{'fraction_non_alphanumeric': 0.014084507042253521, 'fraction_numerical': 0.0, 'mean_word_length': 5.677852348993288, '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}}
Fast Evaluation of Self-Sensing Control Capability for a Synchronous Reluctance Motor

This paper deals with the sensorless detection of rotor position of synchronous reluctance motors in the low speed operating region. In particular, the position estimation is obtained by means of an high frequency voltage signal injection. The convergence and the estimation error of all such sensorless control algorithms of reluctance synchronous motors result troublesome. In fact, they strictly depend on the current working point where they operate. In order to evaluate the self-sensing capability range, an accurate modeling of motor parameters should be required. This paper proposes an innovative solution to identify the self-sensing convergence region through a differential parameters approximation. Advantages of this method include a lower commissioning effort and a reduced computational burden maintaining accurate reliability. The new approach was validated using experimental measurements.