Model-Free Hybrid Parallel Predictive Speed Control Based On Ultralocal Model of PMSM for Electric Vehicles

Conventional model predictive direct speed control (MP-DSC) has received extensive attention because of its easy implementation, fast dynamic response, and simple structure. However, weighting factor and parameter mismatch are two key factors restricting the control performance of MP-DSC. In this article, a model-free hybrid parallel predictive speed control (MF-HPPSC) based on ultralocal model is proposed to solve the above-mentioned problems. First, the multiobjective parallel predictive speed control method realizes synchronous control of speed, torque, and flux linkage without weighting factor. The original excellent dynamic response capability is guaranteed, and the steady-state performance is simultaneously enhanced. Moreover, the linear extended state observer (LESO) designed by the unique ultralocal model makes the calculation process of future state prediction without any machine parameters, and the robustness of the system is significantly improved. Finally, the simulation and experiment comparison among the conventional MP-DSC, conventional model-free control, and the proposed MF-HPPSC verified the superiority of the proposed method.

Automated summary

This article proposes a model-free hybrid parallel predictive speed control method based on ultralocal model to solve the problems of weighting factor and parameter mismatch. The method achieves synchronous control of speed, torque, and flux linkage without using weighting factor. The system's robustness is significantly improved by using a linear extended state observer designed by the unique ultralocal model.