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Lithium-ion batteries (LIBs) are employed in a range of devices due to their high energy and power density. However, the increased power density of LIBs raises concerns regarding their safety when subjected to external abuse. The thermal behavior is influenced by a number of factors, i.e., the state of charge (SoC), the cell chemistry and the abuse conditions. In this study, three distinct cylindrical Li-ion cells, i.e., lithium nickel cobalt aluminum oxide (NCA), lithium titanate oxide (LTO), and lithium iron phosphate (LFP), were subjected to thermal abuse (heating rate of 5 °C/min) in an air flow reactor, with 100% SoC. Venting and thermal runaway (TR) were recorded in terms of temperature and pressure, while the emitted products (gas, solid, and liquid) were subjected to analysis by FT-IR and ICP-OES. The concentrations of the toxic gases (HF, CO) are significantly in excess of the Immediate Danger to Life or Health Limit (IDLH). Furthermore, it is observed that the solid particles are the result of electrode degradation (metallic nature), whereas the liquid aerosol is derived from the electrolyte solvent. It is therefore evident that in the event of a LIB fire, in order to enhance the safety of the emergency responders, it is necessary to use appropriate personal protective equipment (PPE) in order to minimize exposure to toxic substances, i.e., particles and aerosol.

Significant efforts are being made across academia and industry to better characterize lithium ion battery cells as reliance on the technology for applications ranging from green energy storage to electric mobility increases. The measurement of short-term and long-term volume expansion in lithium-ion battery cells is relevant for several reasons. For instance, expansion provides information about the quality and homogeneity of battery cells during charge and discharge cycles. Expansion also provides information about aging over the cell’s lifetime. Expansion measurements are useful for the evaluation of new materials and the improvement of end-of-line quality tests during cell production. These measurements may also indicate the safety of battery cells by aiding in predicting the state of charge and the state of health over the lifetime of the cell. Expansion measurements can also assess inhomogeneities on the electrodes, in addition to defects such as gas accumulation and lithium plating. In this review, we first establish the mechanisms through which reversible and irreversible volume expansion occur. We then explore the current state-of-the-art for both contact and noncontact measurements of volume expansion. This review compiles the existing literature on four approaches to contact measurement and eight noncontact measurement approaches. Finally, we discuss the different considerations when selecting an appropriate measurement technique.

To meet the load voltage and power requirements for various specific needs, a typical lithium–ion battery (LIB) pack consists of different parallel and series combinations of individual cells in modules, which can go as high as tens of series and parallel connections in each module, reaching hundreds and even thousands of cells at high voltage (HV) levels. The inhomogeneity among the cells and modules results in voltage imbalances during operation and reduces the overall system efficiency. In this work, a robust and flexible active balancing topology is presented. It can not only mitigate the charge imbalance within a module, i.e., intramodular equalization, but also help to balance the state of charge (SoC) level of the modules in a high voltage pack, i.e., intermodular equalization, which is an often-overlooked topic. The proposed concept was proven by experimental verification on parallel and series configurations of cells in realistically sized modules and practical battery management system (BMS) hardware, when the LIB was both idle and under load.

With the rapid development of research into flexible electronics and wearable electronics in recent years, there has been an increasing demand for flexible power supplies, which in turn has led to a boom in research into flexible solid-state lithium-ion batteries. The ideal flexible solid-state lithium-ion battery needs to have not only a high energy density, but also good mechanical properties. We have taken a systematic and comprehensive overview of our work in two main areas: flexible materials and flexible structures. Specifically, we first discuss materials for electrodes (carbon nanotubes, graphite, carbon fibers, carbon cloth, and conducting polymers) and flexible solid materials for electrolytes. A discussion of the structural design of flexible solid-state lithium-ion batteries, including one-dimensional fibrous, two-dimensional thin-film and three-dimensional flexible lithium-ion batteries, follows this. In addition, the advantages and disadvantages of different materials and structures are summarized, and the main challenges for the future design of flexible solid-state lithium-ion batteries are pointed out, hopefully providing some reference for the research of flexible solid-state lithium-ion batteries.

