Second Life Applications Research Articles

Second Life Management From Battery Storage System of Electric Waterborne Transport Applications: Perspectives and Solutions

In electric naval applications, battery storage management plays a key role. The second-life battery use is a fundamental part of the sustainable development of these waterborne transport systems. The article deals with the perspective and solutions of the second-life storage battery systems from the electric ship traction area. This paper presents an overview of the topic of second-life use, application, and future direction with a special focus on battery systems from electric propulsion ships. In particular, a modular converter-battery approach in the storage system structure arrangement is considered. The modular battery storage approach in electric naval propulsion applications is the target of SEABAT project. This proposed solution allows both controls of the electrical quantities of the storage output and monitoring of the battery’s electrical parameters to always have its health status available. The advantages of the modular multilevel battery-converter structure developed within the SEABAT project towards second-life use are presented and evaluated, leading to an estimated cost saving of 35% during the whole life time of the batteries. Besides, the integration of multiple battery technology with different degradation state is enabled. Moreover, the power converter features for second-life applications are explored and discussed. Furthermore, the manufacturing and disassembly processes aspects of the SEABAT converter-battery system (CBS) are also investigated to validate the effectiveness of the proposed modular storage solution. The SEABAT project targets a 246 kWh demonstrator with a 1000 V output.

Accelerated state of health estimation of second life lithium-ion batteries via electrochemical impedance spectroscopy tests and machine learning techniques

Estimating the state of health (SoH) of lithium-ion (Li-ion) batteries is a challenging task due to cross coupling and dependency between ageing mechanisms. An accurate estimation is particularly essential for second-life batteries to facilitate their successful implementation in the new application. By adopting the electrochemical impedance spectroscopy (EIS) test and a machine learning (ML) approach, the accelerated SoH estimation problem is studied here. For this purpose, 325 experiments for 30 Li-ion cells were conducted at various SoH, temperature, and state of charge. First an optimised Gaussian process regression model is developed and validated for SoH estimation. Then the sensitivity of the model is evaluated relative to measurement noise. Finally, the model's robustness is quantified through a case study involving cells that have been characterised with different physical test equipment. The results demonstrate that the model can predict the SoH of Li-ion cells with an error about 1.1 % and is reasonably robust to the various testing conditions of the battery. The methodology for handling the EIS data within a machine learning framework, the sensitivity analysis and the robustness quantification techniques are the main novelties of this study in the context of grading Li-ion batteries for second-life applications.

Pack-level performance of electric vehicle batteries in second-life electricity grid energy services

Repurposed electric vehicle (EV) batteries can provide an affordable and sustainable alternative to conventional utility-scale battery energy storage systems. While EV battery packs are often disassembled into modules or cells and repackaged for second life, the required time and labour costs can be mitigated by directly repurposing full EV battery packs when their health allows. However, the diversity among EV battery pack designs introduces uncertainty regarding their relative performance in second-life applications. This study presents experimental data demonstrating the second-life performance of EV batteries from five different EV manufacturers, featuring four unique positive electrodes, three cell formats, and three thermal management designs. All five EV batteries are tested at the pack level in their original housings, providing thermal conditions distinct from module or cell testing. The batteries are tested under 4 h, 2 h, and 1 h deep-discharge constant-power duty cycles to emulate electricity grid energy services such as energy arbitrage or peak shaving. Novel methods are employed to measure, assess, and compare battery performance in this test regime. The results show significant performance differences among the five EV battery packs, particularly between older (2012–2015) and newer (2018–2019) designs due to evolutions in energy density and thermal management. The test results are analyzed and ranked, showing that among the five tested batteries, the 2019 Tesla Model 3 battery (tested with active-liquid cooling) will provide the best overall performance in most second-life energy storage applications, while the 2015 BMW i3 battery (tested with passive-air cooling) will provide the best profit margins in applications where energy losses must be minimized. The novel experimental dataset is used to derive a number of generalized conclusions and recommendations which can be used by researchers and industrial developers to inform the modelling and design of second-life energy storage systems.

