No abstract

Accurate health estimation and lifetime prediction of lithium-ion batteries are crucial for durable electric vehicles. Early detection of inadequate performance facilitates timely maintenance of battery systems. This reduces operational costs and prevents accidents and malfunctions. Recent advancements in "Big Data" analytics and related statistical/computational tools raised interest in data-driven battery health estimation.Here, we will review these in view of their feasibility and cost-effectiveness in dealing with battery health in real-world applications. We categorise these methods according to their underlying models/algorithms and discuss their advantages and limitations. In the final section we focus on challenges of real-time battery health management and discuss potential next-generation techniques. We are confident that this review will inform commercial technology choices and academic research agendas alike, thus boosting progress in datadriven battery health estimation and prediction on all technology readiness levels.

No abstract

Purpose The purpose of this review article is to investigate the usefulness of different types of life cycle assessment (LCA) studies of electrified vehicles to provide robust and relevant stakeholder information. It presents synthesized conclusions based on 79 papers. Another objective is to search for explanations to divergence and "complexity" of results found by other overviewing papers in the research field, and to compile methodological learnings. The hypothesis was that such divergence could be explained by differences in goal and scope definitions of the reviewed LCA studies. Methods The review has set special attention to the goal and scope formulation of all included studies. First, completeness and clarity have been assessed in view of the ISO standard's (ISO 2006a, b) recommendation for goal definition.Secondly, studies have been categorized based on technical and methodological scope, and searched for coherent conclusions.Results and discussion Comprehensive goal formulation according to the ISO standard (ISO 2006a, b) is absent in most reviewed studies. Few give any account of the time scope, indicating the temporal validity of results and conclusions. Furthermore, most studies focus on today's electric vehicle technology, which is under strong development. Consequently, there is a lack of future time perspective, e.g., to advances in material processing, manufacturing of parts, and changes in electricity production. Nevertheless, robust assessment conclusions may still be identified. Most obvious is that electricity production is the main cause of environmental impact for externally chargeable vehicles. If, and only if, the charging electricity has very low emissions of fossil carbon, electric vehicles can reach their full potential in mitigating global warming. Consequently, it is surprising that almost no studies make this stipulation a main conclusion and try to convey it as a clear message to relevant stakeholders. Also, obtaining resources can be observed as a key area for future research. In mining, leakage of toxic substances from mine tailings has been highlighted. Efficient recycling, which is often assumed in LCA studies of electrified vehicles, may reduce demand for virgin resources and production energy. However, its realization remains a future challenge. Conclusions LCA studies with clearly stated purposes and time scope are key to stakeholder lessons and guidance. It is also necessary for quality assurance. LCA practitioners studying hybrid and electric vehicles are strongly recommended to provide comprehensive and clear goal and scope formulation in line with the ISO standard (ISO 2006a, b). Responsible editor: Hans-Joerg AlthausElectronic supplementary material The online version of this article