Lithium batteries are being utilized more widely, increasing the focus on their thermal safety, which is primarily brought on by their thermal runaway. This paper’s focus is the energy storage power station’s 50 Ah lithium iron phosphate battery. An in situ eruption study was conducted in an inert environment, while a thermal runaway experiment was conducted utilizing sealed pressure containers and an external heating triggering mechanism. Both the amount of gas release and the battery’s maximum temperature were discovered. Using gas chromatography, the gas emission from the battery was examined. Its principal constituents included CO, H2, CO2, CH4, C2H4, and so on. Moreover, the experiment discovered a second eruption of lithium iron phosphate, and the stage of its eruption was separated by the pressure signal of the sealed experimental chamber, giving a theoretical foundation and technological backing for the thermal catastrophe safety of lithium batteries.

This article constitutes a relatively new perspective that has emerged from the need to reduce environmental pollution from internal combustion engine vehicles (ICEVs) by reinforcing the fleet of electric vehicles (EVs) on the road. Future requirements to exclusively use zero-emission vehicles have resulted in the necessity of enhancing the testing and monitoring process for EVs in order to release reliable devices. The unpredictable response of lithium-ion batteries (LIBS), future lack of raw materials, and inconsistencies in the present regulations must be reviewed and understood in order to develop enhanced batteries. This article aims to outline the future perspective of nonconventional vehicles monopolizing the roads by year 2035 in order to eradicate CO2 emissions by year 2050.

This article addresses the development of the energy compensation method used for the design of hybrid energy storage systems—HBESS. The combination of two battery technologies offers better cost and performance when considering microgrid systems to provide uninterrupted power to sensitive loads (substation auxiliary system) and also provides greater energy security. In the event of a failure, the load needs to continue operating, and batteries such as lithium ions have a fast response, but are expensive for large-scale systems. However, some technologies offer low-cost and good availability of energy for long hours of discharge, such as lead–acid batteries. Consequently, different battery technologies can be used to meet all the needs of the sensitive loads. A specific method for sizing a HBESS was developed for islanded microgrids to support sensitive loads. This method was developed to meet the demand for substations outside the Brazilian standard of power systems that lack an uninterrupted and reliable energy source. The method is validated by designing a microgrid to support the auxiliary systems of a transmission substation in northeastern Brazil. The results showed a system with a capacity of 1215 kWh of lead-carbon and 242 kWh of lithium ions is necessary to maintain an islanded microgrid for at least 10 h. Furthermore, the microgrid comprises a PV plant with an AC output power of 700 kW in connected operation and 100 kW when islanded from the grid.

Due to the simple structure and the possibility of manual production, coin cells enable fast and, compared to larger cell formats, an inexpensive examination option in battery research. The comparability and traceability of coin cell structures in literature are only feasible to a limited extent due to the lack of a standard in manual production. Since the findings from the literature are barely building up on each other and have not been repeated, a full factorial Design of Experiments (DoE) was performed to investigate the significance of earlier findings in terms of their influence on the reproducibility of the performance. The parameters studied were the anode-to-cathode ratio, the amount of electrolyte, the spring type and the separator count. To quantify the reproducibility of coin cell assembly, the number of functional cells (here: successful formation followed by 30 cycles) and the empirical coefficient of variation for the performance parameters discharge capacity, internal resistance and coulombic efficiency were compared. The critical parameters found in prior literature have no statistically significant influence on reproducibility when focusing on the number of functional cells. Instead, other uninvestigated parameters seem to influence the system coin cell more. By further examining the parameter settings that produced the most functional cells (≥75% of 8 cells), guidance for constructing coin cells (type R2032) was suggested, and other potential influencing parameters are discussed for further study.