Verification of the Modified Degradation Mode Identification Technique by Employing Electrochemical Impedance Spectroscopy and Differential Voltage Analysis

For retired automotive lithium-ion batteries, state of health (SoH) is currently utilised to grade them for a second-life application. However, researchers previously challenged this and expressed that, in addition to SoH, the actual degradation mechanism, also known as degradation mode (DM), should be considered for grading, for efficient second-life operation. To date, there is little evidence to support this. A validated DM detection technique for cell/module grading does not exist. A modified DM detection technique by tracking and indexing the incremental capacity (IC) curves was previously proposed by the authors; nevertheless, it was difficult to validate. Researchers previously proposed DM identification using Electrochemical Impedance Spectroscopy (EIS) and Differential Voltage (DV) analysis. With a direct comparison of the techniques made exploiting IC, DV, and EIS, a correlation can be made, which is presented in this article. The correlation suggests that cells identified as having the same (or different) DM by the proposed technique also identified as having the same (or different) DM growth by EIS technique proposed by other researchers. Likewise, DV analysis suggests that the DV peak’s standard deviation of similar DM cells is smaller than that of the different DM cells.

Smart Battery Technology for Lifetime Improvement

Applications of lithium-ion batteries are widespread, ranging from electric vehicles to energy storage systems. In spite of nearly meeting the target in terms of energy density and cost, enhanced safety, lifetime, and second-life applications, there remain challenges. As a result of the difference between the electric characteristics of the cells, the degradation process is accelerated for battery packs containing many cells. The development of new generation battery solutions for transportation and grid storage with improved performance is the goal of this paper, which introduces the novel concept of Smart Battery that brings together batteries with advanced power electronics and artificial intelligence (AI). The key feature is a bypass device attached to each cell that can insert relaxation time to individual cell operation with minimal effect on the load. An advanced AI-based performance optimizer is trained to recognize early signs of accelerated degradation modes and to decide upon the optimal insertion of relaxation time. The resulting pulsed current operation has been proven to extend lifetime by up to 80% in laboratory aging conditions. The Smart Battery unique architecture uses a digital twin to accelerate the training of performance optimizers and predict failures. The Smart Battery technology is a new technology currently at the proof-of-concept stage.

Electric Vehicle Battery Health Expected at End of Life in the Upcoming Years Based on UK Data

Second-life businesses from Electric Vehicle (EV) batteries are gaining attention considering that these batteries are deemed as inappropriate for transport purposes once they reach 80 or 70% of State of Health (SoH). However, the limited number of retired batteries and the trend in battery capacity increase hinder a realistic evaluation of second-life applications. To analyze battery reuse, a closer look at the End of Life (EoL) conditions of these batteries must be taken. This study presents a battery ageing model to estimate the SoH of EV batteries according to their age and mileage. The model is applied to the current retirement characteristics of combustion vehicles to statistically determine the expected SoH at the vehicle EoL. Results indicate that most EVs will reach EoL for reasons other than under-performance. Once retired, most EV batteries will have a SoH higher than 75% within the next 20 years, opening an interesting market for second-life businesses. However, battery reuse is an option that, considering the growing EV market, will rapidly saturate the stationary energy storage demand. Before 2040, most EV batteries will follow streams towards the circular economy, although at some point, they will have to be sent directly to recycling after the vehicular use.

Design and On-Field Validation of an Embedded System for Monitoring Second-Life Electric Vehicle Lithium-Ion Batteries.

In the last few years, the growing demand for electric vehicles (EVs) in the transportation sector has contributed to the increased use of electric rechargeable batteries. At present, lithium-ion (Li-ion) batteries are the most commonly used in electric vehicles. Although once their storage capacity has dropped to below 80–70% it is no longer possible to use these batteries in EVs, it is feasible to use them in second-life applications as stationary energy storage systems. The purpose of this study is to present an embedded system that allows a Nissan® LEAF Li-ion battery to communicate with an Ingecon® Sun Storage 1Play inverter, for control and monitoring purposes. The prototype was developed using an Arduino® microcontroller and a graphical user interface (GUI) on LabVIEW®. The experimental tests have allowed us to determine the feasibility of using Li-ion battery packs (BPs) coming from the automotive sector with an inverter with no need for a prior disassembly and rebuilding process. Furthermore, this research presents a programming and hardware methodology for the development of the embedded systems focused on second-life electric vehicle Li-ion batteries. One second-life battery pack coming from a Nissan® Leaf and aged under real driving conditions was integrated into a residential microgrid serving as an energy storage system (ESS).

