Abstract
This study proposes an optimal design approach for an inverter-fed permanent magnet synchronous motor (PMSM) considering the variation in motor control parameters and input voltage (inverter output voltage), which vary with respect to the temperature and loading conditions, in an integrated brake system. In an integrated brake system, a quick response to load changes is crucial. Therefore, in this study, to consider the fluctuation in control variables and input voltage, the motor control parameters and input voltage were first calculated according to the operating temperature and loading condition. Subsequently, based on the calculated conditions and the approximated motor input voltage and control parameters, the objective functions corresponding to motor characteristics in transient and steady states were formulated using design-of-experiment (DOE), the moving least square method (MLSM), and the finite element method (FEM). Finally, the optimal design was performed using the genetic algorithm (GA). The validity of the proposed optimal design approach was verified by comparing its optimization results with the FEM analysis results. Thus, it was confirmed that a motor can be designed for an integrated brake system by considering the motor control parameters and motor input voltage, which vary with the driving conditions.
Highlights
Academic Editor: Andrea PagliettiRecently, with the changing automobile structure, electric devices have diversified, and their importance is increasing [1,2,3,4,5]
An optimal design process is proposed for an integrated brake system, considering the variation in motor control parameters and motor input voltage, which vary with the ambient operating temperature and loading condition
This study investigated an optimal motor design process by considering variations in the motor control parameters and motor input voltages, considering the ambient operating temperature and loading conditions
Summary
With the changing automobile structure, electric devices have diversified, and their importance is increasing [1,2,3,4,5]. Combined research on motor design and motor control to obtain a detailed analysis of a motor’s behavior has received considerable attention For this purpose, a recent comprehensive method [12,13,14,15]. Presented an improved motor control parameter modeling that considers motor performance in combination with the optimal design and a new combined optimization of the steady-state and transient-state operation of the overall system, respectively. These methods do not consider the variation in motor control parameters and input voltage, which vary with the ambient operating temperature and loading condition. The optimal solution of the multiobjective functions was obtained using the genetic algorithm (GA)
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