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September 10, 2025

Optimized real-time energy prediction for EV power stations using hybrid algorithms- A review

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Authors

PJPankaj JainRSRambir SinghSDSuman Dutta

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Overview

This review examines energy prediction methods for electric vehicles, highlighting the need for machine learning and deep learning techniques.

Key Points

  • Accurate energy prediction for EV charging stations is crucial for grid stability and optimal utilization.
  • The review emphasizes various statistical and machine learning models, such as ARIMA, SVM, and LSTM networks.
  • Challenges like data heterogeneity and computational complexity must be addressed for robust prediction systems.
  • Novel integrated models, including neural networks and optimization algorithms, enhance the effectiveness of energy prediction.

Cite This Study

Jain et al. (2025) studied this question.

synapsesocial.com/papers/68c1dd9b54b1d3bfb60fc2f7https://doi.org/10.1201/9781003593034-97
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A Comprehensive Systematic Review of Techniques for Predicting Electric Vehicle Energy Demand2025
  2. 2Electric Vehicle Charging Infrastructure Optimization Incorporating Demand Forecasting and Renewable Energy Application2025 · 4 citations
  3. 3Forecasting Energy Demand for Electric Vehicles Using Machine Learning Techniques2026
  4. 4Comparative Performance Analysis of Predictive Model Deployment for Daily Energy Demand of Electric Vehicle Charging Stations2026
  5. 5Electric Vehicle Charging Demand Prediction Using AI2026