TY - JOUR
T1 - An Intelligent Framework for Electric Vehicle Charging Duration Estimation Based on Deep Feature Learning and Clustering
AU - Lucia Romano
AU - Marco Bellini
AU - Paolo Greco
JF - Journal of Smart Grids, Energy Analytics and Optimization
JO - J Smart Grids Energy Anal Optim
Y1 - 2022
VL - 1
IS - 1
SP - 44
N2 - Reliable forecasting of electric vehicle (EV) charging time is vital for improving driver convenience and enabling smart, real-time charge scheduling. The present work introduces a comprehensive dynamic prediction system for EV charging duration that integrates four complementary modules: data preparation, pattern identification, baseline forecasting, and adaptive error adjustment. Raw measurements from the Battery Management System (BMS) are first cleaned and scaled to correct for missing or erroneous entries. A specially designed convolutional autoencoder tailored for EVs (EV-CAE) then extracts features across multiple time scales, after which K-Means clustering groups the sessions into characteristic charging profiles. Drawing on these profile assignments, the baseline forecasting stage computes an initial estimate of remaining charging time using past session records and the assigned cluster label. For improved resilience to changing circumstances, an adaptive correction layer is incorporated; it blends linear regression, logarithmic fitting, ratio-based scaling, and neural-network-driven refinement to update the forecast during the session continuously. Validation on authentic EV field datasets reveals that the overall architecture delivers a clear gain in forecast quality. In particular, activating the adaptive correction layer increases the coefficient of determination (R²) from 0.948 to 0.960. It maintains consistent accuracy even when charging curves vary unexpectedly or when operating in cold-weather conditions. These outcomes highlight the framework’s readiness for deployment and its engineering relevance in next-generation intelligent EV charging infrastructure.
UR - https://isespub.com/c146286582
ER -