Enhancing the accuracy of the battery state of charge (SOC) estimation is essential in developing more effective, dependable, and convenient electric vehicles. In this paper, a hybrid CNN and gated recurrent unit-long short-term memory (CNN-GRU-LSTM) approach, which is a recurrent neural network (RNN) based model with an explainable artificial intelligence (EAI) was used for the battery SOC estimation, where the cell parameters were explicitly synchronized to the SOC. The complexed link between the monitoring signals related to current, voltage, and temperature, and the battery SOC, was established using the deep learning (DL) technique. A LG 18650HG2 li-ion battery dataset was used for training the model so that the battery was subjected to a dynamic process. Moreover, the data recorded at ambient temperatures of −10 °C, 0 °C, 10 °C, and 25 °C are fed into the method during training. The trained model was subsequently used to estimate the SOC instantaneously on the testing datasets. At first, the training process was carried out with all temperature data to estimate the SOC by the trained model at various ambient temperatures. The proposed approach was capable to encapsulate the relationships on time into the network weights and, as a result, it produced more stable, accurate, and reliable estimations of the SOC, compared to that by some other existing networks. The hybrid model achieved a mean absolute error (MAE) of 0.41% to 1.13% for the −10 °C to 25 °C operating temperatures. The EAI was also utilized to explain the battery SOC model making certain decisions and to find out the significant features responsible for the estimation process.

Nowadays, due to the increasing use of electric vehicles, manufacturers are making more and more innovations in the batteries used in electromobility, in order to make these vehicles more efficient and provide them with greater autonomy. This has led to the need to evaluate and compare the efficiency of different batteries used in electric vehicles to determine which one is the best to be implemented. This paper characterises, models and compares three batteries used in electromobility: lithium-ion, lead-acid, and nickel metal hydride, and determines which of these three is the most efficient based on their state of charge. The main drawback to determine the state of charge is that there are a great variety of methods and models used for this purpose; in this article, the Thévenin model and the Coulomb Count method are used to determine the state of charge of the battery. When obtaining the electrical parameters, the simulation of the same is carried out, which indicates that the most efficient battery is the Lithium-ion battery presenting the best performance of state of charge, reaching 99.05% in the charging scenario, while, in the discharge scenario, it reaches a minimum value of 40.68%; in contrast, the least efficient battery is the lead acid battery, presenting in the charging scenario a maximum value of 98.42%, and in the discharge scenario a minimum value of 10.35%, presenting a deep discharge. This indicates that the lithium-ion battery is the most efficient in both the charge and discharge scenarios, and is the best option for use in electric vehicles. In this paper, it was decided to use the Coulomb ampere counting method together with the Thévenin equivalent circuit model because it was determined that the combination of these two methods to estimate the SOC can be applied to any battery, not only applicable to electric vehicle batteries, but to battery banks, BESS systems, or any system or equipment that has batteries for its operation, while the models based on Kalman, or models based on fuzzy mathematics and neural networks, as they are often used and are applicable only to a specific battery system.

The increasing popularity of electric vehicles (EVs) has been attributed to their low-carbon and environmentally friendly attributes. Extensive research has been undertaken in view of the depletion of fossil fuels, changes in climatic conditions due to air pollution, and the goal of developing EVs capable of matching or exceeding the performance of today’s internal combustion engines (ICEs). The transition from ICE vehicles to EVs can reduce greenhouse gases significantly over a vehicle’s lifetime. Across the different types of EVs, the widespread usage of batteries is due to their high power density and steady output voltage, making them an excellent energy storage device (ESD). The current downsides of battery-powered electric vehicles include long recharge times, the impact of additional strain on the grid, poor societal acceptance due to high initial costs, and a lack of adequate charging infrastructure. Even more problematic is their short driving range when compared to standard ICE and fuel cell EVs. Battery degradation occurs when the capacity of a battery degrades, resulting in a reduction in travel range. This review article includes a description of battery degradation, degradation mechanisms, and types of degradation. A detailed investigation of the methods used to address and reduce battery degeneration is presented. Finally, some future orientation in terms of EV research is offered as vital guidance for academic and industrial partners.

The market for eco-friendly batteries is increasing owing to population growth, environmental pollution, and energy crises. The widespread application of lithium-ion batteries necessitates their state of health (SOH) estimation, which is a popular and difficult area of research. In general, the capacity of a battery is selected as a direct health factor to characterize the degradation state of the battery’s SOH. However, it is difficult to directly measure the actual capacity of a battery. Therefore, this study extracted three features from the current, voltage, and internal resistance of a lithium-ion battery during its charging–discharging process to estimate its SOH. A battery-accelerated aging test system was designed to obtain time series battery degradation data. A performance comparison of lithium-ion battery SOH fitting results was conducted for two different deep learning architectures, a long short-term memory (LSTM) network and temporal convolution network (TCN), which are time series deep learning networks based on a recurrent neural network (RNN) and convolutional neural network (CNN), respectively. The results showed that the proposed method has high prediction accuracy, while the performance of the TCN was 3% better than that of the LSTM regarding the average maximum relative error in SOH estimation of a lithium-ion battery.

