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    Disentangling EV Charging Behavior: An Integrated and Explainable Framework for Predicting Session Duration and Energy

    Disentangling EV Charging Behavior: An Integrated and Explainable Framework for Predicting Session Duration and Energy

    Dr. Meenakkshi

    Associate Professor

    meenakshi.malik@bmu.edu.in

    Every evening, across cities, thousands of people plug in their electric vehicles. Some do it as soon as they reach home. Some wait until late night. Some forget and charge only when the battery is almost empty. At first, this may look like a simple routine.But if you look closely, every charging action tells a story. And that story is not just about machines—it is about people.

    A Simple Question That Isn’t So Simple

    We started with a basic question:

    Can we predict how people charge their electric vehicles?

    It sounds easy. But the moment we looked at real data, things became complicated. Two people with the same car behaved completely differently. One charged daily. Another charged once in three days. One unplugged quickly. Another left the car connected for hours.

    That’s when we realized:

    EV charging is not just a technical problem. It is a human behavior problem.

    Listening to the Data

    Instead of forcing all users into one pattern, we decided to listen to the data. We used Artificial Intelligence to observe how people actually behave. Slowly, patterns started to appear. We could see different types of users emerging naturally—almost like personalities.

    Meet the EV Users

    From the data, four types of users stood out:

    • The one who charges every day after work
    • The one who prefers charging overnight
    • The one who drives long distances and charges less often
    • The one who plugs in and forgets, leaving the car connected for long hours

    These are not just categories. They are real habits. Real lifestyles. And suddenly, EV charging started
    to feel more human.