How will retired electric vehicle batteries perform in grid-based second-life applications? A comparative techno-economic evaluation of used batteries in different scenarios

The adoption of electric vehicles is increasing in a global trend toward decarbonization, yet the overall sustainability of these vehicles still poses many questions. The sourcing of many critical raw materials in battery production and their poorly-defined end-of-life management are among the underlined environmental challenges. The sustainability of battery placement in the transportation system in this sense needs to be supported by circular end-of-life strategies. While battery recycling for a secondary supply can be more favourable for producers, reuse disposition is regarded as being more environmentally attractive from a holistic lifecycle perspective. Cascading the life of batteries as such to reduce the environmental burdens is considered by both regulatory and industrial bodies. However, the uncertainties in cost breakdown and reliability of repurposed batteries reflected in naïve second-life market alignment and financial justification are barriers to current reuse policies and practices. For batteries with a variable lifetime subject to technical constraints in every application, the financial dynamics which underpin the choices of how and where to deploy them are challenging to investigate. While present studies make static assumptions about battery lifetime and operating costs, this work develops a dynamic investigation by incorporating battery degradation in hosts of different second-life applications into the financial analysis. This goal is approached by estimating the lifetime of the batteries in cascaded applications, and further evaluating their second-life contribution to energy and non-energy services in power systems. Findings indicate that settling on a lower purchase price for retired batteries and reducing the number of energy trading results in a justifiable return-on-investment. For batteries in early-failure vehicles such as 4-years-old, this arrangement is equally profitable compared to new ones when going below 26% of the original battery cell price, yet for older batteries such as 10-year-olds, the best performance is expected when contributing to grid services while keeping the investment value below 15%. • Evaluating the techno-economic viability of reusing EV batteries. • 80% State-of-health is expected for batteries in 12-year-old disposed of vehicles. • Battery life decreases to a quarter when cycling numerously compared to grid-services. • Grid services were found to be the best reuse candidate in the grid-based stationery. • Retired battery values are below 26% and 15% in four and ten-year-old ones.

Field Study and Multimethod Analysis of an EV Battery System Disassembly

In the coming decades, the number of end-of-life (EoL) traction battery systems will increase sharply. The disassembly of the system to the battery module is necessary to recycle the battery modules or to be able to use them for further second-life applications. These different recovery paths are important pathways to archive a circular battery supply chain. So far, little knowledge about the disassembling of EoL batteries exists. Based on a disassembly experiment of a plug-in hybrid battery system, we present results regarding the battery set-up, including their fasteners, the necessary disassembly steps, and the sequence. Upon the experimental data, we assess the disassembly duration of the battery system under uncertainty with a fuzzy logic approach. The results indicate that a disassembling time of about 22 min is expected for the battery system in the field study if one worker conducts the process. An estimation for disassembling costs per battery system is performed for a plant in Germany. Depending on the plant capacity, the disassembling to battery module level is associated with costs between EUR 80 and 100 per battery system.

(Digital Presentation) Reusing Li-Ion Batteries in Second-Life Applications: Impact of Cell Orientation in Electric Vehicle Pack

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).

Lithium-Ion Battery Second Life: Cell Performance Assessment for Stationary Energy Storage Applications

Repurposing electric vehicle (EV) lithium-ion batteries (LIBs) for second-life applications in stationary energy storage has developed considerable interest. With EV sales continuously rising, some critical materials used in LIBs risk supply shortages, while the volume of spent batteries could begin to overwhelm the facilities capable of disposing or recycling them. EV batteries typically reach end-of-life (EOL) when the capacity fades by 20-30%; although this is EOL exclusively for automotive applications, there still remains plenty of residual energy storage available that can be further utilized for less demanding applications. If viable, this could have significant impact in satisfying economic and environmental concerns as the trend toward greener and more sustainable energy solutions gains momentum. Extending the lifespan of retired EV LIBs can potentially supplement and soften the demand for total product, relaxing the strain on newly manufactured product and changing the standard of practice in the value chain. This lifecycle expansion could also be beneficial with respect to environmental impact by reducing raw material extraction and processing, landfill disposal or recycling, and improving resource sustainability.Existing public work on the reuse of EV batteries has mostly been exploratory, including feasibility studies, techno-economic analyses, and promotional demonstrations. Although necessary as part of the framework to move forward, these investigations lack the data to demonstrate the reliability of EV batteries for second-life applications. The work presented herein utilizes the International Electrotechnical Commission (IEC) standard 62620:2014 to evaluate the compliance, in terms of both capability and longevity, of EOL EV cells for energy storage applications.Battery modules were obtained from consumer-utilized 2012 and 2014 Nissan Leafs and characterization tests were applied to determine the present state of health. Cells were electrically isolated and the IEC Standard’s electrical tests were applied using a de-rated capacity as the new nominal capacity, based on the characterization results. One of the seven IEC Standard tests included a 500-cycle endurance test in which a C/2 charge and discharge rate was applied. Electrochemical impedance spectroscopy was measured periodically throughout the endurance test. Results on the compliance of these cells for stationary energy storage applications will be presented and discussed.

