{'fraction_non_alphanumeric': 0.019230769230769232, 'fraction_numerical': 0.0, 'mean_word_length': 5.349593495934959, '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}}
An Extended Kalman Filter with Exponential Thermoelectric Measurement Model for Sensorless Surface Temperature Estimation of Li-ion Batteries

This paper proposes an extended Kalman filter (EKF) method to allocate and track the surface temperature of a lithium-ion (Li-ion) battery cell. The method employs a simple but effective system and measurement models for the temperature and voltage. The method is highly robust and has low implementation cost. The proposed method is derived using one Li-ion battery cell dataset and validated using other cells’ datasets. Results show that the method is always able to achieve convergence even when measurement contains noise and when incorrectly initialized. Derivation of the method followed by experimental verification is presented.