In many studies, for predicting the remaining capacity of batteries belonging to different electrochemical systems, various analytical models based on the Peukert equation are used. This paper evaluates the advantages and disadvantages of the most famous generalized Peukert equations. For lithium-ion batteries, the Peukert equation cannot be used for estimation of their remaining capacity over the entire range of discharge currents. However, this paper proves that the generalized Peukert equations enable estimation of the capacity released by lithium-ion batteries with high accuracy. Special attention is paid to two generalized Peukert equations: C = Cm/(1 + (i/i0)n) and C = Cmerfc((i-i0)/n))/erfc(-i0/n). It is shown that they correspond to the experimental data the best.

The degradation of lithium-ion cells is an important aspect, not only for quality management, but also for the customer of the application like, e.g., scooters or electric vehicles. During the lifetime of the system, the overall health on the battery plays a key role in its depreciation. Therefore, it is necessary to monitor the health of the battery during operation, i.e., cycle life, but also during stationary conditions, i.e., calendar aging. In this work, the degradation due to calendar aging is analyzed for six different cell chemistries in terms of capacity degradation and impedance increase and their performance are being compared. In a new proposed metric, the relative deviations between various cells with the exact identical aging history are being analyzed for their degradation effects and their differences, which stands out in comparison to similar research. The capacity loss was found to be most drastic at 60 °C and at higher storage voltages, even for titanate-oxide cells. LiNiMnCoO2 (NMC), LiNiCoAlO2 (NCA) and Li2TiO3 (LTO) cells at 60 °C showed the most drastic capacity decrease. NMC and NCA cells at 60 °C and highest storage voltage did not show any open circuit voltage, as their current interrupt mechanism triggered. The effect of aging shows no uniform impact on the changes in the capacity variance when comparing different aging conditions, with respect to the evaluated standard deviation for all cells. The focus of this work was on the calendar aging effect and may be supplemented in a second study for cyclic aging.

Battery degradation is a fundamental concern in battery research, with the biggest challenge being to maintain performance and safety upon usage. From the microstructure of the materials to the design of the cell connectors in modules and their assembly in packs, it is impossible to achieve perfect reproducibility. Small manufacturing or environmental variations will compound big repercussions on pack performance and reliability. This review covers the origins of cell-to-cell variations and inhomogeneities on a multiscale level, their impact on electrochemical performance, as well as their characterization and tracking methods, ranging from the use of large-scale equipment to in operando studies.

This paper examines the specifications of lithium battery cells, which are considered one of the most vital sources for electrical energy storage units. The specifications have been covered to associate battery performance with its usage for electrically powered motor vehicles. With the motivation of rapid deployment of electric vehicles (EVs) around the world, the key contribution of this study is to provide a comparative investigation of well-known commercially available Li-ion battery cells used as a pack for electric race car. Five lithium cells from different manufacturers were analyzed for start voltage, end voltage, current, and the use of active cooling under different test conditions. Thermal imaging was used to provide more comprehensive analysis of tested battery packs. The outcomes of this experimental investigation are described in the sections below in the order in which the analyses were conducted. The key findings of this study are presented in the conclusion section.

