Explore the vast range of titles available.

Battery energy storage systems have gained increasing interest for serving grid support in various application tasks. In particular, systems based on lithium-ion batteries have evolved rapidly with a wide range of cell technologies and system architectures available on the market. On the application side, different tasks for storage deployment demand distinct properties of the storage system. This review aims to serve as a guideline for best choice of battery technology, system design and operation for lithium-ion based storage systems to match a specific system application. Starting with an overview to lithium-ion battery technologies and their characteristics with respect to performance and aging, the storage system design is analyzed in detail based on an evaluation of real-world projects. Typical storage system applications are grouped and classified with respect to the challenges posed to the battery system. Publicly available modeling tools for technical and economic analysis are presented. A brief analysis of optimization approaches aims to point out challenges and potential solution techniques for system sizing, positioning and dispatch operation. For all areas reviewed herein, expected improvements and possible future developments are highlighted. In order to extract the full potential of stationary battery storage systems and to enable increased profitability of systems, future research should aim to a holistic system level approach combining not only performance tuning on a battery cell level and careful analysis of the application requirements, but also consider a proper selection of storage sub-components as well as an optimized system operation strategy.

Battery energy storage systems (BESS) coupled with rooftop-mounted residential photovoltaic (PV) generation, designated as PV-BESS, draw increasing attention and market penetration as more and more such systems become available. The manifold BESS deployed to date rely on a variety of different battery technologies, show a great variation of battery size, and power electronics dimensioning. However, given today’s high investment costs of BESS, a well-matched design and adequate sizing of the storage systems are prerequisites to allow profitability for the end-user. The economic viability of a PV-BESS depends also on the battery operation, storage technology, and aging of the system. In this paper, a general method for comprehensive PV-BESS techno-economic analysis and optimization is presented and applied to the state-of-art PV-BESS to determine its optimal parameters. Using a linear optimization method, a cost-optimal sizing of the battery and power electronics is derived based on solar energy availability and local demand. At the same time, the power flow optimization reveals the best storage operation patterns considering a trade-off between energy purchase, feed-in remuneration, and battery aging. Using up to date technology-specific aging information and the investment cost of battery and inverter systems, three mature battery chemistries are compared; a lead-acid (PbA) system and two lithium-ion systems, one with lithium-iron-phosphate (LFP) and another with lithium-nickel-manganese-cobalt (NMC) cathode. The results show that different storage technology and component sizing provide the best economic performances, depending on the scenario of load demand and PV generation.

In the context of the increased acceptance and usage of electric vehicles (EVs), vehicle-to-building (V2B) has proven to be a new and promising use case. Although this topic is already being discussed in literature, there is still a lack of experience on how such a system, of allowing bidirectional power flows between an EV and building, will work in a residential environment. The challenge is to optimize the interplay of electrical load, photovoltaic (PV) generation, EV, and optionally a home energy storage system (HES). In total, fourteen different scenarios are explored for a German household. A two-step approach is used, which combines a computationally efficient linear optimizer with a detailed modelling of the non-linear effects on the battery. The change in battery degradation, storage system efficiency, and operating expenses (OPEX) as a result of different, unidirectional and bidirectional, EV charging schemes is examined for both an EV battery and a HES. The simulations show that optimizing unidirectional charging can improve the OPEX by 15%. The addition of V2B leads to a further 11% cost reduction, however, this corresponds with a 12% decrease in EV battery lifetime. Techno-economic analysis reveals that the V2B charging solution with no HES leads to strong self-consumption improvements (EUR 1381 savings over ten years), whereas, this charging scheme would not be justified for a residential prosumer with a HES (only EUR 160 savings).

Young’s modulus is a key parameter to describe the compressive behavior of battery electrodes and is therefore frequently employed in mechanical models. In most studies, this property is determined using pristine electrodes. However, during electrochemical cycling, lithium insertion and extraction can alter the mechanical response of the active materials. The literature lacks SOC-dependent compression data of electrodes with different active materials. Especially for LFP electrodes, no SOC dependencies have been reported. This study closes this gap by performing compression tests on graphite, NMC, and LFP electrodes at different states of charge. The results show that the stiffness of graphite and NMC electrodes increases with higher lithium contents, whereas the compressive behavior of LFP remains independent of the lithium content. These findings are consistent with material-level properties reported in the literature. Two hypotheses are proposed to explain this behavior: one hypothesis is related to the contribution of active material particles to electrode deformation and the other hypothesis is related to microstructural changes governed by particle diameter.

Parameter identification with the pseudo-two-dimensional (p2D) model has been an important research topic in battery engineering because some of the physicochemical parameters used in the model can be measured, while some can only be estimated or calculated based on the measurement data. Various methods, either in the time domain or frequency domain, have been proposed to identify the parameters of the p2D model. While the methods in each domain bring their advantages and disadvantages, a comprehensive comparison regarding parameter identifiability and accuracy is still missing. In this present work, some selected physicochemical parameters of the p2D model are identified in four different cases and with different methods, either only in the time domain or with a combined model. Which parameters are identified in the frequency domain is decided by a comprehensive analysis of the analytical expression for the DRT spectrum. Finally, the parameter identifiability results are analyzed and the validation results with two highly dynamic load profiles are shown and compared. The results indicate that the model with ohmic resistance and the combined method achieves the best performance and the average voltage error is at the level of 12 mV.

