Knowing the aging trajectories of lithium-ion batteries (LIBs) in electric vehicles – referred to as state-of-life (SOL) prediction – is essential for timely replacement and effective post-first-life management. In real-world applications, however, operating conditions vary significantly, and this uncertainty must be considered to ensure the generalizability of SOL prediction methods. Existing literature provides limited analysis of how such varying conditions challenge SOL prediction, including the availability of laboratory-like features, the robustness of relationships between features and SOL indicators, and the resulting prediction errors. Similarly, the claimed importance of SOL results for post-first-life decision-making has not been demonstrated in a way that provides a foundation for further progress. To address these gaps, this study proposes a systematic procedure for conducting an in-depth analysis of the impact of uncertainties. A range of input features (IFs) is selected from experimental data; these features capture operational uncertainties and maintain explainable relationships with SOL. These IFs are used to train and validate a deep neural network model for SOL prediction. The analysis confirms that uncertainties influence both the availability and sensitivity of IFs, and that accounting for them is critical to achieving generalizable SOL predictions. The highest mean absolute error observed for SOL prediction was approximately 3%. Finally, the study demonstrates how SOL results can be applied to battery second-life (SL) decision-making and recycling management.

Lithium-ion batteries (LIBs) exhibit sudden non-linear degradation (known as the cell knee point) in operating use, but a quick, simple, and industrially applicable method of predicting knee point failure remains elusive. Addressing this gap, we show for the first time that the Warburg coefficient (readily obtainable from EIS measurement) can predict electrolyte-based knee point failure, well before extreme capacity degradation, in retired electric vehicle pouch cells. The technique is found to be effective across a wide range of battery states of charge (SOC), and the information can be extracted from the pouch cells in only 10 seconds. In principle this enables early detection of electrolyte-based knee point failure within commercial electric vehicle cells if applied ex situ through offline diagnosis (energy storage system) within second life battery application systems, thus allowing greater predictability with regard to the remaining lifetime of the battery.

Investment in DC charging infrastructure is constrained by limited data on charge point utilisation and unclear performance under diverse conditions. This paper proposes an Operational Performance (OP) framework to evaluate DC charger efficiency beyond conventional metrics. The framework incorporates an operational function that models nonlinear factors such as grid availability, ambient temperature, and EV battery charging profiles—that affect charger performance. An Overall Equipment Effectiveness (OEE)-based metric is developed within this framework to provide a comprehensive assessment. This metric enables precise optimisation of charger deployment and operation, thereby improving DC charger efficiency.

The increasing demand for lithium-ion batteries (LiBs) in electric vehicles, renewable energy storage and consumer electronics necessitates a transition towards high-performance, cost-effective, and sustainable manufacturing. Traditional manufacturing methods rely heavily on empirical trial-and-error approaches, leading to inefficiencies such as process variability, material waste and increased production costs. Recent advancements in digitalization, particularly artificial intelligence (AI) driven digital twins, offer transformative solutions to these challenges. This review presents a systematic framework for integrating AI and digital twin technologies into battery manufacturing, emphasizing their role in predictive maintenance, quality control, and process optimization. Unlike existing reviews, which primarily focus on theoretical modelling, this work examines real-world industrial applications, discusses challenges in large-scale AI adoption, and provides a practical roadmap for implementation. Key contributions include an analysis of digital models, shadows and twins in optimizing battery manufacturing processes and defect detection. Additionally, we highlight the contributions of Raw Material Suppliers, Battery Manufacturers, Technology and Innovation Partners, Policymakers and Regulators, along with actionable plans in establishing a fully digitalized battery production ecosystem. By bridging conventional manufacturing with intelligent digital frameworks, this review outlines a path toward scalable, high-quality, and sustainable battery production.

