48 research outputs found
Digitalization of Battery Manufacturing: Current Status, Challenges, and Opportunities
As the world races to respond to the diverse and expanding demands for electrochemical energy storage solutions, lithium-ion batteries (LIBs) remain the most advanced technology in the battery ecosystem. Even as unprecedented demand for state-of-the-art batteries drives gigascale production around the world, there are increasing calls for next-generation batteries that are safer, more affordable, and energy-dense. These trends motivate the intense pursuit of battery manufacturing processes that are cost effective, scalable, and sustainable. The digital transformation of battery manufacturing plants can help meet these needs. This review provides a detailed discussion of the current and near-term developments for the digitalization of the battery cell manufacturing chain and presents future perspectives in this field. Current modelling approaches are reviewed, and a discussion is presented on how these elements can be combined with data acquisition instruments and communication protocols in a framework for building a digital twin of the battery manufacturing chain. The challenges and emerging techniques provided here is expected to give scientists and engineers from both industry and academia a guide toward more intelligent and interconnected battery manufacturing processes in the future
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Reliability evaluation of Lithium-Ion batteries for e-mobility applications from practical and technical perspectives: A case study
Copyright: © 2021 by the authors. Evaluation of the reliability of the components of electric vehicles (EVs) has been studied by international research centers, industry, and original equipment manufacturers over the last few years. Li-ion batteries are the main sensitive component of an EV’s E-power train. In other words, the Li-ion batteries for electromobility applications are one of the main components of an EV, which should be reliable and safe over the operational lifetime of the EV. Thus, investigating how to assess the reliability of the Li-ion battery has been a highly recommended task in most European projects. Moreover, with the increase in the number of new EVs made by European car companies, there has been a competition for market acquisition by these companies to win over customers and gain more market share. This article presents a comprehensive overview of the evaluation of the reliability of Li-ion batteries from practical and technical perspectives. Moreover, a case study for assessing reliability from practical and technical perspectives has been investigated.Deanship of Scientific Research at Jouf University, Saudi Arabia (Grant No. DSR-2021-02-0309)
Implications of the BATTERY 2030+ AI-Assisted Toolkit on Future Low-TRL Battery Discoveries and Chemistries
Funder: Swedish national Strategic e‐Science programmeFunder: Deutsche Forschungsgemeinschaft; Id: http://dx.doi.org/10.13039/501100001659BATTERY 2030+ targets the development of a chemistry neutral platform for accelerating the development of new sustainable high-performance batteries. Here, a description is given of how the AI-assisted toolkits and methodologies developed in BATTERY 2030+ can be transferred and applied to representative examples of future battery chemistries, materials, and concepts. This perspective highlights some of the main scientific and technological challenges facing emerging low-technology readiness level (TRL) battery chemistries and concepts, and specifically how the AI-assisted toolkit developed within BIG-MAP and other BATTERY 2030+ projects can be applied to resolve these. The methodological perspectives and challenges in areas like predictive long time- and length-scale simulations of multi-species systems, dynamic processes at battery interfaces, deep learned multi-scaling and explainable AI, as well as AI-assisted materials characterization, self-driving labs, closed-loop optimization, and AI for advanced sensing and self-healing are introduced. A description is given of tools and modules can be transferred to be applied to a select set of emerging low-TRL battery chemistries and concepts covering multivalent anodes, metal-sulfur/oxygen systems, non-crystalline, nano-structured and disordered systems, organic battery materials, and bulk vs. interface-limited batteries
Rechargeable Batteries of the Future—The State of the Art from a BATTERY 2030+ Perspective
The development of new batteries has historically been achieved through discovery and development cycles based on the intuition of the researcher, followed by experimental trial and error—often helped along by serendipitous breakthroughs. Meanwhile, it is evident that new strategies are needed to master the ever-growing complexity in the development of battery systems, and to fast-track the transfer of findings from the laboratory into commercially viable products. This review gives an overview over the future needs and the current state-of-the art of five research pillars of the European Large-Scale Research Initiative BATTERY 2030+, namely 1) Battery Interface Genome in combination with a Materials Acceleration Platform (BIG-MAP), progress toward the development of 2) self-healing battery materials, and methods for operando, 3) sensing to monitor battery health. These subjects are complemented by an overview over current and up-coming strategies to optimize 4) manufacturability of batteries and efforts toward development of a circular battery economy through implementation of 5) recyclability aspects in the design of the battery
