EV Mobility 2030

The increasing awareness on the harmful effects on the environment of traditional Internal Combustion Engines (ICE) is driving the industry toward cleaner powertrain technologies such as battery-driven Electric Vehicles. Nonetheless, the high energy density of Li-Ion batteries can cause strong exothermic reactions under certain conditions that can lead to catastrophic results, called Thermal Runaway (TR). Hence, a strong effort is being placed on understanding this phenomena and increase battery safety. Specifically, the vented gases and their ignition can cause the propagation of this phenomenon to adjancent batteries in a pack. In this work, Computational Fluid Dynamics (CFD) are employed to predict this venting process in a LG18650 cylindrical battery. The ejection of the generated gases was considered to analyze its dispersion in the surrounding volume through a Reynolds-Averaged Navier-Stokes (RANS) approach. Initial work has focused on developing an appropiate methodology to set the proper boundary conditions that recreate faithfully these events. Once achieved, macroscopic characteristics of the jet including spray tip penetration and spray angle have been extracted and compared against results obtained from Schlieren technique for the initial venting stage (1st venting) and the TR stage (2nd venting). The numerical procedure shows a good agreement with experimental results in the characteristics analyzed, allowing to overcome the limited field-of-view of Schlieren results by providing a complete representation of the spray morphology. Acknowledgements: Research funded by Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación and FEDER through the project PID2021-124696OB-C21 (MCIN/AEI/10.13039/501100011033/FEDER,UE).

The extension of traction batteries from electric vehicles with supercapacitors is regularly discussed as a possibility to increase the lifetime of lithium-ion batteries as well as the performance of the vehicle drive. The objective of this work was to validate these assumptions by developing a simulation model. In addition, an economic analysis is performed to qualitatively classify the simulation results. Initially, a hybrid energy storage system consisting of battery and supercapacitor was developed. A semi-active hybrid energy storage topology was selected. Subsequently, the selection of use cases as well as the application-specific definition of load cycles took place. In addition, the control strategy was further developed so that a simulation on lifetime was made possible. The end-of-life of the battery cells was defined, according to the USABC guideline values. Based on the data of the respective use case, a parameter optimization was carried out according to an empirical approach. In the final step, the developed hybrid energy storage system and the conventional battery system were compared, and the results evaluated both technically and economically. A slowdown of the aging effects and thus an improvement of the battery lifetime in the hybrid energy storage system could be clearly demonstrated. Despite proof of the technical advantage, the use of electric hybrid systems consisting of a battery and supercapacitor in electric vehicles is currently questionable due to the high additional costs. Through further technical development, subsidies or the construction of new, highly automated production facilities, supercapacitors will experience a price reduction in the future, which is why electric hybrid energy storage systems can play an important role in the mobility of tomorrow.

In the dynamic landscape of battery development, the quest for improved energy storage and efficiency has become paramount. The contemporary energy transition, coupled with growing demands for electric vehicles, renewable energy sources, and portable electronic devices, has underscored the critical role that batteries play in our modern world. To navigate this challenging terrain and harness the full potential of battery technology, a well-defined and comprehensive data strategy resp. knowledge management strategy are indispensable. Conversely, the imminent and rapid progression of artificial intelligence (AI) is poised to have a substantial impact on the forthcoming landscape of work and the methodologies organizations employ for the management of their knowledge management (KM) procedures. Conventional KM endeavors encompass a spectrum of activities such as the creation, transmission, retention, and evaluation of an enterprise’s knowledge over the entire knowledge lifecycle. However, these effortsfrequently overlook the ongoing advancements within the domain of AI. Consequently, organizations grapple with the integration of AI into their operational milieu to harness enhanced efficiency in outcomes. This paper will draw upon the tenets of the already established KM strategies in AVL High Voltage Energy Systems Team and AI-centric paradigm tailored for the implementation of KMS within organizational frameworks. Our proposed approach serves to fortify the foundations of KM strategy by outlining the ways in which AI interfaces with existing operational procedures. This, in turn, enables a comprehensive comprehension of the potential roles AI could assume in theintricate interplay between knowledge workers and AI systems.

With the surge of electric vehicles (EVs), high capacity, high energy density materials are essential to fulfill long-distance travel. Ni-rich cathodes are dominant owing to their high energy density and good rate capability. Batteries are the fastest growing market for nickel and the Nickel Institute (NI) is quite active in this space. This presentation provides an overview of the NI Battery Program followed by the current global EV market and the share of nickel-based battery chemistries. Furthermore, a discussion on the patent landscape and the latest technology developments is included.

Not for cases with sizeable irreversible swelling from plating or gas evolution. Dimensional changes of cells can be harbingers of poor health.