The market dynamics, and their impact on a future circular economy for lithium-ion batteries (LIB), are presented in this roadmap, with safety as an integral consideration throughout the life cycle. At the point of end-of-life (EOL), there is a range of potential options—remanufacturing, reuse and recycling. Diagnostics play a significant role in evaluating the state-of-health and condition of batteries, and improvements to diagnostic techniques are evaluated. At present, manual disassembly dominates EOL disposal, however, given the volumes of future batteries that are to be anticipated, automated approaches to the dismantling of EOL battery packs will be key. The first stage in recycling after the removal of the cells is the initial cell-breaking or opening step. Approaches to this are reviewed, contrasting shredding and cell disassembly as two alternative approaches. Design for recycling is one approach that could assist in easier disassembly of cells, and new approaches to cell design that could enable the circular economy of LIBs are reviewed. After disassembly, subsequent separation of the black mass is performed before further concentration of components. There are a plethora of alternative approaches for recovering materials; this roadmap sets out the future directions for a range of approaches including pyrometallurgy, hydrometallurgy, short-loop, direct, and the biological recovery of LIB materials. Furthermore, anode, lithium, electrolyte, binder and plastics recovery are considered in order to maximise the proportion of materials recovered, minimise waste and point the way towards zero-waste recycling. The life-cycle implications of a circular economy are discussed considering the overall system of LIB recycling, and also directly investigating the different recycling methods. The legal and regulatory perspectives are also considered. Finally, with a view to the future, approaches for next-generation battery chemistries and recycling are evaluated, identifying gaps for research. This review takes the form of a series of short reviews, with each section written independently by a diverse international authorship of experts on the topic. Collectively, these reviews form a comprehensive picture of the current state of the art in LIB recycling, and how these technologies are expected to develop in the future.

Measuring flame lengths and areas from turbulent flame flares developing from lithium-ion battery failures is complex due to the varying directions of the flares, the thin flame zone, the spatially and temporally rapid changes of the thermal runaway event, as well as the hazardous nature of the event. This paper reports a novel methodology for measuring heat release rate from flame flares resulting from thermal runaway of electric vehicle lithium-ion modules comprising eight 56.3Ah lithium nickel manganese cobalt (NMC) pouch cells using digital cameras and a newly developed numerical code to process the distortion of the flame size based on distance, direction, and shape. The model is tested with a set of experiments using lithium-ion battery packs and validated with a reference set of measurements using calibration boxes, a method commonly used in the reconstruction of flame areas. The experiments showed that the effect of calibration is large, and thus digital imaging without the appropriate calibration can give very large errors in measurement of flames. The combined imaging and processing method proposed in this work allows the determination of heat release rates from lithium-ion battery packs, one of the most challenging variables to quantify during the failure of a battery pack outside the laboratory. In the example experiment that this method was applied to, almost double the heat released was accounted for, meaning 50% of the total heat released would not have been accounted for without this image processing method.

As the electrification of the transport sector progresses, an abundance of lithium-ion batteries inside electric vehicles (EVs) will reach their end-of-life (EoL). The cells inside battery packs will age differently depending on multiple factors during their use. Currently, there is limited publicly available research on the degradation of the individual cells recovered from real-world EV usage. Once they have been recovered from the vehicle, large-format pouch cells are challenging to characterise, measure their internal structure and determine state-of-health (SoH). Here, large-format (261 x 216 x 7.91 mm) Nissan Leaf cells are harvested from an EV and four complementary non-destructive techniques are used to distinguish the ageing of cells arranged in varying orientations and locations within the pack. The measurement suite includes infrared thermography, ultrasonic mapping, X-ray computed tomography, and synchrotron X-ray diffraction, and represents a unique combination of characterisation techniques. We found that each of the non-destructive diagnostic techniques corroborated each other yet provide different complementary insights. The influence of orientation and location of the cells is significant, with the rotated/vertically aligned cells differing significantly from the flat/horizontally aligned cells in mode and degree of ageing. These insights provide new information on cell degradation that can help to influence pack design and illustrates how rapid and relatively inexpensive technology can provide sufficient information for practical assessment compared to costly synchrotron studies. Such an approach can inform decision support at EoL and more efficient battery production reducing the wastage of raw materials.

Cities are central to increasing the uptake of electric vehicles. A range of situational and contextual factors will influence this process, and cities need to use a variety of mechanisms — including policies and incentives — to drive the necessary change.

Batteries must be discharged prior to recycling, which is a key safety step in the materials reclamation process. The primary objective of this study is to do this in the shortest period of time possible while ensuring that the batteries are not over discharged (which affects the material recoverability). Mismatches in individual cell capacities of Li-ion batteries lead to the requirement for balancing schemes for serially connected cells/modules to avoid over discharge/charge and expanding the available capacity. This paper proposes a new energy management strategy that actively splits current demand from a load provided by a closed loop controller to each battery with respect to its current state, utilising a modular structure with a half bridge topology. Simulation results are presented derived from MATLAB/SIMULINK, showcasing successful SOC synchronisation of equal and unequal capacity sets. A cell bypass is also demonstrated with an introduced fault.