To achieve maximum profit by dispatching a battery storage system in an arbitrage operation, multiple factors must be considered. While revenue from the application is determined by the time variability of the electricity cost, the profit will be lowered by costs resulting from energy efficiency losses, as well as by battery degradation. In this paper, an optimal dispatch strategy is proposed for storage systems trading on energy arbitrage markets. The dispatch is based on a computationally-efficient implementation of a mixed-integer linear programming method, with a cost function that includes variable-energy conversion losses and a cycle-induced battery capacity fade. The parametrisation of these non-linear functions is backed by in-house laboratory tests. A detailed analysis of the proposed methods is given through case studies of different cost-inclusion scenarios, as well as battery investment-cost scenarios. An evaluation with a sample intraday market data set, collected throughout 2017 in Germany, offers a potential monthly revenue of up to 8762 EUR/MWh cap installed capacity, without accounting for the costs attributed to energy losses and battery degradation. While this is slightly above the revenue attainable in a reference application—namely, primary frequency regulation for the same sample month (7716 EUR/MWh cap installed capacity)—the situation changes if costs are considered: The optimisation reveals that losses in battery ageing and efficiency reduce the attainable profit by up to 36% for the most profitable arbitrage use case considered herein. The findings underline the significance of considering both ageing and efficiency in battery system dispatch optimisation.

Silicon is a promising anode material and can already be found in commercially available lithium-ion cells. Reliable modeling and simulations of new active materials for lithium-ion batteries are becoming more and more important, especially regarding cost-efficient cell design. Because literature lacks an electrochemical model for silicon-dominant electrodes, this work aims to close the gap. To this end, a Newman p2D model for a lithium-ion cell with a silicon-dominant anode and a nickel-cobalt-aluminum-oxide cathode is parametrized. The micrometer silicon particles are partially lithiated to 1200 mAh gSi−1. The parametrization is based on values from the electrode manufacturing process, measured values using lab cells, and literature data. Charge and discharge tests at six different C-rates up to 2C serve as validation data, showing a root-mean-squared error of about 21 mV and a deviation in discharge capacity of about 1.3%, both during a 1 C constant current discharge. Overall, a validated parametrization for a silicon-dominant anode is presented, which, to the best of our knowledge, is not yet available in literature. For future work, more in-depth studies should investigate the material parameters for silicon to expand the data available in the literature and facilitate further simulation work.

The temperature of lithium-ion batteries is crucial in terms of performance, aging, and safety. The internal temperature, which is complicated to measure with conventional temperature sensors, plays an important role here. For this reason, numerous methods exist in the literature for determining the internal cell temperature without sensors, which are usually based on electrochemical impedance spectroscopy. This study presents a method in the time domain, based on the pulse resistance, for determining the internal cell temperature by examining the temperature behavior for the cylindrical formats 18650, 21700, and 26650 in isothermal and transient temperature states for different states of charge (SOCs). A previously validated component-resolved 2D thermal model was used to analyze the location of the calculated temperature TR within the cell, which is still an unsolved question for pulse resistance-based temperature determination. The model comparison shows that TR is close to the average jelly roll temperature. The differences between surface temperature and TR depend on the SOC and cell format and range from 2.14K to 2.70K (18650), 3.07K to 3.85K (21700), and 4.74K to 5.45K (26650). The difference decreases for each cell format with increasing SOC and is linear dependent on the cell diameter.

Cylindrical 18650 and 21700 lithium-ion batteries are produced with small gaps between the jelly roll and the case. The size of these gaps and the mechanical attachment of the jelly roll to the case can have a significant impact on the thermal and mechanical properties of cells. To investigate the influence of the state of charge (SOC) and state of health (SOH) on the size of the gap, computed tomography (CT) and gray-value analysis was conducted with various cell types at 0% and 100% SOC and after cycling. The results show a significant influence of the SOC on the gap for new cells and a substantial reduction in the gap during the first cycles.

As electric vehicles are gaining increasing worldwide interest, advances in driving range and safety become critical. Modern automotive battery management systems (BMS) compete with challenging performance and safety requirements and need to monitor a large amount of battery parameters. In this paper, we propose power line communications (PLC) for high voltage (HV) traction batteries to reduce the BMS wiring effort. By modeling a small-scale battery pack for frequencies up to 300 MHz, we predict the PLC channel transfer characteristics and validate the results using a PLC hardware demonstrator employing a narrowband single-carrier modulation. The results demonstrate that battery PLC is a demanding task due to low access impedances and cell coupling effects, yet transfer characteristics can be improved by optimal impedance matching. PLC for HV BMS not only saves weight and cost, but also improves flexibility in BMS design. PLC enables single-cell monitoring techniques such as online electrochemical impedance spectroscopy (EIS) without additional wiring. Online EIS can be used for in-situ state and temperature estimation saving extra sensors. This work unveils possible coexistence issues between PLC and battery monitoring. In particular, we demonstrate that certain PLC data or packet rates have to be avoided not to interfere with EIS measurements.