IPMSM Speed and Current Controller Design for Electric Vehicles Based on Explicit MPC
Author(s) -
Fang Liu,
Feng Gao,
LING LIU,
Denis Sidorov
Publication year - 2019
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2019.p1019
Subject(s) - control theory (sociology) , computer science , controller (irrigation) , model predictive control , nonlinear system , linearization , compensation (psychology) , cascade , torque , voltage , control engineering , control (management) , engineering , artificial intelligence , psychology , physics , electrical engineering , quantum mechanics , chemical engineering , psychoanalysis , agronomy , biology , thermodynamics
The difficulties in implementing the model predictive control (MPC) in interior permanent-magnet synchronous motors (IPMSMs) consist of the nonlinear behavior of IPMSMs and the computational effort required by MPC. This paper presents an IPMSM controller design method for electric vehicles based on explicit MPC (EMPC), which uses a different linearization method. The proposed controller combines the speed and current controllers and replaces the traditional cascade structure. First, the nonlinear terms in the system model are added into the control input as voltage compensation to obtain a simple linear model. Next, the proposed controller based on MPC is designed, which considers the effects of load torque and uses an increment model. Furthermore, the controller applies both current and voltage constraints. The EMPC method based on a binary search is used to accelerate the solution of the optimization problem. Finally, the simulation results show the validity and superiority of the proposed method.
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