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

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.