Energy storage is a key solution to supply renewable electricity on demand and in particular batteries are becoming attractive for consumers who install PV panels. In order to minimize their electricity bill and keep the grid stable, batteries can combine applications. The daily match between PV supply and the electricity load profile is often considered as a determinant for the attractiveness of residential PV-coupled battery systems, however, the previous literature has so far mainly focused on the annual energy balance. In this paper, we analyze the techno-economic impact of adding a battery system to a new PV system that would otherwise be installed on its own, for different residential electricity load profiles in Geneva (Switzerland) and Austin (U.S.) using lithium-ion batteries performing various consumer applications, namely PV self-consumption, demand load-shifting, avoidance of PV curtailment, and demand peak shaving, individually and jointly. We employ clustering of the household’s load profile (with 15-minute resolution) for households with low, medium, and high annual electricity consumption in the two locations using a 1:1:1 sizing ratio. Our results show that with this simple sizing rule-of-thumb, the shape of the load profile has a small impact on the net present value of batteries. Overall, our analysis suggests that the effect of the load profile is small and differs across locations, whereas the combination of applications significantly increases profitability while marginally decreasing the share of self-consumption. Moreover, without the combination of applications, batteries are far from being economically viable.

CubeSats and small satellite solutions are increasing in popularity as they enable a fast, cheap, and agile way for satellite applications. An essential component of nearly every satellite is the energy storage device, which is practically equal to a battery. Consequently, an overview of past, present, and future battery technologies for CubeSats is presented. CubeSats use typically commercial off-the-shelf (COTS) batteries. They are not primarily dedicated to space, so their suitability to the space environment needs to be evaluated. Batteries are also considered as potentially dangerous goods. Thus, there are guidelines and standards that specify safety criteria and tests for the batteries in order to be allowed for transportation and launch. Furthermore, the character of satellites’ missions determines their demand on batteries in terms of current rates, depth-of-discharge, and lifetime. Thus, these expectations are discussed. A market survey was also carried out to identify currently available commercial battery solutions and their parameters. This work summarizes the status, requirements, and the market situation of batteries for CubeSats.

Philippine off-grid islands are mostly electrified by diesel generators, resulting in costly electricity that is interrupted by fuel supply disruptions. The archipelagic nature of the country also impedes off-grid electrification due to the high capital cost of grid extension. Transitioning from diesel-only systems to hybrid renewable energy systems and interconnecting the island microgrids can solve these problems while promoting cleaner energy production. In this work, a comparative study on decentralized and clustered hybrid renewable energy system microgrids in the Polillo group of islands in the Philippines, using HOMER Pro, was performed. Microgrids comprising solar photovoltaics, lithium-ion battery energy storage, and diesel generators were designed on each island. Clustered systems encompassing multiple islands in the island group were simulated by also considering the least-cost interconnection paths. The techno-economics of each decentralized or clustered system and the four-island system were evaluated based on the levelized cost of electricity (LCOE). Reliability was assessed using the change in LCOE upon the failure of a component and during weather disturbances. Transitioning from diesel-only systems to hybrid systems reduces generation costs by an average of 42.01% and increases the renewable energy share to 80%. Interconnecting the hybrid systems results in an average increase of 2.34% in generation costs due to the cost of submarine cables but improves system reliability and reduces the optimum solar photovoltaic and lithium-ion storage installations by 6.66% and 8.71%, respectively. This research serves as a framework for the interconnection pre-feasibility analysis of other small off-grid islands.

Stationary battery systems are becoming increasingly common worldwide. Energy storage is a key technology in facilitating renewable energy market penetration and battery energy storage systems have seen considerable investment for this purpose. Large battery installations such as energy storage systems and uninterruptible power supplies can generate substantial heat in operation, and while this is well understood, the thermal management systems that currently exist have not kept pace with stationary battery installation development. Stationary batteries operating at elevated temperatures experience a range of deleterious effects and, in some cases, serious safety concerns can arise. Optimal thermal management prioritizes safety and balances costs between the cooling system and battery degradation due to thermal effects. Electric vehicle battery thermal management has undergone significant development in the past decade while stationary battery thermal management has remained mostly stagnant, relying on the use of active and passive air cooling. Despite being the default method for thermal management, there is an absence of justifying research or comparative reviews. This literature review seeks to define the role of stationary battery systems in modern power applications, the effects that heat generation and temperature have on the performance of these systems, thermal management methods, and future areas of study.

