{'fraction_non_alphanumeric': 0.03121516164994426, 'fraction_numerical': 0.002229654403567447, 'mean_word_length': 5.414285714285715, '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}}
Comparison of State-of-Charge (SOC) estimation performance based on three popular methods: Coulomb counting, open circuit voltage, and Kalman filter

In this research, three battery models are proposed, i.e., simple battery model, Thevenin battery model, and modified Thevenin battery model. State-of-Charge (SOC) estimation based on those battery models are conducted with coulomb counting, open circuit voltage, and Kalman Filter. Simulation about false on battery capacity initialization is tested over the battery. The results show that the proposed battery modeling can accurately provide SOC estimation. On the simulation of false initialization, SOC estimation method with coulomb counting, open circuit voltage model 1 and 2 methods cannot track the true value, while Kalman Filter method can accurately provide SOC estimation and is able to correct false SOC initialization in short time.