A Roadmap for Transforming Research to Invent the Batteries of the Future Designed within the European Large Scale Research Initiative BATTERY 2030+
This roadmap presents the transformational research ideas proposed by “BATTERY 2030+,” the European large-scale research initiative for future battery chemistries. A “chemistry-neutral” roadmap to advance battery research, particularly at low technology readiness levels, is outlined, with a time horizon of more than ten years. The roadmap is centered around six themes: 1) accelerated materials discovery platform, 2) battery interface genome, with the integration of smart functionalities such as 3) sensing and 4) self-healing processes. Beyond chemistry related aspects also include crosscutting research regarding 5) manufacturability and 6) recyclability. This roadmap should be seen as an enabling complement to the global battery roadmaps which focus on expected ultrahigh battery performance, especially for the future of transport. Batteries are used in many applications and are considered to be one technology necessary to reach the climate goals. Currently the market is dominated by lithium-ion batteries, which perform well, but despite new generations coming in the near future, they will soon approach their performance limits. Without major breakthroughs, battery performance and production requirements will not be sufficient to enable the building of a climate-neutral society. Through this “chemistry neutral” approach a generic toolbox transforming the way batteries are developed, designed and manufactured, will be created
Degradation Mechanism Detection for NMC Batteries based on Incremental Capacity Curves
Path dependence degradation detection is getting lot of attention due to high demand of long lasting batteries for applications with sporadic usage such as electric vehicles. In this regard, this work presents a study of the degradation mechanism of NMC/Graphite cells cycled under different depth of discharges. Analysis will be based on the study of incremental capacity curves. The trends observed on experimental curves will be compared to simulations in order to exemplify the differences and highlight the path dependence of the degradation
Understanding Voltage Behavior of Lithium-Ion Batteries in Electric Vehicles Applications
Electric vehicle (EV) markets have evolved. In this regard, rechargeable batteries such as lithium-ion (Li-ion) batteries become critical in EV applications. However, the nonlinear features of Li-ion batteries make their performance over their lifetime, reliability, and control more difficult. In this regard, the battery management system (BMS) is crucial for monitoring, handling, and improving the lifespan and reliability of this type of battery from cell to pack levels, particularly in EV applications. Accordingly, the BMS should control and monitor the voltage, current, and temperature of the battery system during the lifespan of the battery. In this article, the BMS definition, state of health (SoH) and state of charge (SoC) methods, and battery fault detection methods were investigated as crucial aspects of the control strategy of Li-ion batteries for assessing and improving the reliability of the system. Moreover, for a clear understanding of the voltage behavior of the battery, the open-circuit voltage (OCV) at three ambient temperatures, 10 °C, 25 °C, and 45 °C, and three different SoC levels, 80%, 50%, and 20%, were investigated. The results obtained showed that altering the ambient temperature impacts the OCV variations of the battery. For instance, by increasing the temperature, the voltage fluctuation at 45 °C at low SoC of 50% and 20% was more significant than in the other conditions. In contrast, the rate of the OCV at different SoC in low and high temperatures was more stable
Understanding Voltage Behavior of Lithium-Ion Batteries in Electric Vehicles Applications
Electric vehicle (EV) markets have evolved. In this regard, rechargeable batteries such as lithium-ion (Li-ion) batteries become critical in EV applications. However, the nonlinear features of Li-ion batteries make their performance over their lifetime, reliability, and control more difficult. In this regard, the battery management system (BMS) is crucial for monitoring, handling, and improving the lifespan and reliability of this type of battery from cell to pack levels, particularly in EV applications. Accordingly, the BMS should control and monitor the voltage, current, and temperature of the battery system during the lifespan of the battery. In this article, the BMS definition, state of health (SoH) and state of charge (SoC) methods, and battery fault detection methods were investigated as crucial aspects of the control strategy of Li-ion batteries for assessing and improving the reliability of the system. Moreover, for a clear understanding of the voltage behavior of the battery, the open-circuit voltage (OCV) at three ambient temperatures, 10 °C, 25 °C, and 45 °C, and three different SoC levels, 80%, 50%, and 20%, were investigated. The results obtained showed that altering the ambient temperature impacts the OCV variations of the battery. For instance, by increasing the temperature, the voltage fluctuation at 45 °C at low SoC of 50% and 20% was more significant than in the other conditions. In contrast, the rate of the OCV at different SoC in low and high temperatures was more stable