Blockchain Papers

Jasem M. Alostad, R. Gopi, A. Ananthi, B. Sathiya

No abstract is available for this record.

Allam Maalla, Ying Chen

No abstract is available for this record.

Ching-Chuan Luo, Cheng-En You, Ming‐Feng Yeh

Sustainable EV charging infrastructure is fragmented by proprietary applications, vendor lock-in, and weakly time-differentiated pricing, blunting its contribution to urban-mobility decarbonisation. This paper asks whether an open-protocol, super-app-mediated photovoltaic–storage charging architecture can jointly resolve these three fragmentations under deployed field conditions and what its sustainability profile then looks like. We report a campus photovoltaic–storage microgrid integrating heterogeneous EV chargers under an open, vendor-neutral charging-control protocol with super-app authentication and payment replacing dedicated charging applications and a time-differentiated tariff aligned at the meter-interval level with the underlying utility wholesale rate; the deployment is exercised through a researcher-scheduled commissioning campaign of 13 sessions designed to establish functional correctness across the operating envelope rather than to measure user behaviour. Three results emerge across cross-vendor compatibility, onboarding friction, and grid alignment. First, basic message-level OCPP compatibility is sustained across two charger vendors under a single cloud management system—in sequential single-vendor sessions—including the full charging profile up to near-rated DC peak power. Second, the super-app-mediated workflow, which requires no charging-specific application installation and no new charger-operator account, structurally eliminates the dedicated application installation and the email/SMS/credit-card verification round-trips of conventional onboarding, compressing measured first-use end-to-end interaction to 31 s; relative to reconstructed commercial-operator baselines, this is, to the best of the authors’ knowledge, an order-of-magnitude reduction rather than a controlled benchmark. Third, mid-day energy delivery aligns incidentally with the utility off-peak window, not user-driven demand shifting, while PV-displacement and BESS-discharge contributions to charging are bracketed by scenario rather than being separately metered. The paper’s contribution is therefore a replicable, policy-embedded sustainable charging architecture validated at field scale within the New Taipei Net-Zero Carbon Demonstration Site Programme, with no claim of global novelty; the same architecture is structurally positioned to convert the observed incidental grid-friendliness into a deliberate, user-facing benefit via a hardware-free mid-day-discount redesign.

Ushaa Eswaran, Vivek Eswaran, Keerthna Murali, Vishal Eswaran

This chapter examines the emerging role of decentralized finance (DeFi) as a transformative catalyst in the digitalization of electric vehicle (EV) charging infrastructure within the energy and utilities sector. While global sustainability agendas envision seamless, affordable, and interoperable charging networks to support large-scale EV adoption, existing systems remain fragmented, capital-intensive, and institutionally constrained. Ideally, charging ecosystems should enable transparent financing, efficient energy exchange, and user-centric governance. In practice, however, high deployment costs, limited grid flexibility, regulatory inconsistencies, and restricted access to investment continue to impede this vision. Building on prior research on smart grids, blockchain-enabled energy markets, and sustainable mobility frameworks, this work critically evaluates how 2 DeFi-driven models extend beyond conventional centralized approaches. Existing studies emphasize technical optimization and policy mechanisms, yet they often overlook decentralized financial governance, peer-to-peer energy trading, and tokenized infrastructure funding. Addressing this gap, the study develops an integrated conceptual model linking DeFi principles, smart grid technologies, and EV charging ecosystems. Through analytical synthesis and selected case evidence, the paper demonstrates how trustless transactions, decentralized autonomous organizations, and micropayment mechanisms can enhance financial inclusivity, operational transparency, and system scalability. By situating EV charging infrastructure within a broader digital-financial transformation paradigm, this study advances theoretical understanding and offers strategic insights for policymakers, utilities, and technology providers seeking to accelerate sustainable and resilient mobility transitions.

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.

