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This is a Quantitative Study study.

September 20, 2025EnergiesOpen Access

State of Charge Prediction for Li-Ion Batteries in EVs for Traffic Microsimulation

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Novel framework predicts state of charge in electric vehicles from traffic data, suggesting efficiency improvements.

The model predicts state of charge (SOC) with R2 = 0.86, improving energy management in electric vehicles.
Trained on 87,000 observations under various temperatures, it utilizes four key inputs for accurate predictions.
Analysis applied to traffic simulations generates SOC distributions, demonstrating potential for energy-saving interventions.
The approach reduces reliance on costly sensors, enabling better traffic management and planning for charging infrastructure.

Maksymilian Mądziel (2025) studied this question.

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