Blockchain Papers

Taner Çarkıt

No abstract is available for this record.

Ngoc-Tien Tran

The accelerating adoption of Electric Vehicles (EVs) has intensified the need for efficient and sustainable life-cycle management of Lithium-Ion Batteries (LIBs). However, the complexity of battery supply chains, data fragmentation, and varying technological characteristics among distributed ledger platforms create significant uncertainty in selecting an appropriate infrastructure for implementing Digital Battery Passports (DBP). This study proposes a structured decision-support model to evaluate and differentiate among Distributed Ledger Technologies (DLT) under an uncertain decision environment. The proposed framework integrates the plithogenic set theory to capture expert uncertainty and inconsistency, the Best–Worst Method (BWM) to determine the relative importance of evaluation criteria, and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank alternative platforms. The model is applied to assess eight leading DLT platforms for DBP implementation in the automotive context. The results indicate that Hedera is the most suitable platform, achieving the highest TOPSIS closeness coefficient (0.8223), followed by IOTA and EOS. The findings confirm that incorporating contradiction-aware uncertainty modeling into a hybrid MCDM framework enhances the robustness and transparency of DLT platform selection for DBP-oriented applications.

Seyit Cem Yılmaz, İrfan Kösesoy

The transition to electric vehicles (EVs) plays a critical role in reducing global carbon emissions. However, the end-of-life management of electric vehicle batteries (EVBs) presents significant sustainability and operational challenges. This study proposes a blockchain-based framework that enables full lifecycle tracking of EVBs, from production to disposal or reuse, while addressing issues of transparency, efficiency, and regulatory compliance. The framework incorporates a multi-criteria decision model to guide data-driven end-of-life routing—whether for second-life reuse or direct recycling—based on technical, environmental, and economic indicators. By integrating smart contracts with a hybrid web/mobile platform, the system ensures tamper-proof documentation, stakeholder accountability, and compliance with the EU battery passport regulation. A detailed cost analysis of deploying the framework on Ethereum is also presented. The proposed solution aims to enhance the sustainability of EVB management, reduce environmental impact, and promote circular economy practices within the EV industry.

K Sujit, Komala Chowdenahally Ramaswamy, Siva Ramkumar M, Jayant Giri · 5 authors

Research and development in the vehicle industry have emphasized the potential for advancing electric transportation that is highly efficient, secure, and sustainable. The electric vehicle (EV), powered by renewable energy sources and equipped with high-efficiency electric motors and controls, offers a practical, dependable, and ecologically friendly urban transportation system. EVs operate using a battery that is equipped onboard. Practical and dependable system operation relies heavily on managing and monitoring batteries. Nevertheless, the market for electric vehicles has experienced a decline in growth due to their limited lifespan and high price. To enhance the system's efficiency and lifespan, substantially improving the battery management aspect is imperative. In this research, the Internet of Things (IoT), machine learning (ML), and Blockchain (BC) technologies are used to develop an energy-efficient EV battery management system (BMS). The IoT sensors are attached to the electric vehicles to collect data such as the charging level, the distance that must be driven, and the position of the electric vehicles. This information was saved and processed by a database, then inputted to the LightGBM classifier to determine the cost of charging. After that, it was processed by the power scheduling approach (PSA) to determine the space and time of charging that is closest to a particular electric vehicle and the charging site. At last, this information is saved in blocks to prevent electric vehicles from being misrouted and ensure that pricing transactions between users and charging stations are conducted securely using BC. The results demonstrate that the research model provided enhanced EV-BMS with an accuracy rate of 96.52% and that it retains a communication overhead that is 12% lower compared to the other models.