M. Lavanya, V Thiruppathy Kesavan, G. Sathya, R. Gopi

Electric Vehicles (EVs) that use Internet of Things (IoT) networks often involve the exchange of sensitive data between vehicles, charging stations, and other infrastructure, making data security and user privacy critical concerns. Existing methods for securing data in EV IoT networks rely on centralized systems, which create a single point of failure and are vulnerable to cyberattacks, data breaches, and unauthorized access. Furthermore, these systems struggle to address privacy concerns effectively, especially regarding user location and personal information. The proposed solution introduces a Blockchain Technology-based privacy preservation framework for EV networks (BCT-PP-EV). This framework leverages blockchain's decentralized nature to provide secure, transparent, and tamper-proof data exchanges. It ensures user privacy using cryptographic techniques such as zero-knowledge proofs (ZKP) and data anonymization, allowing privacy-preserving transactions without compromising data accuracy. Blockchain's immutability guarantees the integrity of the shared data, while smart contracts automate secure and efficient interactions within the network. The proposed method enhances secure data sharing while preserving privacy across EV IoT networks. By decentralizing data storage and enabling transparent auditing, BCT-PP-EV fosters trust among stakeholders and reduces the risks of unauthorized access or data manipulation. Preliminary findings suggest that implementing BCT-PP-EV significantly improves the security and privacy of data exchanges in EV networks, providing a scalable and resilient solution for the evolving smart transportation ecosystem. Experimental results demonstrate that BCT-PP-EV achieves 94.91% secure data sharing efficiency, reduces data breaches by 92.84%, and ensures data accuracy of 91.44%. Additionally, the framework exhibits high scalability of 96.57% with increasing network nodes, while maintaining controlled latency and throughput. Although unauthorized access resistance is measured at 24.71%, indicating scope for further improvement, the overall results confirm that BCT-PP-EV provides a robust, scalable, and privacy-preserving solution for next-generation smart transportation systems.

Alaa Alqaryuti, Haya Aljaghoub, Khaled Salah, Ahmad Mayyas

The growing adoption of Proton Exchange Membrane (PEM) fuel cell electric vehicles (FCEVS) has increased the need for secure, transparent, and verifiable certification and lifecycle tracking of hydrogen-related components. Current practices rely on fragmented documentation and centralized record-keeping, which creates risks of data manipulation, incomplete maintenance histories, and limited visibility for regulators and service providers. This paper introduces a blockchain-based framework that integrates decentralized storage, oracle-driven automation, and three interoperable smart contracts to manage stakeholder registration, component certification, vehicle assembly validation, and maintenance tracking. Implemented and evaluated in an EVM-compatible environment, the system enforces strict role-based access control, generates immutable audit trails, and automates both failure-based and mileage-based maintenance triggers using real-time inputs. A gas-cost analysis demonstrates that all contract functions operate at minimal cost under current Ethereum conditions, supporting the feasibility of real-world deployment. Overall, the proposed framework improves traceability, regulatory compliance, and operational accountability by enabling near real-time verification of certification records and reducing manual audit processing steps compared to traditional document-based certification workflows. • Blockchain ensures secure, tamper-proof FCEV component traceability. • Smart contracts automate certification, assembly, and maintenance. • Oracle triggers enable real-time, failure-, and scheduled service. • Framework improves compliance, transparency, and lifecycle oversight.

N. V. Ravindhar, A. Manju, S. Murugesan, T. K. S. Rathish Babu

Electric Vehicle-to-Grid (V2G) arrangements stand at the center of bidirectional energy exchange in modern smart grids and are, however, challenged by real-time decision-making, load balancing, and the security of transaction validation. This paper has proposed an energy-efficient optimization framework based on a Bio-Inspired Deep Learning Controller using a Monarch Butterfly Optimization (MBO) algorithm with Gated Recurrent Unit (GRU) network for optimizing charging and discharging schedules across EV fleets. GRU networks forecast short-term grid demand and EV battery availability while MBO tunes the controller weights dynamically to adapt to scheduling under varying conditions. Furthermore, in order to maintain the trust over the transaction in a tamper-resistant fashion, a blockchain layer is embedded with the use of smart contracts to keep a track of authentication, pricing, and energy transfer log records for V2G. The proposed system shows charging cost reduction of 19.6%, peak load shaving efficiency of 23.2%, and forecast accuracy of 96.4%, in all mobility scenarios evaluated. The architecture also contributes to improving grid regulation response time by 28% and reducing EV queuing delay by 31%. Simulated by using MATLAB/Simulink, TensorFlow, and Ethereum-based blockchain, the architecture renders a scalable and secure framework for V2G coordination. It is noted that the findings are based on simulation, and co-simulation experiments, and the actual conditions of deployment like latency in communications, non-idealities of the hardware and regulatory factors are not factored into the analysis. Furthermore, the model facilitates real-time adaptation, strengthens grid resilience, and guides EV operation according to concurrent market conditions for energy.