Within Li-ion batteries, lithium plating is considered as one of the main reasons behind the capacity fade that occurs during low temperature and fast charging conditions. Previous studies indicate that plating is influenced by the levels of loss of lithium inventory (LLI) and the loss of active material (LAM) present in a battery. However, it is not clear from the literature on how lithium plating influences battery degradation in terms of LAM and LLI. Quantifying the undesirable impacts of lithium plating can help in understanding its impact on battery degradation and feedback effects of previous lithium plating on the formation of present plating. This study aims to quantify the degradation modes of lithium plating: LLI, LAM at the electrode level. A commercial Li-ion cell was first, aged using two different cases: with and without lithium plating. Second, a degradation diagnostic method is developed to quantify the degradation modes based on their measurable effects on open-circuit voltage (OCV) and cell capacity. The results highlight that LAMNE and LLI levels under the fast charge profile are increased by 10% and 12%, respectively, compared to those under the less aggressive charge profile. Further, limitations of the degradation analysis methods are discussed.

The energy storage industry has expanded globally as costs continue to fall and opportunities in consumer, transportation, and grid applications are defined. As the rapid evolution of the industry continues, it has become increasingly important to understand how varying technologies compare in terms of cost and performance. This paper defines and evaluates cost and performance parameters of six battery energy storage technologies (BESS)—lithium-ion batteries, lead-acid batteries, redox flow batteries, sodium-sulfur batteries, sodium-metal halide batteries, and zinc-hybrid cathode batteries—four non-BESS storage systems—pumped storage hydropower, flywheels, compressed air energy storage, and ultracapacitors—and combustion turbines. Cost and performance information was compiled based on an extensive literature review, conversations with vendors and stakeholders, and costs of systems procured at sites across the United States. Detailed cost and performance estimates are presented for 2018 and projected out to 2025. Annualized costs were also calculated for each technology.

The usage of electric vehicle batteries to assist the main electric grid for the storage of energy provided by intermittent sources should become an essential tool to increase the penetration of green energies. However, this service induces additional usage on the cells and, therefore, could degrade them further. Since degradation is path-dependent, it is of paramount importance to test the impact of all the different grid applications on the batteries. In this work, we tested the additional usage induced by using electric vehicle batteries for frequency regulation at moderate rates during rest or charge and found no detrimental effect after around 2000 cycles on the cells.

Conjugated coordination polymers attract attention as materials for electrochemical energy storage, mostly as cathode materials for supercapacitors. Faradaic capacity may be introduced to such materials using redox-active building blocks, metals, or ligands. Using this strategy, a novel hybrid cathode material was developed based on a Ni2+ metal-organic polymer. The proposed material, in addition to double-layer capacitance, shows high pseudocapacitance, which arises from the contributions of both the metal center and ligand. A tailoring strategy in the ligand design allows us to minimize the molecular weight of the ligand, which increases its gravimetric energy. According to computational results, the ligand makes the prevailing contribution to the pseudocapacitance of the material. Different approaches to metal–organic polymer (MOP) synthesis were implemented, and the obtained materials were examined by FTIR, Raman spectroscopy, powder XRD, SEM/EDX (energy-dispersive X-ray spectroscopy), TEM, and thermal analysis. Energy-storage performance was comparatively studied with cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD). As a result, materials with an excellent discharge capacity were obtained, reaching the gravimetric energy density of common inorganic cathode materials.

The aim of this work is to age commercial battery cells far beyond their expected lifetime. There is a gap in the literature regarding run to failure tests of lithium-ion batteries that this work intends to address. Therefore, twenty new Samsung ICR18650-26F cells were aged as a battery pack in a run to failure test. Aging took place with a constant load current and a constant charge current to accelerate capacity decrease. Important aging parameters such as capacity and internal resistance were measured at each cycle to monitor their development. The end of the test was initiated by the explosion of a single battery cell, after which the battery pack was disassembled and all parameters of the still intact single cells were measured. The distribution of all measured capacities and internal resistances is displayed graphically. This clearly shows the influence of the exploded cell on the cells in its immediate vicinity. Selected cells from this area of the battery were subjected to computed tomography (CT) to detect internal defects. The X-rays taken with computed tomography showed clear damage within the jelly roll, as well as the triggered safety mechanisms.