Rashmi Sharma, Himani Garg, Chitvan Agrawal

With the growing prevalence of electric vehicles (EVs), electrical grids face increasing strain due to heightened demand and potential overload during charging. This paper proposes a tokenized Ethereum-based framework that enables charging point operators (CPOs) and stations (CSs) to manage EV charging requests while ensuring grid stability through time flexibility (adjustable durations) and power flexibility (dynamic load modulation). Smart contracts automate peer-to-peer trading of charging parameters like energy needs and time limits, shifting loads to off-peak hours and adjusting prices based on real-time grid capacity. Simulations reveal that EV users who adopted time- and power-flexible charging experienced a 42% increase in participation compared to those using rigid, fixed-rate systems. Two scenarios were tested: 1) requests every 15 minutes on a 33 kW grid, where smart charging achieved a 71% efficiency improvement over uncontrolled charging and increased acceptance rates from 38% to 70%; and 2) consecutive requests to the same CSs, where acceptance rates rose from 23% to 43%, with smart charging reducing peak-to-valley load differences by 43–50%, flattening demand profiles. The system, developed on Ethereum using Remix IDE and MetaMask and tested on the Sepolia testnet, demonstrates higher electricity sales, improved grid stability, and enhanced flexibility in time, power, and cost. Tokenization incentivizes participation through rewards, allows users to bid for priority slots via proof-of-stake (PoS), and ties reputation metrics to token costs. Practical Byzantine Fault Tolerance (PBFT) ensures fault tolerance, while dynamic pricing and monetized flexibility create scalable EV-grid synergy, balancing supply-demand mismatches and attracting investors.

Haya R. Hasan, Khaled Salah, Ahmad Mayyas, Ahmad Musamih · 7 authors

Greenhouse gas emissions and carbon footprints have surged dramatically, with the transportation industry being a major contributor. While the UN aims to adopt zero-emission vehicles by 2040, the demand for electric vehicles (EVs) raises sustainability concerns about sourcing earth metals for batteries. Digital passports have emerged to track a product’s lifecycle, composition, certifications, origin, and recyclability. However, existing EV battery passport systems lack sufficient traceability, immutability, auditability, and are prone to manipulation due to their centralized nature. In this paper, we propose a decentralized blockchain-based digital passport for EV batteries using composable Non-Fungible Tokens (NFTs) to ensure traceable, tamper-proof records that promote transparency across the supply chain. Our solution enables standardized data sharing and interoperability while integrating off-chain storage for efficiency. We evaluate four cathode chemistries using ten sustainability Key Performance Indicators (KPIs) to compute an overall sustainability score per battery. We present a system architecture, smart contracts, and supporting algorithms are presented, with testing and validation in a simulated environment. A cost and security analysis confirms affordability and resilience against known attacks. Our approach offers practical value for sustainability assessments, regulatory audits, carbon footprint tracking, and circular economy initiatives by providing immutable, component-level provenance and real-time KPI updates. Limitations include simulation-based validation, lack of stakeholder testing, and scalability challenges in live deployments. While we address some of these, via Layer 2 scaling and modular smart contract design, further research is required to validate adoption in real-world EV supply chains. The smart contract code is made publicly available on GitHub.

Karim Moawad, Ahmad Musamih, Assia Chadly, Ahmad Mayyas · 8 authors

The urgency to combat climate change and reduce greenhouse gas emissions has led to increased global demand for Lithium-ion (Li-ion) batteries. Such batteries are widely used in portable electronics and electric vehicles. However, their adoption encounters challenges related to mining ethics, supply chain transparency, sustainability, and waste management. This paper proposes a blockchain-based solution that addresses these challenges in the Li-ion battery supply chain. Using the ERC-721 standard for Non-fungible tokens (NFTs), we tokenize all items/materials in the supply chain, ensuring data management, transparency, and ownership control. We integrate the Ethereum blockchain with the Interplanetary File System (IPFS) to handle NFT metadata and large-sized files, reducing storage costs and network congestion. We develop ten smart contracts (SCs) to facilitate various Li-ion supply chain functionalities, managing items/materials data and ownership. By leveraging NFTs, our solution promotes circular economy principles by facilitating secondary market trading, asset reuse, and sustainable recycling practices. We introduce a structured decision framework that empowers stakeholders to navigate operational and ethical challenges effectively. The effectiveness and practicality of the solution are demonstrated through system architecture, sequence diagrams, algorithms, and testing results. Furthermore, we assess our proposed solution’s affordability, efficiency, security, and generalizability across different industries.

