In position sensorless positioning servo systems, the parameter mismatch between interior permanent magnet synchronous motors (IPMSMs) and a position controller and/or a position estimator due to thermal variation and aged deterioration has not been sufficiently investigated. This paper proposes a convolutional integration-based secondorder differential calculation to identify the parameters of IPMSMs for a high-performance positioning servo system in an adaptive scheme. In addition, we propose a high-frequency voltage injection strategy considering the trade-off between acoustic noise suppression and estimation performance. The effectiveness of the proposed second-order differential calculation calculation method, and the high-frequency voltage injection for the acoustic noise suppression is verified experimentally.
Position-sensorless positioning control system of interior permanent magnet synchronous motors (IPMSMs) has been energetically researched for high reliability and cost reduction. To achieve fast response of positioning servo systems, accurate parameters of IPMSMs are required. The parameters vary due to temperature and/or ageing, which results in degradation of the positioning control performance. Thus, this study proposes a position-sensorless adaptive positioning control system for IPMSMs using the dynamic certainty equivalence principle for stable parameter identification. In addition, comb filters are used for fast estimation instead of low-pass filters. Experiments are demonstrated to validate the effectiveness and the feasibility of the proposed method. (a) High-frequency current (Δθ re ≠ 0), (b) High-frequency current (Δθ re = 0), (c) Construction of position estimator based on PLL, (d) Algorithm for amplitude computation
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