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Lithium-ion batteries are developing into a widely used technology in the field of electromobility, defense and stationary energy storage owing to their high energy density and low associated costs. However, recent incidents such as rapid failure of battery packs, fire-safety issues and damage to battery packs by fast-charging have harmed brand reputations of cell manufacturers and OEMs. Majority of such incidents are a result of poor cell quality and ineffective quality-detection methods adopted as the industry standard. Real-time electrochemical impedance spectroscopy (RT-EIS) by far supersedes the existing quality-detection methods in the most important metrics - speed, accuracy, robustness and operational costs.
Combined with the power of intelligent algorithms, machine-learning and digital twin modelling, the impedance data of batteries can be automatically analyzed to effectively assess the quality of lithium-ion batteries and predict the electrical, thermal and aging behaviour of cells. When RT-EIS is further integrated into a standardized and scalable quality assurance system, cell manufacturers and OEMs can ensure the safety of their battery systems and reduce the warranty and maintenance costs, thereby maintaining a stellar brand reputation and smooth operation of a profitable business model.PDF download