Karim Moawad, Ammar Hummieda, Ahmad Musamih, Khaled Salah · 5 authors

Lithium-ion batteries (LIBs) have become a cornerstone of modern technology, where they serve as the power source for a wide range of applications, including electric vehicles and renewable energy storage systems. However, rapid production growth has introduced challenges regarding end-of-life management, particularly with waste disposal, resource recovery, and environmental sustainability. Inefficient recycling often leads to valuable materials like cobalt, lithium, and nickel being discarded in landfills, which exacerbates resource scarcity and poses environmental and health risks. To address these issues, there is a critical need for more efficient, transparent, and accountable systems for the collection, recovery, and recycling of LIBs. In this paper,A blockchain and Non-Fungible Token (NFT)-based solution is proposed to enable circular recycling and material recovery. This system improves transparency, traceability, and accountability throughout the battery lifecycle. The smart contracts (SCs) source code is made publicly available on GitHub.

Jilong Song, Su Yao, Ke Xu, Kai Wang

As a distributed ledger technology, blockchain demonstrates broad prospects in battery recycling due to its decentralized, transparent, and secure characteristics. However, practical implementation faces challenges including technical barriers, cost investments, regulatory adjustments, and data privacy protection. This paper comprehensively introduces blockchain applications in battery recycling, explaining its principles, advantages, and real-world deployment. It analyzes existing problems in current recycling systems, such as data fragmentation, inefficient reverse logistics, and regulatory failures. Furthermore, blockchain-IoT integration applications, including full lifecycle data management, intelligent monitoring, and logistics optimization, are discussed. Innovative business models are proposed, such as decentralized recycling platforms, data-driven frameworks, and sharing economy models. The importance of establishing unified industry standards is emphasized, along with an outlook on future development directions. Through systematic analysis, this study offers insights for researchers and practitioners and serves as a reference for promoting sustainable development in the battery recycling industry.

Rashmi Sharma, Himani, Chetan Agrawal

No abstract is available for this record.

Ismail, Mohanad

EVs live and die by their batteries. To keep drivers safe and confident in their vehicles, we need efficient, accurate, and private ways to track each battery's SoH. But, EV labelled data is scarce, sharing raw data raises privacy flags, and big models strain on-board hardware. This thesis tackles all three problems through a two-step remedy in one shot. 1. Learn data representations without needing labels: Each car trains a small autoencoder to reconstruct its own collected sensor data after randomly hiding parts of the signal. 2. Share knowledge, not data: Instead of uploading the raw collected data, every car sends only its trained model parameters to a remote cloud server. The server aggregates parameters from all cars and sends the improved model back. Four simple questions guide our work: 1. Does this usage of unlabelled data improve the model's performance? 2. How much of the signal should be hidden to get the best representation learning? 3. What is the optimal strategy for incorporating the limited labelled data available into the model? 4. Does this aggregation of separately trained models hurt accuracy compared with a fully centralized approach? Our experiments show a 17% lower average MAE, with up to a 60% improvement in the best cases, when we make use of the available unlabelled data versus training exclusively on labelled data. Hiding 30-40% of signals strikes the balance between challenge and clarity. Finally, aggregation of models on average stays within 0.05Ah of centralized training, virtually no loss, with zero raw-data exposure. This thesis incorporates cloud computing, SSL, and FL to present a light, privacy-friendly pipeline for fleet-wide SoH estimation, evidence that unfrozen fine-tuning outshines frozen variants, the first systematic look at how masking ratio shapes battery time-series representation learning, and practical proof that sharing model weights instead of data keeps accuracy basically untouched and privacy intact.

Ndenga Lumbu Barack

No abstract is available for this record.

Lu Xiao, Yu Ping Ouyang, Qiang Lin, Yujuan Guo

No abstract is available for this record.

Gunnar Prause, Laima Gerlitz

Abstract The classical pathway of mass production followed a linear model with trashed products and wasted remaining materials at the final stage of their life cycle. Smart approaches of manufacturing and product life cycle management aim for Circular Economy (CE) models to implement sustainable business models to overcome imbalances between resource supply and demand of goods. Non-Fungible Token (NFT) solutions together with smart contracts seem to have the potential to realise such new sustainable business models in the context of CE. The study demonstrates how NFT technology can become an integral part of smart product life cycle management for batteries of e-cars. The research highlights how circular business models can be developed and implemented in the e-car sector around the life cycle management of batteries as well as how NFT technology can contribute to sustainable conceptualisation for battery recycling.