Lilia Tightiz, Sufyan Danish, Hyosik Yang

No abstract is available for this record.

Jagdish Yadav, Asha Durafe, Perla Anitha, Ch.Phani Kumar · 6 authors

This paper introduces an energy-efficient, Blockchain-Based, Dual-Agent, Reinforcement Learning (BDARL) model of resilient EV-grid integrative effect. All EV energy transactions and agent decisions are validated by the blockchain layer that is integrated through a lightweight proof-of-stake consensus mechanism, and this ensures the tamper-proof functioning and decentralized trust. The proposed framework is applying to a MATLAB/Simulink-Python TensorFlow-Hyperledger Fabric co-simulation environment where the performance analysis shows a 98.8 per cent Resilience Coordination Index (RCI), a 36.7 per cent Energy Efficiency Gain (EEG), a 31.5 per cent Load Stabilization Score (LSS), and a transaction latency of 25 ms. Compared to baseline DRL and non-blockchain schedulers, BDARL offers 7.9% improvement in terms of resilience, 8.4% in terms of energy efficiency, and 14 ms better convergence, so it provides a safe, sustainable, and smart paradigm of managing next-generation EV-grid synergy.

Rong Zhao, Jiaxiang Sun, Haoran Yin, Lehao Lin · 6 authors

The quest for carbon neutrality in the 21st century has led to the rise of decentralized low-carbon energy systems as a promising solution. Blockchain technology has played a pivotal role in catalyzing this transition, with various Web3 projects exploring decentralized operational models and carbon credit markets. However, there is a notable gap in harnessing blockchain’s potential to integrate electric vehicles (EVs) into low-carbon energy systems effectively. This article addresses this gap by proposing a decentralized low-carbon EV charging system that enables transactions between individual low-carbon energy producers and EV owners. Leveraging blockchain and smart contracts, the proposed system issues low-carbon tokens to certify and incentivize environmentally conscious charging behaviors, while enabling token circulation to further promote low-carbon participation. A blockchain-based double auction mechanism is designed to ensure fair and efficient energy allocation, achieving individual rationality, incentive compatibility, and social welfare maximization. By incentivizing user engagement and ensuring fair transactions, this model paves the way for sustainable EV integration within low-carbon energy systems.

Al Mothana Al Shareef, Serap Ulusam Seçkiner

The accelerating adoption of electric vehicles (EVs) is intensifying pressure on urban power grids, particularly during evening peak hours. Existing smart-charging frameworks remain constrained by centralized control, static pricing, and limited integration of predictive intelligence. This study presents SMARGE, a hybrid AI–Blockchain smart charging platform that combines load forecasting, dynamic pricing, and cryptocurrency-based incentives to enhance decentralized EV energy management in Gaziantep Province. An ensemble of forecasting models (SARIMA, LightGBM, N-BEATS, and TFT) predicts 2026 hourly electricity demand, while an adaptive inverse-sigmoid pricing mechanism generates real-time incentives and disincentives for EV charging behavior. A fuzzy logic-based behavioral model simulates both unmanaged and managed charging across three scenarios. Results show that managed charging reduces peak load by 22.43%, shifts 67.45% of energy demand to off-peak periods, and achieves 94.86% charging fulfillment under constrained grid conditions. The blockchain layer—implemented through a custom ERC-20 token (SMARGE) on the Ethereum Sepolia testnet—enables secure, transparent, and low-cost microtransactions with an average confirmation time of 0.63 s. These findings demonstrate that tightly coupling AI forecasting with tokenized blockchain incentives can improve grid stability, lower operational costs, and enhance user autonomy in a scalable and decentralized manner. While promising, the study is limited by assumptions of synthetic user behavior and ideal communication conditions; future work will validate the platform in real-world pilot deployments and across different urban regions.