As the number of EVs hitting the roads increased, dealing with their waste such as retired LIBs become an increasingly important issue to guarantee sustainability and reduce the cost of the recycling process. This imposes establishing a practical and cost-effective gateway testing framework to sort the retired batteries based on their remaining energy capacity, and to assign them for repurposing/reusing or for recycling to extract the raw materials. Therefore, the purpose of this paper is to introduce a practical sorting method that entails the use of incremental capacity, equivalent circuit model, and manipulated coulomb counting to evaluate the full capacity of retired battery modules based on partial discharge profile. The feasibility of the proposed method is demonstrated on both truncated full discharge profile and pulse discharge profile from partially charged battery. For the investigation, 48 lithium-ion modules from retired 24 kWh Nissan Leaf battery pack are used. The experimental results show that the proposed method is capable to estimate the full capacity with a maximum error of 5%. Furthermore, a considerable reduction in the test time is achieved, with only the terminal voltage and discharge current are used, which is of great practical significance to the battery recycling industry where the cost and time are dominant.

Abstract The pre-ignition stage following nail penetration of 1.67 kWh NMC(532) pouch cell modules at State-of-Charge ≤ 40% is associated with temperatures too low for combustion or pyrolysis (< 40°C), yet large volumes of a vapour cloud are produced. The vapour cloud is associated directly with a blue emission and it is suggested that this emission is due to the nitrogen in a plasma arc. Plasmas are increasingly associated with highly novel chemical processes.

Li-ion batteries (LiBs) in electric vehicles (EVs) finish their life with a significant amount of capacity left in them (about 80% of the nominal capacity), which provides a promising avenue for reusing the spent EV-batteries in less demanding second-life applications, such as grid-scale energy storage for peak shaving, EV charging, storage for intermittent energy sources (solar or wind power), backup storage for industries and property owners, and less demanding vehicle propulsion (ferries or forklifts) [1, 2]. However, reusing spent EV batteries in second-life applications is not as straightforward as taking a battery pack from an EV then installing it directly into a second-life application. One must consider the state-of-health (SoH) of the battery packs and hence the modules and cells to avoid any mismatch in terms of capacity, state-of-charge/depth-of-discharge (SoC/DoD). Even within the batteries suitable for reuse, cells must be sorted by similar remaining capacity and identical degradation state, or else the second-life system performance would suffer. The SoH needs careful assessment and ageing conditions evaluated to send heavily degraded batteries to recycling facilities. Whilst assessing the SoH is straightforward [3], identifying the ageing condition is complex, as ageing and degradation of LiBs over time are caused by various factors, including charging/discharging rate (C-rate), operating temperature, lifetime, SoC, and cycling [2]. Moreover, pack design, configuration, cooling methods as well as cell/module’s orientation in a pack can influence the battery degradation. In the present study, the effect of cell orientation on battery ageing and degradation has been investigated that can have an impact on the life of a battery in second-life applications. Eight large-size pouch batteries from two differently orientated modules from a dismantled first-generation Nissan Leaf retired battery pack have been analysed utilising infrared (IR) thermography and electrochemical impedance spectroscopy (EIS) techniques along with a brand-new second-generation Nissan Leaf battery which has almost the same geometry as batteries from the retired pack. Temperature derivative maps over the battery surface during discharging have been analysed, which show a direct correlation with the battery’s heat generation rates. Obtained results show that the thermal behaviour of brand-new batteries in orientations mimicking aged battery's orientation in the pack during EV life are very similar showing that the temperature derivative map’s hot spot is more towards the edge opposite to gravity vector (Figure 1 left). Also, EIS results (RCT+RSEI, charge transfer and solid electrolyte interphase layer resistances) show a wider range over SoCs for rotated-aged than flat-aged cells (Figure 1 right). It is worth noting that cells aged in flat orientation retained higher capacity compared to the cells aged in rotated orientation. These results show that different LiB orientations in EV batteries cause ageing non-uniformities over the battery surface, which would impact their second-life applications [4]. Non-uniform ageing is found to be more pronounced for the rotated module compared with the flat orientation inside the battery pack (Figure 1). Based on the present results, it is clear that avoiding different orientations in the battery pack can be a sustainable design for future EV battery back if reusing of spent EV batteries is envisaged. This work was part of the ReLiB project (https://relib.org.uk) and was supported by the Faraday Institution (https://www.faraday.ac.uk; grant numbers FIRG005 and FIRG027). References [1] ReLiB: Reuse and Recycling of Lithium-ion Batteries, accessed 12 December 2021, . [2] P.S. Attidekou, Z. Milojevic, M. Muhammad, M. Ahmeid, S. Lambert, P.K. Das, “Methodologies for large-size pouch lithium-ion batteries end-of-life gateway detection in the second-life application,” Journal of the Electrochemical Society, vol. 167, pp. 160534, 2020, DOI: 10.1149/1945-7111/abd1f1. [3] M. Muhammad, M. Ahmeid, P. Attidekou, Z. Milojevic, S. Lambert, P. Das, “Assessment of spent EV batteries for second-life application”, 2019 IEEE 4th International Future Energy Electronics Conference (IFEEC), IEEE, pp. 1-5, 2019, DOI: 10.1109/IFEEC47410.2019.9015015. [4] Z. Milojevic, P.S. Attidekou, M. Muhammad, M. Ahmeid, S. Lambert, P.K. Das, “Influence of orientation on ageing of large-size pouch lithium-ion batteries during electric vehicle life,” Journal of Power Sources, vol. 506, pp. 230242, 2021, DOI: 10.1016/j.jpowsour.2021.230242 Figure 1

