Bibliography

This section lists key references, datasets, and publications that have informed DeCharge’s product design, market assumptions, reward model, infrastructure forecasts, and overall strategic positioning. These sources provide both foundational context and ongoing validation for the development of decentralized EV infrastructure.

Each reference below contributes to one or more of the following:

  • Global EV adoption trends

  • Energy demand projections

  • Infrastructure deployment benchmarks

  • Smart grid innovation

  • DePIN theory and token economics

  • Autonomous systems and electrification use cases

Global EV Adoption & Forecasts

Charging Infrastructure Standards & Economics

  • U.S. Department of Energy - Alternative Fuels Data Center EV Charging Infrastructure Trends, 2024 afdc.energy.gov

  • European Alternative Fuels Observatory (EAFO) Datahub - Charging Point Statistics and Tariff Bands Accessed April 2025 www.eafo.eu

  • National Renewable Energy Laboratory (NREL) DC Fast-Charging Cost Study, Golden, CO, 2023 www.nrel.gov

  • Bureau of Energy Efficiency (India) EV Tariff Handbook 2025, Government of India www.beeindia.gov.in

Autonomous Systems & New Energy Demand

  • Federal Aviation Administration (FAA) Aerospace Forecast 2024-2044. Washington DC, 2024 www.faa.gov

  • World Economic Forum & Oliver Wyman The Autonomous Delivery Market 2024, Geneva, 2024 www.weforum.org

  • Narang, S. et al. Energy Demand Modelling for Autonomous Drones, IEEE Transactions on Transportation Electrification, Vol. 10(4): pp. 455-467, 2024

Energy Markets & Long-Term Outlook

  • International Renewable Energy Agency (IRENA) Innovation Outlook: Smart Charging for Electric Vehicles, Abu Dhabi, 2023 www.irena.org

  • McKinsey & Company Global Energy Perspective 2024, New York, 2024 www.mckinsey.com

  • World Bank Commodity Markets Outlook 2024, Washington DC, 2024 www.worldbank.org

  • International Monetary Fund (IMF) World Economic Outlook 2024, Washington DC, 2024 www.imf.org

Decentralization & Network Economics

These references are used not just for documentation but also to inform quarterly model updates, scenario forecasts, hardware strategy, and deployment economics.

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