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Cloud-Based Battery Digital Twin Middleware Using Model-Based Development

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Published:06 June 2020Publication History

ABSTRACT

Following the trends of electrification, the energy storage of vehicles is gaining importance as the most expensive part of an electric car. Since lithium-ion batteries are perishable goods and underlie e. g. aging effects, environmental and operating conditions during manufacturing and car usage need close supervision. With regard to the paradigm of digital twins, data from various life cycle phases needs to be collected and processed to improve the general quality of the system. To achieve this complex task, a suitable framework is needed in order to operate the fleet of digital twins during manufacturing processes, the automotive usage and a potential second life. Based on a literature review, we formulate requirements for a digital twin framework in the field of battery systems. We propose a framework to develop and operate a fleet of digital twins during all life cycle phases. Results feature a case study in which we implement the stated framework in a cloud-computing environment using early stages of battery system production as test a bed. With the help of a self-discharge model of li-ion cells, the system can estimate the SOC of battery modules and provide this information to the arrival testing procedures.

References

  1. Alam, K. M., Sopena, A., and Saddik, A. E. Design and Development of a Cloud Based Cyber-Physical Architecture for the Internet-of-Things. Proceedings - 2015 IEEE International Symposium on Multimedia, ISM 2015 (2016), 459--464.Google ScholarGoogle Scholar
  2. Bao, J., Guo, D., Li, J., and Zhang, J. The modelling and operations for the digital twin in the context of manufacturing. Enterprise Information Systems 0, 0 (2018), 1--23.Google ScholarGoogle Scholar
  3. Ciavotta, M., Alge, M., Menato, S., Rovere, D., and Pedrazzoli, P. A Microservice-based Middleware for the Digital Factory. Procedia Manufacturing 11, June (2017), 931--938.Google ScholarGoogle ScholarCross RefCross Ref
  4. Delsing, J. Arrowhead, 2019.Google ScholarGoogle Scholar
  5. Deutschen, T., Gasser, S., Schaller, M., and Siehr, J. Modeling the self-discharge by voltage decay of a NMC/ graphite lithium-ion cell. Journal of Energy Storage 19, June (2018), 113--119.Google ScholarGoogle ScholarCross RefCross Ref
  6. Ding, K., Chan, F. T., Zhang, X., Zhou, G., and Zhang, F. Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors. International Journal of Production Research 0, 0 (2019), 1--20.Google ScholarGoogle Scholar
  7. Etzkorn, L. H. Introduction to Middleware, 1 ed. Chapman and Hall/CRC, New York, 2017.Google ScholarGoogle Scholar
  8. Liu, X. F., Al Sunny, S. M. N., Nguyen, N.-T., Tao, W., Leu, M. C., Shahriar, M. R., and Hu, L. Modeling of Cloud-Based Digital Twins for Smart Manufacturing with MT Connect. Procedia Manufacturing 26 (2018), 1193--1203.Google ScholarGoogle ScholarCross RefCross Ref
  9. Lukasiewycz, M., Steinhorst, S., Sagstetter, F., Chang, W., Waszecki, P., Kauer, M., and Chakraborty, S. Cyber-Physical Systems Design for Electric Vehicles. In 2012 15th Euromicro Conference on Digital System Design (sep 2012), IEEE, pp. 477--484.Google ScholarGoogle Scholar
  10. Merkle, L., Segura, A. S., Torben Grummel, J., and Lienkamp, M. Architecture of a Digital Twin for Enabling Digital Services for Battery Systems. In 2019 IEEE International Conference on Industrial Cyber Physical Systems (ICPS) (may 2019), IEEE, pp. 155--160.Google ScholarGoogle ScholarCross RefCross Ref
  11. Monostori, L., Kádár, B., Bauernhansl, T., Kondoh, S., Kumara, S., Reinhart, G., Sauer, O., Schuh, G., Sihn, W., and Ueda, K. Cyber-physical systems in manufacturing. CIRP Annals 65, 2 (2016), 621--641.Google ScholarGoogle ScholarCross RefCross Ref
  12. OASIS Standard. Mqtt-v3.1.1- Specification, 2014.Google ScholarGoogle Scholar
  13. OMG. Data Distribution Service Specification Version 1.4, 2015.Google ScholarGoogle Scholar
  14. Schluse, M., and Rossmann, J. From Simulation to Experimentable Digital Twins. Systems Engineering (ISSE), 2016 IEEE International Symposium on (2016), 1--6.Google ScholarGoogle ScholarCross RefCross Ref
  15. Schroeder, G. N., Steinmetz, C., Pereira, C. E., and Espindola, D. B. Digital Twin Data Modeling with AutomationML and a Communication Methodology for Data Exchange. IFAC-PapersOnLine 49, 30 (2016), 12--17.Google ScholarGoogle ScholarCross RefCross Ref
  16. Yun, S., Park, J. H., and Kim, W. T. Data-centric middleware based digital twin platform for dependable cyber-physical systems. International Conference on Ubiquitous and Future Networks, ICUFN (2017), 922--926.Google ScholarGoogle ScholarCross RefCross Ref

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  1. Cloud-Based Battery Digital Twin Middleware Using Model-Based Development

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              cover image ACM Other conferences
              ISCSIC 2019: Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control
              September 2019
              397 pages
              ISBN:9781450376617
              DOI:10.1145/3386164

              Copyright © 2019 ACM

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              Publication History

              • Published: 6 June 2020

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              ISCSIC 2019 Paper Acceptance Rate77of152submissions,51%Overall Acceptance Rate192of401submissions,48%

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