Dhivya Govindasamy, Rajarajeswari R

<div class="section abstract"><div class="htmlview paragraph">As electric vehicles adoption becomes more common, power grid operators are facing new challenges in managing the unpredictable and varying energy demands in the existing electrical infrastructure. Moreover, the cost of Electric vehicle is high when compared to fuel vehicle it has limited access to charging infrastructure along with the driving range that act as a key barrier preventing the drivers from making shift to EVs. When the EV usage integrates with blockchain, it mitigates the limitation in charging station infrastructure along with the former problem discussed. The lack of trust exists between EV owners and charging station providers can be solved through secure and transparent payment processing possible by blockchain based smart contract. Building charging station on blockchain will ease the automated payment through the use of smart contract and create more efficient EV charging network. Also, the blockchain-based charging system would enable EV owners know if they are being charged in excess and Prosumer know if they are being underpaid. The high initial cost is another prominent issue within the market place. To address this issue the introduction of sharing economy to the EV industry showcases another innovative solution that blockchain offers. The blockchain enabled sharing economy platform allows individuals to access collaboratively with the prosumer and the consumer. This provides alternative to traditional ownership while reduces individual financial barriers and maximizing electric vehicle utilization across the network. The EV users have great opportunity worldwide to take a stake in the future of EV adoption on blockchain. Therefore, this work demonstrates the sharing economy while designing, building, and customizing smart contracts for prosumers and consumers by enabling decentralized payment systems. Our research aims to develop decentralized charging electronic payment systems using blockchain and customized smart contracts to build and design the application. For blockchain Solidity programming language is used. The application displays the charging process, payment system, and charging history information.</div></div>

Yuan Chang, Tom H. Luan, Jinkai Zheng, Yinuo Li · 5 authors

The rapid adoption of electric vehicles (EVs) has created new opportunities for decentralized energy trading, where EVs can act as mobile energy providers in peer-to-peer markets. Blockchain provides a secure foundation for such systems, ensuring trust and accountability. However, its inherent transparency creates privacy risks, as it enables the tracking of trading activities. Existing privacy-preserving mechanisms typically focus on concealing payment transactions but often expose other critical interactions, such as matching coordination. To address these challenges, we proposePriVET, a privacy-preserving framework for vehicular energy trading. PriVET leverages smart contracts for trade matching and uses an enhanced Paillier encryption scheme to support encrypted comparisons, ensuring secure coordination without revealing sensitive data. Additionally, a Bloom-filter– based Geohash encoding is used to protect location privacy during spatial matching. We evaluate PriVET through both theoretical analysis and practical experiments. In a simulation environment, the transaction computation time for 100 vehicles is shown to be under 30ms, with communication overhead kept below 20KB. These results demonstrate that PriVET provides robust privacy protection while maintaining minimal overhead, making it a practical solution for real-world blockchain-based energy trading scenarios.

Pavan Ramchandra Padghan, Vikash Rajak

No abstract is available for this record.

Inam Ul Haq, Himani Uppal, Vandita Nandal

No abstract is available for this record.

Idowu Adetona Ayoade, Omowunmi Mary Longe

Electromobility requires transactive coordination that respects distribution-network limits while preserving auditability and privacy. This study presents a reproducible peer-to-peer energy trading system that integrates a network-constrained market with permissioned blockchain settlement. The market solves a convex welfare program with linearized power-flow limits and recovers nodal prices from dual variables to match bids and offers and determine clear quantities. Settlement uses Hyperledger Fabric via the Gateway API, including proposal endorsement, ordering, validation, and commit notifications. Meter evidence is hashed and, when necessary, stored with private data collections. A co-simulation harness links MATLAB/Simulink and MATPOWER for feeder dynamics and price formation with chaincode and client logic for settlement. Three case studies are evaluated: an urban microgrid, a suburban microgrid, and a mobile electric-vehicle swarm. An Ethereum testnet serves as a public-chain baseline. In the testbed, a tuned Fabric configuration sustained approximately 1.6 to 1.7 thousand transactions per second with 99th-percentile submit-to-commit latency near one second and full deadline compliance at a one-second clearing cadence. Energy delivery accuracy remained tight, Multi-Version Concurrency Control conflicts were low, and dynamic nodal prices reduced EV charging cost relative to a flat tariff while signaling congestion through predictable rent patterns. The contribution is a deployable blueprint that connects network economics to verifiable settlement, with an open repository, benchmarking artefacts, and practical targets for endorsement width, block size, and timeouts, and clear pathways to field trials, stochastic and robust clearing, zero-knowledge meter proofs, and city-scale deployment.