Remaining Useful Life Prediction of Lithium-Ion Battery via a Sequence Decomposition and Deep Learning Integrated Approach

The remaining useful life (RUL) prediction of Lithium-ion batteries (LIBs) is of great importance to the health management of electric vehicles and hybrid electric vehicles. However, fluctuation and nonlinearity occur during battery degradation, resulting in difficulties in both model adaptability and RUL prediction accuracy. To face the challenge, we propose a sequence decomposition and deep learning integrated prognostic approach for the RUL prediction of LIBs. Complementary ensemble empirical mode decomposition and principal component analysis are applied to separate the local fluctuations and the global degradation trend from the battery aging data. The long short-term memory neural network combined with fully connected layers is designed as a transfer learning model. The hyperparameter optimization and finetuning strategy of the model is developed based on offline training data. In addition, to further realize the reasonable and effective LIB second-life applications, the RUL corresponding to different failure thresholds is predicted. The performance of the proposed integrated approach in degradation modeling and RUL prediction is evaluated on three publicly available LIB datasets with different degradation characteristics, as well as compared with other prediction algorithms under the same conditions. The illustrative results demonstrate that the proposed approach can achieve accurate, adaptive, and robust prediction for both capacity trajectory and RUL.

Commercialization of Electric Vehicles in Hong Kong

Road vehicles are responsible for air pollution in Hong Kong, and electric vehicles (EVs) are a promising alternative to internal combustion engine vehicles as the city is transitioning to clean energy. In this work, EV adoption in Hong Kong is investigated and analyzed, including the global EV markets, present EV status in Hong Kong, local challenges facing EV development, suggestions for EV promotion in Hong Kong, emerging technologies, and decommissioning of batteries and EVs. The challenges of EVs include insufficient charging infrastructures, inadequate management of public charging facilities, difficulties in EV repair and maintenance, “dead mileage” during charging, unacceptable long charging times, and limited commercial EV models. Strategies such as providing incentives and bonuses for commercial EVs, offering high-power quick-charging facilities, actively developing commercial EVs, installing more charging infrastructures for private EVs, building connections among stakeholders, encouraging the participation of the private sector to promote fee-based services, and supporting the development of innovative technologies should be implemented to promote EVs in Hong Kong. Emerging technologies for EVs such as wireless charging, smart power distribution, vehicle-to-grid and vehicle-to-home systems, connected vehicles, and self-driving are discussed. Eco-friendly decommissioning of EV batteries can be realized by recycling and second-life applications. This paper serves as a reference and guide for the sustainable and smart evolution of the transportation sector in Hong Kong and other global large cities.

A review on second-life of Li-ion batteries: prospects, challenges, and issues

High energy density has made Li-ion battery become a reliable energy storage technology for transport-grid applications. Safely disposing batteries that below 80% of their nominal capacity is a matter of great concern to reduce overall carbon footprint. As battery typically accounts for 40% of the total cost of an electrical vehicle, it becomes necessary to combine reutilization and recycling for extending the lifetime of retired automotive batteries and make the overall battery supply chain profitable rather than dumping them directly. From an economic, technical, and environmental standpoint, this paper provides a comprehensive overview of the present state of second-life Li-ion batteries through exploring relevant literature. Specifically, the fundamental of Li-ion battery degradation and experimental approaches are first surveyed. After examining the obstacles and methods of reusing and recycling Li-ion battery, related applications, cost issues, and business models of second-life Li-ion batteries are discussed. By offering a systematical survey of current status of recycled Li-ion battery, this review could inform commercial technology selections and academic research agendas alike, thus boosting progress in Li-ion battery second-life applications.

Implementation of Battery Digital Twin: Approach, Functionalities and Benefits

The concept of Digital Twin (DT) is widely explored in literature for different application fields because it promises to reduce design time, enable design and operation optimization, improve after-sales services and reduce overall expenses. While the perceived benefits strongly encourage the use of DT, in the battery industry a consistent implementation approach and quantitative assessment of adapting a battery DT is missing. This paper is a part of an ongoing study that investigates the DT functionalities and quantifies the DT-attributes across the life cycles phases of a battery system. The critical question is whether battery DT is a practical and realistic solution to meeting the growing challenges of the battery industry, such as degradation evaluation, usage optimization, manufacturing inconsistencies or second-life application possibility. Within the scope of this paper, a consistent approach of DT implementation for battery cells is presented, and the main functions of the approach are tested on a Doyle-Fuller-Newman model. In essence, a battery DT can offer improved representation, performance estimation, and behavioral predictions based on real-world data along with the integration of battery life cycle attributes. Hence, this paper identifies the efforts for implementing a battery DT and provides the quantification attribute for future academic or industrial research.