The renewable energy transition has introduced new electricity tariff structures. With the increased penetration of photovoltaic and wind power systems, users are being charged more for their peak demand. Consequently, peak shaving has gained attention in recent years. In this paper, we investigated the potential of peak shaving through battery storage. The analyzed system comprises a battery, a load and the grid but no renewable energy sources. The study is based on 40 load profiles of low-voltage users, located in Belgium, for the period 1 January 2014, 00:00−31 December 2016, 23:45, at 15 min resolution, with peak demand pricing. For each user, we studied the peak load reduction achievable by batteries of varying energy capacities (kWh), ranging from 0.1 to 10 times the mean power (kW). The results show that for 75% of the users, the peak reduction stays below 44% when the battery capacity is 10 times the mean power. Furthermore, for 75% of the users the battery remains idle for at least 80% of the time; consequently, the battery could possibly provide other services as well if the peak occurrence is sufficiently predictable. From an economic perspective, peak shaving looks interesting for capacity invoiced end users in Belgium, under the current battery capex and electricity prices (without Time-of-Use (ToU) dependency).

This research is aligned with the engineering challenge of scaling-up individual battery cells into a complete energy storage system (ESS). Manufacturing tolerances, coupled with thermal gradients and the differential electrical loading of adjacent cells, can result in significant variations in the rate of cell degradation, energy distribution and ESS performance. The uncertain transition from cell to system often manifests itself in over-engineered, non-optimal ESS designs within both the transport and energy sectors. To alleviate these issues, the authors propose a novel model-based framework for cell-in-the-loop simulation (CILS) in which a physical cell may be integrated within a complete model of an ESS and exercised against realistic electrical and thermal loads in real-time. This paper focuses on the electrical integration of both real and simulated cells within the CILS test environment. Validation of the CILS approach using real-world electric vehicle data is presented for an 18650 cell. The cell is integrated within a real-time simulation model of a series string of similar cells in a 4sp1 configuration. Results are presented that highlight the impact of cell variability (i.e., capacity and impedance) on the energy available from the multi-cell system and the useable capacity of the physical cell.

Understanding battery characteristic behaviors is indispensable in designing and managing large-scale battery-based energy storage systems in high-power applications. This paper presents a practical-based characterization method to model the ohmic series resistance of lithium-ion batteries under life-cycle consideration. Aging cells were prepared in a controlled environment, and the testing information was automatically characterized using a developed computer-based battery test system. An experimental methodology based on the cycling of pulse tests is applied for modeling the ohmic series resistance. Several aspects of the testing parameters during the cycling operations, such as the characteristic changes of the ohmic series resistance, amplitudes of the periodic test current, cell capacity, state of charge, and the rate of change of the resistance increment, are also investigated and analyzed so as to fulfill the resistance model. The accuracy of the proposed model is verified by comparing the testing information, showing a satisfactory result.

Cooling the surface of large format batteries with solid conductive plates, or fins, has an inherent advantage of reducing the number of liquid seals relative to some mini-channel cold plate designs, as liquid is not passed through the numerous individual plates directly. This may reduce the overall pack leakage risk which is of utmost importance due to safety concerns associated with the possibility of a cell short circuit and thermal runaway event. However, fin cooling comes at a cost of an increased thermal resistance which can lead to higher cell temperatures and a poorer temperature uniformity under aggressive heat generation conditions. In this paper, a novel graphite-based fin material with an in-plane thermal conductivity 5 times greater than aluminium with the same weight is presented for advanced battery cooling. The thermal performance of the fin is benchmarked against conventional copper and aluminium fins in an experimental programme cycling real 53 Ah pouch cells. The results from the extensive experimental testing indicate that the new fin can reduce both the peak measured temperature and surface temperature gradient by up to 8 °C and 5 °C respectively, when compared to aluminium fins under an aggressive electric vehicle duty-cycle.

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.

