  The surging demand for new energy vehicles is driven by the imperative to
conserve energy, reduce emissions, and enhance the ecological ambiance. By
conducting behavioral analysis and mining usage patterns of new energy
vehicles, particular patterns can be identified. For instance, overloading the
battery, operating with low battery power, and driving at excessive speeds can
all detrimentally affect the battery's performance. To assess the impact of
such driving behavior on the urban ecology, an environmental computational
modeling method has been proposed to simulate the interaction between new
energy vehicles and the environment. To extend the time series data of the
vehicle's entire life cycle and the ecological environment within the model
sequence data, the LSTM model with Bayesian optimizer is utilized for
simulation. The analysis revealed the detrimental effects of poor driving
behavior on the environment.