There is growing interest in recycling and re-use of electric vehicle batteries owing to their growing market share and use of high-value materials such as cobalt and nickel. To inform the subsequent applications at battery end of life, it is necessary to quantify their state of health. This study proposes an estimation scheme for the state of health of high-power lithium-ion batteries based on extraction of parameters from impedance data of 13 Nissan Leaf 2011 battery modules modelled by a modified Randles equivalent circuit model. Using the extracted parameters as predictors for the state of health, a baseline single hidden layer neural network was evaluated by root mean square and peak state of health prediction errors and refined using a Gaussian process optimisation procedure. The optimised neural network predicted state of health with a root mean square error of (1.729 ± 0.147)%, which is shown to be competitive with some of the most performant existing neural network–based state of health estimation schemes, and is expected to outperform the baseline model with ∼50 training samples. The use of equivalent circuit model parameters enables more in-depth analysis of the battery degradation state than many similar neural network–based schemes while maintaining similar accuracy despite a reduced dataset, while there is demonstrated potential for measurement times to be reduced to as little as 30 s with frequency targeting of the impedance measurements.

To boost the circular economy of the electric vehicle battery industry, an accurate assessment of the state of health of retired batteries is essential to assign them an appropriate value in the post automotive market and material degradation before recycling. In practice, the advanced battery testing techniques are usually limited to laboratory benches at the battery cell level and hardly used in the industrial environment at the battery module or pack level. This necessitates developing battery recycling facilities that can handle the assessment and testing undertakings for many batteries with different form factors. Towards this goal, for the first time, this article proposes proof of concept to automate the process of collecting the impedance data from a retired 24kWh Nissan LEAF battery module. The procedure entails the development of robot end-of-arm tooling that was connected to a Potentiostat. In this study, the robot was guided towards a fixed battery module using visual servoing technique, and then impedance control system was applied to create compliance between the end-of-arm tooling and the battery terminals. Moreover, an alarm system was designed and mounted on the robot's wrist to check the connectivity between a Potentiostat and the battery terminals. Subsequently, the electrochemical impedance spectroscopy test was run over a wide range of frequencies at a 5% state of charge. The electrochemical impedance spectroscopy data obtained from the automated test is validated by means of the three criteria (linearity, causality and stability) and compared with manually collected measurements under the same conditions. Results suggested the proposed automated configuration can accurately accomplish the electrochemical impedance spectroscopy test at the battery module level with no human intervention, which ensures safety and allows this advanced testing technique to be adopted in grading retired battery modules.

Lithium-ion Batteries (LIB) are an essential facilitator of the decarbonisation of the transport and energy system, and their high energy densities represent a major technological achievement and resource for humankind. In this research, it has been argued that LIBs have penetrated everyday life faster than our understanding of the risks and challenges associated with them. The current safety standards in the car industry have benefited from over 130 years of evolution and refinement, and Electric Vehicle (EV) and LIB are comparably in their infancy. This paper considers some of the issues of safety over the life cycle of batteries, including: the End of Life disposal of batteries, their potential reuse in a second-life application (e.g. in Battery Energy Storage Systems), recycling and unscheduled End of Life (i.e. accidents). The failure mechanism and reports from a range of global case studies, scenarios and incidents are described to infer potential safety issues and highlight lessons that can be learned. Therefore, the safety risks of LIBs were categorised, and the regularity requirements to create and inform a wider debate on the general safety of LIBs were discussed. From the analysis, a range of gaps in current approaches have been identified and the risk management systems was discussed. Ultimately, it is concluded that robust educational and legal processes are needed to understand and manage the risks for first responders and the public at large to ensure a safe and beneficial transition to low carbon transportation and energy system.