In this study, we develop a method for calculating electric vehicle lithium-ion battery pack performance and cost. To begin, we construct a model allowing for calculation of cell performance and material cost using a bottom-up approach starting with real-world material costs. It thus provides a supplement to existing models, which often begin with fixed cathode active material (CAM) prices that do not reflect raw metal price fluctuations. We collect and display data from the London Metal Exchange to show that such metal prices, in this case specifically cobalt and nickel, do indeed fluctuate and cannot be assumed to remain static or decrease consistently. We input this data into our model, which allows for a visualization of the effects of these metal price fluctuations on the prices of the CAMs. CAMs analyzed include various lithium transition metal oxide-type layered oxide (NMC and NCA) technologies, as well as cubic spinel oxide (LMO), high voltage spinel oxide (LNMO), and lithium metal phosphate (LFP). The calculated CAM costs are combined with additional cell component costs in order to calculate full cell costs, which are in turn scaled up to full battery pack costs. Economies of scale are accounted for separately for each cost fraction.

On 16 January 2013, all Boeing 787 Dreamliners were indefinitely grounded due to lithium-ion battery failures that had occurred in two planes. Subsequent investigations into the battery failures released through the National Transportation Safety Board (NTSB) factual report, the March 15th Boeing press conference in Japan, and the NTSB hearings in Washington D.C., never identified the root causes of the failures—a major concern for ensuring safety and meeting reliability expectations. This paper discusses the challenges to lithium-ion battery qualification, reliability assessment, and safety in light of the Boeing 787 battery failures. New assessment methods and control techniques that can improve battery reliability and safety in avionic systems are then presented.

Temperature control of the lithium-ion pouch cells is crucial for smooth operation, longevity and enhanced safety in the battery-operated electric vehicles. Investigating the thermal behavior of lithium-ion pouch cells and optimizing the cooling performance are required to accomplish better performance, long life, and enhanced safety. In the present study, the cooling performance characteristics of 20 Ah lithium-ion pouch cell with cold plates along both surfaces are investigated by varying the inlet coolant mass flow rates and the inlet coolant temperatures. The inlet coolant mass flow rate is varied from 0.000833 kg/s to 0.003333 kg/s, and the inlet coolant temperature is varied from 5 °C to 35 °C. In addition, the effects of the cold plate geometry parameter on cooling performance of 20 Ah lithium-ion pouch cell are studied by varying the number of the channels from 4 to 10. The maximum temperature and difference between the maximum and the minimum temperatures are considered as important criteria for cooling performance evaluation of the 20 Ah lithium-ion pouch cell with cold plates along both surfaces. The cooling energy efficiency parameter (β) and the pressure drop for 20 Ah lithium-ion pouch cell with cold plates along both surfaces are also reported. The study shows that enhanced cooling energy efficiency is accompanied with low inlet coolant temperature, low inlet coolant mass flow rate, and a high number of the cooling channels. As a result, the temperature distribution, the pressure drop, and the cooling energy efficiency parameter (β) of the 20 Ah lithium-ion pouch cell with cold plates along both surfaces are provided, and could be applied for optimizing the cooling performances of the thermal management system for lithium-ion batteries in electric vehicles.

Nexus 6P smartphones have been beset by battery drain issues, which have been causing premature shutdown of the phone even when the charge indicator displays a significant remaining runtime. To investigate the premature battery drain issue, two Nexus 6P smartphones (one new and one used) were disassembled and their batteries were evaluated using computerized tomography (CT) scan analysis, electrical performance (capacity, resistance, and impedance) tests, and cycle life capacity fade tests. The “used” smartphone battery delivered only 20% of the rated capacity when tested in a first capacity cycle and then 15% of the rated capacity in a second cycle. The new smartphone battery exceeded the rated capacity when first taken out of the box, but exhibited an accelerated capacity fade under C/2 rate cycling and decreased to 10% of its initial capacity in just 50 cycles. The CT scan results revealed the presence of contaminant materials inside the used battery, raising questions about the quality of the manufacturing process.

Lithium-ion battery (LIB) power systems have been commonly used for energy storage in electric vehicles. However, it is quite challenging to implement a robust real-time fault diagnosis and protection scheme to ensure battery safety and performance. This paper presents a resilient framework for real-time fault diagnosis and protection in a battery-power system. Based on the proposed system structure, the self-initialization scheme for state-of-charge (SOC) estimation and the fault-diagnosis scheme were tested and implemented in an actual 12-cell series battery-pack prototype. The experimental results validated that the proposed system can estimate the SOC, diagnose the fault and provide necessary protection and self-recovery actions under the load profile for an electric vehicle.