Caleb Price, Albert Schmidt

The adoption of emerging transport technologies-such as autonomous vehicles, electric charging infrastructure, and hyperloop systems-increasingly depends not only on regulatory approvals and corporate investment but also on the collective sense-making and knowledge validation that occurs within informal digital spaces. Online communities, including forums, social media groups, and specialized platforms, have become influential arenas where early adopters, enthusiasts, developers, and policymakers co-construct technical knowledge, debate safety standards, and shape public perceptions. However, the governance of these virtual spaces remains critically under-examined. While organizations traditionally rely on formal, top-down mechanisms for technology dissemination and risk management, online communities operate through decentralized, peer-driven dynamics that can accelerate or hinder adoption trajectories. This research investigates the governance structures-both emergent and designed-that enable or constrain knowledge exploitation within transport-focused online communities. Specifically, it examines how community mediators, platform design features, and participant norms influence the credibility, accessibility, and translation of technical knowledge into actionable insights for adoption decisions. Employing a qualitative case study approach, this study analyzes two contrasting transport technology communities: an enthusiast-driven forum for electric vehicle charging standards and a professionally oriented group discussing autonomous freight logistics. Findings are expected to contribute a governance framework that transportation organizations can leverage to engage constructively with online communities, transforming them from peripheral chatter into strategic assets for technology adoption. The research further offers practical recommendations for community managers and transport policymakers on fostering productive knowledge ecosystems that balance openness with accountability.

Koustav Kumar Mondal, Amritesh Kumar, Debasis Das

Decentralized energy trading among electric vehicles (EVs) and charging stations (CSs) still suffers from high energy consumption, low throughput, and heavy consensus overheads. We present Reputation-Aware Proof-of-Energy (RPoE), a lightweight consensus that combines an energy score (ES) and a reputation score (RS); nodes with RPoE above a threshold participate in validation, and the highest-scoring node proposes the block. To sustain participation, we introduce a budget-balanced incentive with a guaranteed participation floor and a proportional share derived from concave weights of normalized RPoE and exchanged energy; tunable parameters trade fairness for efficiency. Our security analysis provides formal guarantees of double-spend resistance, Sybil resistance (trust-authority-backed identities), liveness under bounded delays, and resilience to DDoS/eclipse through eligibility gating. On a multi-node Raspberry Pi (RPi) testbed, RPoE reduces CPU workload by 47%, bandwidth by 5%, and energy consumption by 10% relative to Practical Byzantine Fault Tolerance (PBFT), Proof-of-Stake (PoS), and Proof-of-Authority (PoA), while achieving higher throughput and lower confirmation latency. The incentive remains fair and balanced. In a 10-node study with a participation floor of 20%, Jain's Fairness Index (JFI) is 0.853 (values closer to 1 indicate more fair splits) and the Gini coefficient is 0.221 (values closer to 0 indicate more equal splits), demonstrating equitable and budget-balanced rewards that avoid dominance.

C.Madhusudhana Rao, Praveen Kumar Naidu Rayanki, Polepalli Rajeev Meenon, Salapakshi Jai Kumar · 5 authors

Massive growth of the Chinese carbon-credit market has been characterized by endemic data obscurity, certification latency, and fraud, specifically in the Passenger Cars Corporate Average Fuel Consumption and New Energy Vehicle Credit Regulation (PCFN) scheme in the automotive industry. Its present centralized management system is not transparent and has information asymmetries and is very prone to manipulation results in erroneous carbon-credit determination, inefficient dealings, and the deteriorating stakeholder confidence. This paper offers a federated blockchain-IoT information infrastructure to deal with these severe inadequacies, namely, the provision of end-to-end transparency, tamper-resistance, and autonomous functionality in managing carbon-credit. The framework uses radio frequency identification (RFID) to capture real-time emission data, delegated proof-of-stake (DPoS) consensus to provide scalable verification and uses smart contracts to provide a decentralized credit assessment and trading. Besides, an AI-based predictive analytics control is incorporated to dynamically predict credit prices and identify anomalies on distributed nodes. Experimental comparison with national automotive carbon datasets reveals that the 72.6% latency of credit verification is reduced, the 38.2% transparency of audit is increased, and the 93.5% accuracy of fraud detection is achieved rather significantly in comparison to the traditional centralized model. The suggested framework will offer a platform on which the cross-sector carbon-credit markets of China can be scaled and verified to speed up the process of the country achieving its carbon neutrality targets of 3060.