In the electric vehicle (EV) battery packs, large-size lithium-ion pouch batteries (LiBs) are mostly used and to miniaturise the battery pack's volume, some manufacturers put the LiBs in different orientations. It is well established that temperature gradients over large-size LiBs surface cause ageing non-uniformities, but the influence of the LiBs orientation on the ageing has to date received little attention. Here, we present an analysis of orientation influence on the large-size pouch LiB's ageing on eight batteries from two differently orientated modules from the dismantled first-generation Nissan Leaf retired battery pack. The influence of orientation is also analysed for brand-new second-generation Nissan Leaf battery which has almost the same geometry as batteries from the retired pack. By utilising infrared (IR) thermography and electrochemical impedance spectroscopy (EIS) techniques, the influence of orientation on the LiBs ageing non-uniformity is detected. Whilst temperature maps analysis shows different LiBs' thermal behaviour depends on their orientation, EIS measurements show that ageing non-uniformity can be identified by analysing the solid-electrolyte-interphase and charge-transfer resistances. Presented results show that different LiBs orientation in EV battery packs should be avoided because it can cause ageing non-uniformities over the battery surface and their second-life applications should be applied with caution.

Haimeng Wu Department of Mathematics, Physics & Electrical Engineering Ellison Building, Northumbria University, Newcastle upon Tyne, NE1 8ST, United Kingdom. Email: Haimeng.wu@northumbria.ac.uk Abstract Electric vehicles (EVs) require an onboard battery charger unit and a battery management system (BMS) unit that balances the voltage levels for each battery cell. So far, both units are two completely autarkic power electronics systems. The circuit presented here operates as a battery charger when the EV is connected to the grid and as a voltage balancer when the EV is driving. Thus, the proposed circuit utilises two functions in one and therefore eliminates the need of having two autarkic units reducing complexity and reduction in component count. The proposed circuit operates as a flyback converter and achieves power factor correction during battery charging. The constant‐current constant‐ voltage (CC–CV) charging method is employed to charge the batteries. However, to limit the number of sensors that will be employed as a result of varying cells during charging, the battery current is estimated using a single current transducer and embedding a converter model in the controller. The operation of the circuit is presented in detail and is supported by simulation results. A laboratory prototype is built to verify the effectiveness of the proposed topology. Experiment results show that the proposed method provides an integrated solution of on‐board charging and voltage equalisation.

This paper reports thermal (burner) and mechanical (blunt trauma and nail penetration) abuse experiments on electric vehicle lithium ion modules comprising eight 56.3 Ah lithium nickel manganese cobalt (NMC) pouch cells. The aim of project part of which is described in this paper was to study the problem of thermal runaway in lithium ion batteries under different abuse conditions and at different SOC and to bridge the current gap in the literature between cell level studies and research at pack and system level. These experiments were part of an ongoing research programme leading up to studies at pack and system level. The responses of the cells to the various forms of abuse were monitored with optical and thermal cameras, thermocouples and by measuring cell voltage. Draeger gas sensors were also employed where possible. The nail penetration experiments were carried out at (nominally) 96.5%, 75% and 50% SOC, and at 96.5% SOC as a function of penetration location: the experiments strongly suggest that low SOC is as hazardous as high SOC, in contrast to a general perception in the literature, as the likely hazards are simply different and include the possibility of violent vapour cloud explosion. Thus, in all experiments, the first obvious indication of thermal runaway was the ejection of white vapour: if this ignited, the obvious hazard was that of fire. If, however, the vapour did not ignite, it posed an entirely different hazard in terms of high toxicity and the potential for a violent vapour cloud explosion: this is the first mention of such a phenomenon linked to lithium ion batteries in the academic literature. The experiments showed that cell voltage cannot be employed as a reliable warning of thermal runaway. Finally, the data obtained support a wholly novel theory, yet to be adopted across the community, in which thermal runaway can involve the direct solid-state electrochemical reaction between anode and cathode at temperatures >= 250 degrees C following venting of the electrolyte.

Rapid growth in the market for electric vehicles is imperative, to meet global targets for reducing greenhouse gas emissions, to improve air quality in urban centres and to meet the needs of consumers, with whom electric vehicles are increasingly popular. However, growing numbers of electric vehicles present a serious waste-management challenge for recyclers at end-of-life. Nevertheless, spent batteries may also present an opportunity as manufacturers require access to strategic elements and critical materials for key components in electric-vehicle manufacture: recycled lithium-ion batteries from electric vehicles could provide a valuable secondary source of materials. Here we outline and evaluate the current range of approaches to electric-vehicle lithium-ion battery recycling and re-use, and highlight areas for future progress.