Parallel SDA multi-step current prediction control method applied to PMSM
By adopting the parallel SDA multi-step current prediction control method in PMSM motor control, the parallelized spherical decoding algorithm is used to find the optimization, which solves the problem of high complexity of multi-step prediction control operations, and improves the control effect and prediction steps.
CN119743064APending Publication Date: 2025-04-01TIANJIN POLYTECHNIC UNIV +1
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Patent Information
- Application Number
- CN202411922037.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-25
- Publication Date
- 2025-04-01
AI Technical Summary
Technical Problem
The computational complexity of multi-step prediction control in motor control is too high, making it difficult for the controller to complete the algorithm calculation within one control cycle, affecting the control effect.
Method used
The parallel SDA multi-step current prediction control method is adopted, and Zynq's permanent magnet synchronous motor multi-step prediction control is used to optimize the system through parallel spherical decoding algorithm, reducing program execution time and increasing the number of prediction steps.
Benefits of technology
It effectively reduces the program calculation time, increases the number of prediction steps, reduces the current harmonic distortion rate of permanent magnet synchronous motor, and improves the control effect.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention discloses a parallel SDA multi-step current prediction control method applied to a PMSM, and the method comprises the steps: carrying out the calculation according to motor parameters, an encoder and data collected by a current sensor, and obtaining a counter electromotive force; performing coordinate transformation on the current under the three-phase coordinate system to obtain the current under the static coordinate system so as to construct a multi-step prediction current expression and a value function, and converting a minimum problem of the value function into a least square problem; and then according to all predicted nodes, a parallel SDA optimization algorithm is utilized to perform layer-by-layer calculation on all layers, each layer extends 0 and 1 on the basis of the nodes of the upper layer, two large branches are calculated at the same time until the last layer, and the node with the minimum output node value is taken as an optimal solution. The optimization mode of the method adopts the parallelized SDA, the characteristics of high assembly line and parallelization of the FPGA are fully utilized, the program execution time is shortened, the prediction step number is increased, and then the control effect is improved.
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