The increasing demand for Lithium-ion batteries for Electric Vehicle calls for the adoption of sustainable practices and a switch towards a circular economy-based system to ensure that the electrification of transportation does not come at a high environmental cost. While driving patterns have not changed much over the years, the current Electric Vehicle market is evolving towards models with higher battery capacities. In addition, these batteries are considered to reach the End of Life at 70-80% State of Health, regardless of their capacity and application requirements. These issues may cause an underuse of the batteries and, therefore, hinder the sustainability of the Electric Vehicle. The goal of this study is to review and compare the circular processes available around Electric Vehicle batteries. The review highlights the importance of prioritizing the first-life of the battery onboard, starting with reducing the nominal capacity of the models. In cases where the battery is in risk of reaching the End of Life with additional value, Vehicle to Grid is encouraged over the deployment of second-life applications, which are being strongly promoted through institutional fundings in Europe. As a result of the identified research gaps, the methodological framework for the estimation of a functional End of Life is proposed, which constitutes a valuable tool for sustainable decision-making and allows to identify a more accurate End of Life, rather than considering the fixed threshold assumed in the literature.

Using batteries after their first life in an Electric Vehicle (EV) represents an opportunity to reduce the environmental impact and increase the economic benefits before recycling the battery. Many different second life applications have been proposed, each with multiple criteria that have to be taken into consideration when deciding the most suitable course of action. In this article, a battery assessment procedure is proposed that consolidates and expands upon the approaches in the literature, and facilitates the decision-making process for a battery after it has reached the end of its first life. The procedure is composed of three stages, including an evaluation of the state of the battery, an evaluation of the technical viability and an economic evaluation. Options for battery configurations are explored (pack direct use, stack of battery packs, module direct use, pack refurbish with modules, pack refurbish with cells). By comparing these configurations with the technical requirements for second life applications, a reader can rapidly understand the tradeoffs and practical strategies for how best to implement second life batteries for their specific application. Lastly, an economic evaluation process is developed to determine the cost of implementing various second life battery configurations and the revenue for different end use applications. An example of the battery assessment procedure is included to demonstrate how it could be carried out.

Effective Electric Vehicle (EV) operation relies on robust State of Health (SoH) estimation algorithms, key for informed battery management. Various algorithms have been proposed to estimate degradation, often depending on full charge segmentation or on conditions that deviate from real-world EV operation. Addressing this gap, this study introduces a cell-level SoH estimation algorithm based on partial charges. The proposed approach employs Health Indicators (HIs) derived from realistic laboratory testing, which contains a variety of voltage ranges during charge to replicate the complexity of real data. The study compares two commonly employed data-driven algorithms, Support Vector Regression (SVR) and Neural Networks (NN) and two estimation voltage ranges, which encompass the second and third Incremental Capacity (IC) peak. Along with the SoH, the battery functionality is estimated through the State of Function (SoF), leveraging degradation data and performance requirements for each tested cell. This enables the definition of an indicator quantifying the proximity of the battery to underperformance in specific applications. In general, the second IC peak shows higher correlation to the SoH. However, the NN SoH algorithm, when trained with high number of observations in the third IC peak, shows the lowest error with an average Root Mean Square Error (RMSE) of 0.00330. Moreover, the translation from SoH to SoF highlights the different performance requirements for each case and supports a functional definition of End of Life (EoL) beyond the fixed threshold.

The rapid deployment of electric vehicles is increasing the need for economically competitive battery technologies. While life cycle costing (LCC) is widely used to assess battery economics, most studies focus either on process-level manufacturing costs or large-scale industrial systems, limiting their applicability to emerging technologies at low technology readiness levels. This study proposes a hybrid framework combining bottom-up and top-down approaches to evaluate the economic performance of modular lithium-ion battery systems developed within the HELIOS project.The framework integrates a cradle-to-gate manufacturing cost assessment based on process-level inventory data with a top-down scalability analysis incorporating learning-curve modelling. The resulting manufacturing costs feed into a manufacturing-to-end-of-life LCC that includes second-life repurposing and recycling. The benefit of second-life deployment is captured by the functional unit, defined as total energy delivered across both first- and second-life operation.The methodology is applied to two HELIOS battery configurations for electric passenger car and e-bus applications. Prototype manufacturing costs are substantially higher than industry benchmarks but converge toward market-relevant levels as production scales. Cost targets of 130–170 €/kWh are achieved within cumulative production volumes consistent with realistic industrial deployment pathways. In the final LCC assessment, manufacturing remains the dominant cost contributor, while repurposing and end-of-life costs have a comparatively small influence. Including second-life operation reduces LCC per unit of energy delivered by 46% and 48% for the passenger car and e-bus applications, respectively.The proposed framework supports design optimisation, investment decisions, and policy development through a scalable and transferable assessment of cost evolution across the full battery life cycle.

The rapid deployment of electric vehicles is increasing the need for economically competitive battery technologies. While life cycle costing (LCC) is widely used to assess battery economics, most studies focus either on process-level manufacturing costs or large-scale industrial systems, limiting their applicability to emerging technologies at low technology readiness levels. To support early techno-economic decision-making during the transition from prototype development to industrial deployment, this study proposes a hybrid framework combining bottom-up and top-down approaches to evaluate the economic performance of modular lithium-ion battery systems developed within the HELIOS project.The framework integrates a cradle-to-gate manufacturing cost assessment based on process-level inventory data with a top-down scalability analysis incorporating learning-curve modelling. The resulting manufacturing costs feed into a manufacturing-to-end-of-life LCC that includes second-life repurposing and recycling. The benefit of second-life deployment is captured by the functional unit, defined as total energy delivered across both first- and second-life operation.The methodology is applied to two HELIOS battery configurations for electric passenger car and e-bus applications. Prototype manufacturing costs are substantially higher than industry benchmarks but converge toward market-relevant levels as production scales. Cost targets of 130–170 €/kWh are achieved within cumulative production volumes consistent with realistic industrial deployment pathways. In the final LCC assessment, manufacturing remains the dominant cost contributor, while repurposing and end-of-life costs have a comparatively small influence. Including second-life operation reduces LCC per unit of energy delivered by 46% and 48% for the passenger car and e-bus applications, respectively.The proposed framework provides a transferable decision-support tool for battery developers, manufacturers and policymakers, supporting design optimisation, investment planning and the economic assessment of emerging battery technologies prior to commercial deployment.