Deepika Choudhary, Kuldip Singh Sangwan, Arpit Singh

Widespread use of lead acid batteries (LABs) is resulting in the generation of million tons of battery waste, globally. LAB waste contains critical and hazardous materials, which have detrimental effects on the environment and human health. In recent times, recycling of the LABs has become efficient but the collection of batteries in developing countries is not efficient, which led to the non-professional treatment and recycling of these batteries in the informal sector. This paper proposes a blockchain-enabled architecture for LAB circularity, which ensures authentic, traceable and transparent system for collection and treatment of batteries. The stakeholders-battery manufacturers, distributors, retailers, users, and validators (governments, domain experts, third party experts, etc.)-are integrated in the circular loop through a blockchain network. A mobile application user interface is provided to all the stakeholders for the ease of adoption. The batteries manufactured and supplied in a geographical region as well as the recycled materials at the battery end-of-life are traced authentically. This architecture is expected to be useful for the battery manufacturers to improve their extended producer responsibility and support responsible consumption and production.

Xin Chen

As electric vehicles (EV) become more prevalent and advances in electric vehicle electronics continue, vehicle-to-grid (V2G) techniques and large-scale scheduling strategies are increasingly important to promote renewable energy utilization and enhance the stability of the power grid. This study proposes a hierarchical multistakeholder V2G coordination strategy based on safe multi-agent constrained deep reinforcement learning (MCDRL) and the Proof-of-Stake algorithm to optimize benefits for all stakeholders, including the distribution system operator (DSO), electric vehicle aggregators (EVAs) and EV users. For DSO, the strategy addresses load fluctuations and the integration of renewable energy. For EVAs, energy constraints and charging costs are considered. The three critical parameters of battery conditioning, state of charge (SOC), state of power (SOP), and state of health (SOH), are crucial to the participation of EVs in V2G. Hierarchical multi-stakeholder V2G coordination significantly enhances the integration of renewable energy, mitigates load fluctuations, meets the energy demands of the EVAs, and reduces charging costs and battery degradation simultaneously.

Syed Muhammad Danish, Aroosa Hameed, Ali Ranjha, Gautam Srivastava · 5 authors

The increased charging demand resulting from the rapid development of electric vehicles (EVs) poses various challenges to the stable operation of the distribution network and smart grid. Due to the stochastic EV charging behaviour, the high charging demand at the charging stations (CSs) elevates the load curve which may lead to a spatially imbalanced load demand. As such, forecasting the highly stochastic EV charging load considering an individual EV's unique charging behaviour can result in maintaining the safe operation of the grid and distribution network. Therefore, in this work, we propose Block-FeDL, a blockchain-based Federated Learning (FL) approach for EV charging load forecasting considering the private and sensitive charging information of each EV user. Thereafter, we use a Bidirectional Long Short Term Memory (BiLSTM) model within the FeDL for predicting the EV charging load patterns at each client. Moreover, instead of using a centralized server for global model aggregation, we use blockchain technology, where the model aggregation is performed in a decentralized manner and the local model parameters shared by the FL clients can be validated and securely recorded. Lastly, the results show that the Block-FeDL outperform the second-best baseline method by 95%, 96% and 77% in terms of mean square error (MSE), mean absolute error (MAE), and root mean square error (RMSE) for forecasting the EV charging load.

Xinran Li, Wei Wang, Kun Jin, Hao Gu

No abstract is available for this record.

Weijia Jin, Chenhui Li, Min Zheng

No abstract is available for this record.

Kuo-Yang Wu, Tzu-Ching Tai, Bo-Hong Li, Cheng‐Chien Kuo

Under net-zero objectives, the development of electric vehicle (EV) charging infrastructure on a densely populated island can be achieved by repurposing existing facilities, such as rooftops of wholesale stores and parking areas, into charging stations to accelerate transport electrification. For facility owners, this transformation could enable the showcasing of carbon reduction efforts through the self-use of renewable energy while simultaneously gaining charging revenue. In this paper, we propose a dynamic energy management system (EMS) for a solar-and-energy storage-integrated charging station, taking into consideration EV charging demand, solar power generation, status of energy storage system (ESS), contract capacity, and the electricity price of EV charging in real-time to optimize economic efficiency, based on a real-world situation in Taiwan. This study confirms the benefits of ESS in contracted capacity management, peak shaving, valley filling, and price arbitrage. The result shows that the incorporation of dynamic EMS with solar-and-energy storage-integrated charging stations effectively reduces electricity costs and the required electricity contract capacity. Moreover, it leads to an augmentation in the overall operational profitability of the charging station. This increase contains not only the revenue generated from electricity sales at the charging station but also the additional income from surplus solar energy sales. From a comprehensive cost–benefit perspective, introducing this solar-and-energy storage-integrated EMS can increase facility owners’ net income by 1.25 times compared to merely installing charging infrastructure.

