{'fraction_non_alphanumeric': 0.009302325581395349, 'fraction_numerical': 0.0, 'mean_word_length': 4.926605504587156, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Estimation of Remaining Range of Electric Vehicle Using Kalman Filter

Electric vehicles have a limited driving range compared to conventional vehicles. Running out of battery energy is same as breakdown. The charging times for the EVs are also significant. Hence it is important to accurately indicate the driving range of the vehicle to the driver. In this paper a simple approach to calculate the real time driving range of the EV using Kalman estimation is implemented. Kalman filter try to provide a better estimation of the energy consumption considering the nonlinear nature of the vehicle energy consumption and noise in the measurement.