The use of technologies such as Internet of Things (IoT), data processing and blockchain have allowed companies to serve their customers with better quality, efficiency, reliability and in the shortest possible time. The growing adoption of electric vehicles on the market has increased the demand for batteries that may have numerous manufacturers. Life expectancy is affected on manufacture, but also on operational conditions. A large number of parameters have a role on battery's health and thousands of data need to be evaluated and combined. The present work investigates the scenario of the battery industry in order to implement a blockchain-based platform for the supply chain implementation thus allowing a better control on performance of batteries and environmental impact. To achieve this goal, the authors carried out a systematic review with the following steps: identification of relevant studies, evaluation and summary of similar studies, comparison and extraction of data from the papers. The main motivation of this work is the use of the literature for justifying the use of the blockchain technology to track batteries and for identifying the main challenges in the related markets that can be addressed by this technology. The results of this systematic review show that the development of a blockchain-based platform for battery tracking will allow for greater transparency across the entire supply chain: production, reuse, recycling, disposal. Trasparency and traceability prevent clandestine markets, misuse and release of pollutants. Adressing these topics forsters the successful implemention of electric vehicles in the market. 

Blockchain review for battery supply chain monitoring and battery trading

The concept of Digital Twin (DT) is widely explored in literature for different application fields because it promises to reduce design time, enable design and operation optimization, improve after-sales services and reduce overall expenses. While the perceived benefits strongly encourage the use of DT, in the battery industry a consistent implementation approach and quantitative assessment of adapting a battery DT is missing. This paper is a part of an ongoing study that investigates the DT functionalities and quantifies the DT-attributes across the life cycles phases of a battery system. The critical question is whether battery DT is a practical and realistic solution to meeting the growing challenges of the battery industry, such as degradation evaluation, usage optimization, manufacturing inconsistencies or second-life application possibility. Within the scope of this paper, a consistent approach of DT implementation for battery cells is presented, and the main functions of the approach are tested on a Doyle-Fuller-Newman model. In essence, a battery DT can offer improved representation, performance estimation, and behavioral predictions based on real-world data along with the integration of battery life cycle attributes. Hence, this paper identifies the efforts for implementing a battery DT and provides the quantification attribute for future academic or industrial research.

Implementation of Battery Digital Twin: Approach, Functionalities and Benefits

Energy storage systems (ESS) are among the fastest-growing electrical power system due to the changing worldwide geography for electrical distribution and use. Traditionally, methods that are implemented to monitor, detect and optimize battery modules have limitations such as difficulty in balancing charging speed and battery capacity usage. A battery-management system overcomes these traditional challenges and enhances the performance of managing battery modules. The integration of advancements and new technologies enables the provision of real-time monitoring with an inclination towards Industry 4.0. In the previous literature, it has been identified that limited studies have presented their reviews by combining the literature on different digital technologies for battery-management systems. With motivation from the above aspects, the study discussed here aims to provide a review of the significance of digital technologies like wireless sensor networks (WSN), the Internet of Things (IoT), artificial intelligence (AI), cloud computing, edge computing, blockchain, and digital twin and machine learning (ML) in the enhancement of battery-management systems. Finally, this article suggests significant recommendations such as edge computing with AI model-based devices, customized IoT-based devices, hybrid AI models and ML-based computing, digital twins for battery modeling, and blockchain for real-time data sharing.

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Digital Technology Implementation in Battery-Management Systems for Sustainable Energy Storage: Review, Challenges, and Recommendations

Digitalization and decarbonization are projected to be two major trends in the coming decades. As the already widespread process of digitalization continues to progress, especially in energy and transportation systems, massive data will be produced, and how these data could support and promote decarbonization has become a pressing concern. This paper presents a comprehensive review of digital technologies and their potential applications in low-carbon energy and transportation systems from the perspectives of infrastructure, common mechanisms and algorithms, and system-level impacts, as well as the application of digital technologies to coupled energy and transportation systems with electric vehicles. This paper also identifies corresponding challenges and future research directions, such as in the field of blockchain, digital twin, vehicle-to-grid, low-carbon computing, and data security and privacy, especially in the context of integrated energy and transportation systems. 

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Shaping future low-carbon energy and transportation systems: Digital technologies and applications

Safety is a major challenge plaguing the use of Li-ion batteries (LIBs) in electric vehicle (EV) applications. A wide range of operating conditions with varying temperatures and drive cycles can lead to battery abuse. A dangerous consequence of these abuses is thermal runaway (TR), an exponential increase in temperature inside the battery caused by the exothermic decomposition of the cell materials that leads to fire and explosion. It is imperative to develop methodologies to accurately predict and mitigate thermal runway. Sodium-ion batteries (SIBs) are inherently safer than LIBs. In addition to offering better safety, SIBs are gaining momentum due to the abundance and low cost of their raw materials compared to the limited lithium resources and high cost of elements such as cobalt, copper, and nickel used in LIBs. However, the challenge of low energy density impedes the maturation of sodium-ion technology to the same level as lithium-ion technology. There are additional challenges to the acceptability of sodium-ion batteries due to the poor sodium kinetics during insertion reactions, leading to rapid material degradation. Additionally, the higher solubility of the solid electrolyte interface (SEI) observed in the case of SIBs may lead to undesired side reactions, causing increased heat generation. This paper presents a comprehensive review of the heat-release mechanisms, their differences, and prediction methodologies for the two battery chemistries. Various experimental and modeling approaches for TR detection from the literature are reviewed. Future research directions toward the development of a battery management system (BMS) with the capability to identify the precursors to thermal runaway and implement mitigation strategies are also discussed. 

Thermal Behavior of Lithium- and Sodium-Ion Batteries: A Review on Heat Generation, Battery Degradation, Thermal Runway – Perspective and Future Directions

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 of the digital twin, and summarizes current research methods and challenges in battery modeling, state estimation, remaining useful life prediction, battery safety and control. Furthermore, based on digital twin we describe the solutions for battery digital modeling, real-time state estimation, dynamic charging control, dynamic thermal management, and dynamic equalization control in the intelligent battery management system. We also give development opportunities for digital twin in the battery field. Finally we summarize the development trends and challenges of smart battery management.

Jun Wang

Papers

Application of Digital Twin in Smart Battery Management Systems

Fast response humidity sensor based on hyperbranched zwitterionic polymer for respiratory monitoring and non-contact human machine interface