Imran Hussain, Hafiz Ashiq Hussain, Nasim Ullah, Stanislav Mišák

Conventional centralized optimization and management approaches may not work well in an emerging and distributed energy system with a high penetration of electric vehicles and green energy sources. The usage of blockchain technology is growing as a strong competitor as it can provide this kind of market with a transparent, secure, and efficient transactional platform. Nevertheless, most energy systems usually depend on complex mathematical optimization, which is poorly incorporated into blockchain applications. Moreover, time-sensitive message dissemination requirements, resource-intensiveness, high computational load, and communication overhead of the traditional blockchain consensus mechanisms make it difficult to connect with real-time vehicular networks. Here, we employ Proof of Intelligence (PoI), a novel prosumer-centric blockchain consensus mechanism to develop a comprehensive model of trust based on commitments of supply and demand through the application of peer-to-peer energy exchange with effective and dynamic integration of renewable sources and electric vehicles both in the day ahead and real-time energy trading platforms. Additionally, the PoI smart contract is developed to seamlessly incorporate mathematical optimization with an increased level of security, scalability, throughput, and low confirmation latency of transactions achieved through the reduced effort involved in finding and confirming the optimal solution in comparison with conventional blockchain consensus mechanisms.

Alia Al Sadawi, Eiman ElGhanam, Mohamed S. Hassan, Ahmed Osman

With the increasing investments in on-the-move electric vehicle (EV) charging solutions and wireless charging lanes (WCLs), coordination of the energy requirements of mobile EVs becomes essential to ensure load balancing while maximizing demand coverage. This necessitates the development of online and mobility-aware algorithms for assigning EV-to-charging lanes. In this work, a decentralized, blockchain-based EV assignment and energy allocation system is presented. The objective of system is to coordinate the charging requirements of mobile EVs among the available WCLs within a network of EV chargers in an Internet of Electric Vehicles (IoEVs). This blockchain-based system offers higher security, transparency and immutability over traditional rule-based coordination schemes. It also offers an integrated end-to-end framework that handles user registration, authentication, lane activation and energy reporting. This is in addition to its main functionality of establishing a real-time and load-balanced EV-to-WCL assignment process that addresses the EV energy requirements within constraints of traveling distance and remaining EV energy. The proposed system is tested on the Ethereum blockchain and its security and transparency are both validated accordingly.

Alessandro Neri, Maria Angela Butturi, Henrique L. Sauer, Francesco Lolli · 6 authors

The growing demand for electric vehicles necessitates an efficient and sustainable life-cycle management of lithium-ion batteries. This work examines existent literature on digital battery passports, crucial for high-quality data for decision-making purposes, and distributed ledger technologies as transparent and efficient enablers. An hybrid BWM-TOPSIS approach is employed to rank various platforms for digital passport implementation in an automotive company. The analysis identifies Hedera as the most suitable ledger, followed by IOTA and EOS. Future research directions include empirical validation of the findings and exploring collaborative decision-making models to enhance the robustness of the selection process.

Sama Almubarak, Hasan Ibrahim, Dev Singhania, Prasad Enjeti

This paper presents an in depth study of electric energy consumption and power quality analysis in Bitcoin mining facilities in Texas. The study includes energy consumption, voltage, current, power and current harmonics analysis from measured data on both grid connected and standalone facilities (powered by flared gas). Additionally, these results are also compared to the data gathered on an identical laboratory mining machine. Since large MW range Bitcoin mining loads are termed as "flexible loads" by the grid operators, the paper discusses examples of their potential role in participating in ancillary services to help stabilize the grid. Laboratory test results on voltage ride-through of Bitcoin machines is also presented and discussed. Analysis is also included on how large Bitcoin mining facilities can earn substantial additional revenue via their participation in ancillary services. Finally experimental data collected on a 3.5 kW S19 Pro Bitcoin miner installed in the laboratory and a 2.2 MW commercial mining facilities is tabulated and discussed.