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This study introduces an innovative strategy to enhance electric vehicle (EV) fleet operations by combining predictive analytics and renewable energy sources. Leveraging real-world data from an active EV fleet, our method encompasses predictive maintenance, charging schedule optimization, and route planning, all empowered by advanced machine learning techniques. The results demonstrate a significant 15% reduction in greenhouse gas emissions, substantial annual cost savings exceeding $550,000, and noteworthy adaptability. This approach aligns with global sustainability targets and delivers valuable insights for fleet operators, policymakers, and researchers, promoting a more environmentally friendly and sustainable future.
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DOI: 10.1109/icsmartgrid61824.2024.10578265
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