MPC-based torque control of permanent magnet synchronous motor for electric vehicles via switching optimization

被引：3
作者：
Ren B. [1 ,2 ]
Chen H. [1 ,2 ]
Zhao H. [1 ,2 ]
Xu W. [2 ]
机构：
[1] State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun Jilin
[2] Department of Control Science and Engineering, Jilin University, Changchun Jilin
来源：
Control Theory and Technology | 2017年 / 15卷 / 2期
基金：
中国国家自然科学基金;
关键词：
electric vehicle; model predictive control; Permanent magnet synchronous motor; torque optimal control;
D O I：
10.1007/s11768-017-6193-z
中图分类号：
学科分类号：
摘要：
In order to effectively achieve torque demand in electric vehicles (EVs), this paper presents a torque control strategy based on model predictive control (MPC) for permanent magnet synchronous motor (PMSM) driven by a two-level three-phase inverter. A centralized control strategy is established in the MPC framework to track the torque demand and reduce energy loss, by directly optimizing the switch states of inverter. To fast determine the optimal control sequence in predictive process, a searching tree is built to look for optimal inputs by dynamic programming (DP) algorithm on the basis of the principle of optimality. Then we design a pruning method to check the candidate inputs that can enter the next predictive loop in order to decrease the computational burden of evaluation of input sequences. Finally, the simulation results on different conditions indicate that the proposed strategy can achieve a tradeoff between control performance and computational efficiency. © 2017, South China University of Technology, Academy of Mathematics and Systems Science, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg.
引用
收藏
页码：138 / 149
页数：11
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