH decreases, impacting the slope of the entropy coefficient.

The heat generation of lithium-ion batteries is a critical parameter, as it significantly affects cell temperature. Poor thermal management can lead to elevated cell temperatures, accelerating side reactions, reducing cell lifetime, and, in extreme cases, causing thermal runaway. Therefore, understanding heat generation is crucial for the commercialization of emerging battery materials. Due to its high energy density, lithium–nickel–manganese–oxide (LNMO) is an attractive candidate for next-generation cathode materials; however, the composition of its heat generation is not yet fully understood. To address this, the state-of-charge (SoC)-dependent entropy coefficient and resistance of disordered LNMO cathodes are determined using the potentiometric method. The results show that both values are strongly influenced by the redox reactions of Ni and Mn. The entropy coefficient varies between 5.2 and −32.4 J ${\mathrm{mol}}^{-1}{\mathrm{K}}^{-1}$, depending on the SoC. Furthermore, the resistance exhibits a switching dependence on kinetics and mass transfer. The resulting heat flux calculations indicate that, at SoC < 20%, heat generation is dominated by the kinetic behavior of LNMO, leading to two exothermal peaks during discharge and one exothermal peak during charge. This behavior is validated through a comparison with a low-current calorimetric measurement.