Abstract
This paper deals with efficient operation method for the electromechanical brake (EMB). A three-phase interior permanent magnet synchronous motor (IPMSM) is applied to the EMB operation. A current controller, speed controller, and position controller based on proportional-integral (PI) control are used to drive the IPMSM. Maximum torque per ampere (MTPA) control is applied to the current controller to perform efficient control. For MTPA control, the angle β is calculated from total input current, and the synchronous frame d–q axis current reference is determined by the angle β. The IPMSM is designed and analyzed with finite element analysis (FEA) software and current control is simulated by Matlab/Simulink using a motor model designed by FEA software. The simulation results were verified to compare with experimental results that are input current and clamping force of caliper. In addition, the experimental results showed that the energy consumption is reduced by MTPA.
Highlights
The electromechanical brake (EMB) uses the rotational motion of the motor to move the caliper to exert clamping force on the brake disc
The interior permanent magnet synchronous motor (IPMSM) model designed in the previous section was used instead of the Matlab/Simulink model to account for finite element analysis (FEA) results
Matlab/Simulink is used for current control of the Maximum torque per ampere (MTPA) algorithm
Summary
The electromechanical brake (EMB) uses the rotational motion of the motor to move the caliper to exert clamping force on the brake disc. The development of the initial EMB was actively carried out in the automotive field to replace the hydraulic brake [1,2]. Due to the development of the manufacturing technology of the motor and inverter, many researches are being carried out to improve the performance of EMB. EMB control methods have been studied: clamping force control by cascade connection of position, velocity, and current controller based on PID control [3,4]; clamping force control using sliding mode controller [5]; adaptive sliding mode control using neural network to estimate disturbance [6]; estimation of clamping force considering gear friction [7]; predictive control of clamping force by rotor position due to limitation of force sensor space [8]; and observer-based sensor-less robust force control method [9]. Since the power input of inverter for EMB operation is connected to the battery system of the train, EMB requires efficient control to achieve
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