An experimental study on the effectiveness of conventional state-of-health diagnosis schemes for second-use supercapacitors

Reuse of the retired/aged supercapacitors plays an important role in production sustainability and environmental concerns. Therefore, appropriate health characterization methods along with proper guidelines to identify the remaining useful capacitance of the retired supercapacitor cells are required. This paper focuses on conventional approach based capacitance diagnosis of retired supercapacitors, since there is a lack of technological development for the same. In particular, we evaluate the effectiveness of Maxwell six-step process-based time domain approach and electrochemical impedance spectroscopy based frequency domain approach in identifying the remaining capacitance of the retired supercapacitors. This work considers a retired cell of the commercially available Maxwell supercapacitors to demonstrate the approach. The results obtained from the conventional approaches via cyclic voltammetry test is validated. Subsequently, the effectiveness of the test methods are experimentally verified by considering a new specimen of the Maxwell 100 F supercapacitor. The obtained results confirm that both the approaches are showing promising results, however, for different operating voltage range. This clearly indicates the need for future research towards second-life application of retired supercapacitors. Finally, the importance of choosing proper capacitance characterization scheme for reliable use of retired supercapacitors considering a wireless sensor network based realistic second-life application is discussed.

Applying levelized cost of storage methodology to utility-scale second-life lithium-ion battery energy storage systems

The dramatic increase in electric vehicle (EV) sales has led to a rapid increase in deployed lithium-ion battery (LIB) capacity over the last decade. As EV batteries age and are retired from use in vehicles, they will require management. Second-life applications are often proposed as an environmentally and economically preferable management strategy to direct recycling or disposal. In particular, the repurposing of EV LIBs in stationary applications is expected to provide cost-effective solutions for utility-scale energy storage applications. However, the adoption of second-life battery energy storage systems (BESS) has been slow. One barrier to adoption is the lack of meaningful cost estimates of second-life BESS. Thus, this study develops a model for estimating the Levelized Cost of Storage (LCOS) for second-life BESS and develops a harmonized approach to compare second-life BESS and new BESS. This harmonized LCOS methodology predicts second-life BESS costs at 234–278 ($/MWh) for a 15-year project period, costlier than the harmonized results for a new BESS at 211 ($/MWh). Despite having a higher LCOS, the upfront costs for second-life BESS are 64.3–78.9% of new systems' costs. Results for second-life BESS are highly sensitive to assumptions of discount rate, depth of discharge, and module repurposing costs. If deemed environmentally or societally beneficial, policies should stimulate the use of second-life LIBs, such as providing incentives equal to or greater than those available for first life BESS. Further work can explore comparative economics at smaller scales and quantify non-economic benefits of second-life BESS.

Influence of orientation on ageing of large-size pouch lithium-ion batteries during electric vehicle life

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.

Risk management over the life cycle of lithium-ion batteries in electric vehicles

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.

Standardization of electric vehicle battery pack geometry form factors for passenger car segments in India

The Electric Vehicles (EV) adaptability is at the early stage in India due to many performances and commercial constraints among the potential customers. Battery Electric Vehicles (BEV) are slowly picking up in the Indian market and likely to grow due to stringent Government regulations and Green Mobility initiatives. The primary constraint in EV purchase is the driving range offered by Original Equipment Manufacturers (OEM) and EV range anxiety. This paper discusses the current battery pack integration among Indian Original Equipment Manufacturers (OEMs), design challenges, and the need for Standardised Battery Pack envelope (SBP). This study analyses the India OEMs vehicle data and, using a statistical and engineering assessment model, recommends the critical standard dimensions, type, size for the Standardised Battery Pack (SBP). This is possible by means of Electric Vehicle (EV) skateboard platform architecture, and platform sharing proliferate among EV manufacturers and start-ups. The model verifies the results by analytical and Simulation techniques. The results show the proposed model with SBP gives higher flexibility, improved driving range ,convenient battery swapping operation, improved operation time, and helps in second-life applications. This study's limitation is that due to the rapid advancement in battery technology, a specific battery chemistry is under consideration throughout the study.