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.

Quang Huy Duong, Carlos F.A. Arranz, Mao Xu, Li Zhou · 5 authors

The rapid transition to electric vehicles has intensified challenges in electric vehicle battery (EVB) closed-loop supply chains (CLSC), particularly regarding material traceability, supply chain transparency, and recycling efficiency. While decentralised technologies, particularly Web3 and Metaverse, offer promising solutions, their integration into EVB CLSC remains fragmented and insufficiently examined. We introduce an Operational Decentralisation Framework enabling a systematic analysis of centralised operations and a critical evaluation of decentralised alternatives as transformational forces. By adopting a holistic perspective, the framework equips firms with strategic guidance for transitioning from centralised structures to decentralised ecosystems. We analyse 588 academic articles and 1,168 industry documents through two advanced text mining techniques – Dynamic Latent Dirichlet Allocation and Burst Detection. Web3 and metaverse can potentially reconfigure the design, manufacturing, end-of-life diagnostics, procurement, waste management, load balancing, capacity planning, inventory management and service operations of two key areas: (1) EVB CLSC operations and (2) EVB circular energy/grid operations. We also found that while blockchain and digital twins show established applications, Web3 and Metaverse applications face significant barriers, including scalability, technology complexity, and expertise gaps, despite their great potentials. Therefore, we propose four visionary models integrating Web3, Metaverse, and AI technologies that have the potential to overcome existing barriers and enable transformative decentralisation. Extending the TOE framework, the study contributes to the theory by developing an integrated framework for evaluating decentralised technology adoption in EVB CLSCs. For practitioners, we provide actionable insights and pathways for technology implementation across different CLSC stages and guidance for addressing key adoption barriers.

Sarim Zia, Saleha Qureshi, Muhammad Zulfiqar, Arfa Ijaz

The paper discusses the economic and infrastructural challenges preventing the adoption of Electric Vehicles (EVs) in Pakistan.It focuses on key factors such as affordability, consumer preferences, and the overall readiness of the market.Based on a segment-wise comparison, the analysis reveals that four-wheeler EVs carry an initial price premium of 20 to 64 percent over internal combustion engine (ICE) vehicles, with payback periods ranging from 11 to 25 years, placing them out of reach for most middle-income consumers.In contrast, electric two-and three-wheelers-comprising more than 90 percent of registered vehicles-offer a significantly more practical and affordable pathway for mass adoption.These vehicles exhibit minimal upfront cost differences, annual operational savings exceeding PKR 62,000, and short payback periods of just 4 to 6 months, making them highly feasible in the local context.The study adopts a mixed-methods approach using national price data, vehicle registration records, and international case studies from India, Kenya, and Norway.It evaluates financing innovations such as battery leasing, concessional green loans, and carbon-credit-linked microfinance, and outlines a consumer-focused policy framework that emphasizes financial inclusion, decentralized infrastructure development, and phased implementation strategies.By aligning global lessons with Pakistan's socioeconomic and infrastructural realities, the paper offers a scalable and inclusive roadmap for accelerating EV adoption through targeted, consumer-driven solutions.

Amrendra Singh Yadav, Vijayant Pawar, Abdul Mazid

The exponential growth in automobile ownership has intensified global carbon emissions, underscoring the urgent need for sustainable transport solutions. Electric Vehicles (EVs) represent a cleaner alternative; however, their adoption in India remains limited. This paper proposes a blockchain-enabled carbon credit trading platform designed to incentivise EV adoption by converting verified charging activities into carbon credit tokens. Through smart contracts and decentralized verification, the system ensures transparency, accountability, and equitable distribution of credits. Two innovative algorithms underpin the model: the Carbon Credit Generation Algorithm, which standardizes token issuance, and the Voting Algorithm, which validates charging data through a consensus-based mechanism. Experimental results demonstrate that the proposed framework achieves up to 500 transactions per second with energy consumption as low as 0.01 kWh per transaction, significantly outperforming Proof-of-Work and Proof-of-Stake consensus models. The findings confirm that blockchain-driven mechanisms can effectively link green energy use to measurable rewards, fostering trust, scalability, and active participation in carbon-neutral mobility ecosystems.