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Whitepaper: A new generation of aging models for lithium-ion batteries

The ongoing global energy transition, driven by the dual imperatives of environmental sustainability and economic efficiency, has catalyzed the rise of two essential fields: electric vehicles (EVs) and energy storage systems (ESS). At the heart of these innovative technologies lies an essential component — the battery system. Its performance, efficiency, and longevity significantly impact the overall functionality and viability of both EVs and ESS.Over the last few years, scientists have invested a lot of time and resources to optimize semi-empirical, physico-chemical, and data-driven simulation models. All of them show different challenges and limitations. To overcome this dead end, scientists and engineers combine physicochemical-mechanical degradation effects and integrate them into (semi)-empirical as well as data-driven approaches. We call this combination physics-motivated semi-empirical aging models.
The whitepaper covers the following topics:
The new TWAICE simulation model portfolio: base model, customized base model, premium model
The new generation of physics-motivated semi-empirical aging models: OCV aging, degradation modes, understanding the accuracy of models, simulation of swelling force
Vision and outlook
Download the whitepaper from TWAICE
Download the whitepaper from TWAICE
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The post Whitepaper: A new generation of aging models for lithium-ion batteries first appeared on EV Tech Insider.