Research// Energy storage systems

SmartPro – Key to Smart Products!

In order to be able to store energy, for example from regenerative sources, for later use, energy storage technologies such as efficient batteries are urgently needed. Due to the increased demands on the performance of mobile electronic devices and electrified vehicles in terms of charging time and range as well as on new energy sources, the current request for rechargeable batteries with enhanced energy density has significantly increased. Thus, research is of particular relevance – both economically as well as socio-politically.

The research projects LiMaProMet (2017-2021) and Smart-BAT (2021-2025) of the SmartPro partnership proceed to improve both energy density and quality of batteries as well as to reduce the production costs.

Smart-BAT

// Project duration: 01.03.2021 to 28.02.2025

 

Project management

Prof. Dr. Timo Sörgel
Zentrum Elektrochemische Oberflächentechnik
Phone: +49 (0) 7361 576-2468
timo.soergel@hs-aalen.de

 

Project partner

Aalen University
Companies
  • Carl Zeiss IMT
  • Carl Zeiss Microscopy GmbH
  • IoLiTec
  • Kessler & Co. GmbH & Co. KG
  • VARTA Microbattery GmbH
  • Volkswagen AG
  • Wieland-Werke AG
Other research institutions
  • Forschungsinstitut Edelmetalle und Metallchemie (fem)
  • Karlsruher Institut für Technologie (KIT) – Institut für Angewandte Materialien Werkstoff- und Biomechanik (IAM-WBM)
Transfer players

e-mobil BW GmbH

Smart-BAT

New material concepts, innovative process technologies and evaluation tools for future lithium-based battery systems

Energy storage systems – among these especially rechargeable batteries (accumulators) – are indispensable for the energy transition. They are not only used in electromobility, but also play an important role in the consumer sector and in medical technology. As a result, the requirements for such batteries are also increasing. They are asked/called/wanted to perform better and better, to have higher energy density and quality as well as a longer service life, and ideally be as cost-effective as possible. The project Smart-BAT addressed these requirements in three subprojects.

Firstly, the aim is to increase the energy density of solid-state batteries. Correlations between the battery material’s microstructure and its properties like performance and quality were examined and innovative manufacturing processes developed.

In parallel, research on new electrode structures and manufacturing processes is aimed at the development of new smart battery concepts. Here, the focus is on three-dimensional current collectors made of highly porous aluminum foam, which are manufactured by means of electrodeposition.

Intelligent quality assurance methods based on Machine Learning are also developed as suitable tools for assessing battery quality − crucial for effective digitization of industrial processes.

LiMaProMet

Smart material systems, intelligent manufacturing processes and quality methods for lithium-based batteries

The demand for rechargeable batteries with increased energy density, safety and lifetime is very high due to the increased requirements for mobile applications. In recent years, the focus has been on range, charging time and safety for resource-efficient electromobility, energy supply or portable electronics. The increased use of renewable energies anticipated in the energy transition requires cost-effective energy storage systems with a long service life. Crucial keys are smart battery materials as well as intelligent manufacturing processes and quality assessment methods. Therefore, the (impulse) project LiMaProMet aimed at developing intelligent lithium-based storage technologies to market maturity.

LiMaProMet

// Project duration: 01.03.2017 to 31.08.2021

 

Project management

Prof. Dr. Timo Sörgel
Surface Technology
Phone: +49 (0) 7361 576-2468
timo.soergel@hs-aalen.de

 

Project partner

Aalen University
Companies
  • Carl Zeiss Microscopy GmbH
  • CCT GmbH
  • Kessler & Co. GmbH & Co. KG
  • Outlast Europe GmbH
  • VARTA Microbattery GmbH
Other research institutions
  • Forschungsinstitut Edelmetalle und Metallchemie (fem)
  • Karlsruher Institut für Technologie (KIT) – Institut für Angewandte Materialien Werkstoff- und Biomechanik (IAM-WBM)
  • Universität Ulm – Institut für Elektrochemie
Transfer players
  • e-mobil BW GmbH

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Explorative projects

To further deepen research into more efficient batteries, explorative projects have examined, for example, how manufacturing processes can be monitored and improved using Artificial Intelligence.

PreMo-LiB // 01.03.2019 to 31.08.2020

Artificial Intelligence and Machine Learning as enablers for improving process quality in battery mass production

High-quality lithium-ion batteries with a long service life is needed in many industrial products, e.g. in electric cars, smartphones or power tools. In the explorative project PreMo-LiB, we − in cooperation with the Varta Microbattery GmbH − investigated innovative in-line methods enabling to predict the service life of accumulators and to improve their overall quality. To achieve this, we used modern self-learning software algorithms − Machine Learning (applied Artificial Intelligence).

Commonly, it is only in later usage that a lithium-ion based battery is revealed whether it meets the customer requirements. Due to the complex physical interactions within a battery, so far, quality prediction during production has been only possible to a very limited extent and not suitable for mass production.

But remarkably, in the project PreMo-LiB, Machine Learning methods could have been developed to predict the quality and service life of (test) batteries during production in a both cost-effective and feasible manner. Most importantly, the established quality assurance process is non-destructive and scalable for the mass production of high-quality lithium-ion batteries.

  • Project management

    Prof. Dr. Ricardo Büttner, Wirtschaftsinformatik

  • Project partner

    VARTA Microbattery GmbH

DiMa // 01.10.2019 to 30.09.2020

Digitization potential of materials research in SmartPro

The explorative project DiMa on Machine Learning methods was carried out in four subprojects, each of which focused on one of the applications fields of SmartPro or Additive Manufacturing, respectively. Here, the methodological competence of ML experts was combined with expertise in the particular research areas. In this way, interdisciplinary approaches were successfully used to push research further towards tailored (development and) application of ML methods within SmartPro. Each of the four subprojects served as a starting point for the current cross-sectional impulse project BEYOND with a focus on Machine Learning.

Based on the subproject DigitEL on energy storage systems (assigned to the impulse project LiMaProMet) the application of Machine Learning in the analysis of microstructures of electrode material in lithium-ion accumulators was improved with respect to performance parameters. A particular focus was on the prediction of current rate capability.

SmartPro // FH-Impuls:
Strong universities of applied sciences – impulses for the region

With SmartPro, Aalen University of Applied Sciences has positioned itself in the top group of universities of applied sciences nationwide. SmartPro is one of ten partnerships funded by the funding measure “FH-Impuls” of the Federal Ministry of Education and Research with around 10 million euros from 2017 until 2025. Core objectives are the sustainable expansion of the regional transfer and cooperation network, the strengthening of research, and innovative power. SmartPro makes contributions to social challenges such as climate protection and digitization.