2021
DOI: 10.1186/s10033-021-00577-0
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Application of Digital Twin in Smart Battery Management Systems

Abstract: Lithium-ion batteries have always been a focus of research on new energy vehicles, however, their internal reactions are complex, and problems such as battery aging and safety have not been fully understood. In view of the research and preliminary application of the digital twin in complex systems such as aerospace, we will have the opportunity to use the digital twin to solve the bottleneck of current battery research. Firstly, this paper arranges the development history, basic concepts and key technologies o… Show more

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Cited by 83 publications
(29 citation statements)
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“…Such temperature measurements and models do not represent the battery behaviour in the actual EV operating conditions. Making the digital twin for the battery pack is a complex task and certainly poses challenges as there are inconsistencies among the cells in the pack due to defects in manufacturing, leading to non-uniformity and equalisation problems [8]. This poses a paramount challenge to study and predict the complete battery pack interdependent electrical, thermal and ageing (calendar and cyclic) behaviour in real-time.…”
Section: Introductionmentioning
confidence: 99%
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“…Such temperature measurements and models do not represent the battery behaviour in the actual EV operating conditions. Making the digital twin for the battery pack is a complex task and certainly poses challenges as there are inconsistencies among the cells in the pack due to defects in manufacturing, leading to non-uniformity and equalisation problems [8]. This poses a paramount challenge to study and predict the complete battery pack interdependent electrical, thermal and ageing (calendar and cyclic) behaviour in real-time.…”
Section: Introductionmentioning
confidence: 99%
“…Recently, the notion of digital twin is receiving great attention as it can be used for real-time monitoring of complex multiphysics systems and is also responsible for bi-directional mapping of the actual physical system to its virtual system [6][7][8]. Digital twin is not one specific method but a comprehensive framework that is based on a combination of advanced technologies, such as artificial intelligence (AI) with clusters of machine learning (ML) algorithms, Internet of Things (IoT), blockchain, cloud storage and cloud computing, sensors, hardware etc., to achieve its primary goal of connecting virtual systems to real systems and predict and optimise its behaviour in real time [9,10].…”
Section: Introductionmentioning
confidence: 99%
“…Lithium-ion (Li-ion) batteries are widely used in Electric Vehicles (EVs) and stationary energy storage because of their high charge/discharge efficiency, low self-discharge rate, and long lifespan [1]- [3]. To extend the service life of the batteries and ensure their safe operation, a well-designed Battery Management System (BMS) is required to monitor the State of Health (SOH) and State of Charge (SOC) [4]- [6]. Model-based estimation approaches, such as Kalman filters and particle filter, have been proposed to realize these functionalities.…”
Section: Introductionmentioning
confidence: 99%
“…Sensing the battery data and uploading that to a storage server gives the opportunity to easily access the battery data and create learning models, which directly guide the product design, and optimization process [27]. The battery data storage platform stores the design and usage history, which supports behavioral integration in consequent life cycle phases and simplifies the prediction of the remaining useful life (RUL) during operation and also at EoL for second life assessment [32].…”
mentioning
confidence: 99%
“…Similarly, thermal management based on battery DT relies on prediction of aging effect of temperature distribution across the battery pack using thermal models. Detection and traceability of sensor faults, electrical faults, and thermal runaway in a battery DT can allow integration of fault diagnosis procedure of the BMS with the battery DT functionalities [32].…”
mentioning
confidence: 99%