Roles of coercivity and remanent flux density of permanent magnet in interior permanent magnet synchronous motor (IPMSM) performance for electric vehicle applications

We used four rotor topologies of an interior permanent magnet synchronous motor (IPMSM) to investigate the effects of remanent flux density (Br) and coercivity (Hc) of permanent magnet on motor performance. Commercial strontium hexaferrite (SrFe12O19: energy product, (BH)max, of 4.62 MGOe) and Nd-Fe-B ((BH)max of 38.2 MGOe) magnets were used for the rotor designs. The same machine specifications and magnet volume keep constant, while the Hc and Br vary to calculate torque and energy efficiency with the finite-element analysis. A combination of high Hc and low Br more effectively increased maximum torque of IPMSM when the hexaferrite magnet was used. For Nd-Fe-B magnet, the same combination did not affect maximum torque, but increased energy efficiency at high speed. Therefore, the Hc value of a permanent magnet is more effective than the Br in producing high maximum torque for SrM-magnet based IPMSM and high energy efficiency at high speed for Nd-Fe-B magnet based IPMSM

Novel Design of Six-Phase Spoke-Type Ferrite Permanent Magnet Motor for Electric Truck Application

This paper proposes a 300 kW 24-slot/10-pole 6-phase stator-shifted fractional-slot concentrated winding spoke-type ferrite permanent magnet machine for electric truck applications. The proposed motor consists of a stator with dual three-phase windings positioned 75 degrees apart to reduce higher-order MMF harmonic order, and a rotor with an inexpensive and high-resistance ferrite permanent magnet in the spoke configuration. The simulated result of the stator-shifted machine is compared with a fabricated stator-shifted machine, and the results show good agreement with each other. To further reduce the torque ripple from 2.5 to 0.9% while maintaining a high maximum torque of 2980 Nm, circular voids with a diameter of 11 mm are embedded in the rotor. The proposed motor is evaluated for irreversible demagnetization, mechanical and thermal stability, and fault tolerant ability. To assess the proposed motor performance, the electric truck simulation model is constructed using MATLAB/Simulink and used to compare with the reported 12-slot/10-pole rare-earth permanent magnet-based machine. Compared to a previously reported six-phase rare-earth permanent magnet based flat-type machine, the proposed motor can save 4.3 kWh of energy with a USD 2512 lower cost while retaining a similar motor performance

Novel Design of Six-Phase Spoke-Type Ferrite Permanent Magnet Motor for Electric Truck Application

This paper proposes a 300 kW 24-slot/10-pole 6-phase stator-shifted fractional-slot concentrated winding spoke-type ferrite permanent magnet machine for electric truck applications. The proposed motor consists of a stator with dual three-phase windings positioned 75 degrees apart to reduce higher-order MMF harmonic order, and a rotor with an inexpensive and high-resistance ferrite permanent magnet in the spoke configuration. The simulated result of the stator-shifted machine is compared with a fabricated stator-shifted machine, and the results show good agreement with each other. To further reduce the torque ripple from 2.5 to 0.9% while maintaining a high maximum torque of 2980 Nm, circular voids with a diameter of 11 mm are embedded in the rotor. The proposed motor is evaluated for irreversible demagnetization, mechanical and thermal stability, and fault tolerant ability. To assess the proposed motor performance, the electric truck simulation model is constructed using MATLAB/Simulink and used to compare with the reported 12-slot/10-pole rare-earth permanent magnet-based machine. Compared to a previously reported six-phase rare-earth permanent magnet based flat-type machine, the proposed motor can save 4.3 kWh of energy with a USD 2512 lower cost while retaining a similar motor performance

Development and evaluation of a novel neural network of PMSM for electric vehicle

This thesis investigates an artificial neural network (ANN)-based field-oriented control (FOC) for a surface-mounted and an interior-mounted permanent magnet synchronous machine (SPMSM and IPMSM). The ANN was trained by using Levenberg-Marquardt and forward accumulation through time algorithm. First, the thesis examines the fundamentals of motor parameters and two aforementioned vector controls, with training algorithms, in detail. Then, the background and various algorithms of Maximum Torque per Ampere (MTPA) and flux weakening (FW) control are undertaken while the following part epitomizes an off-the-shelf component-based electric vehicle (EV) model that is constructed using MATLAB SimPowerSystems and SimDriveline. The proposed control is validated in both simulation and hardware experiment and compared with a PI-based field-oriented control. First, for SPMSM, the results of simulation and hardware experiment show that the maximum operating speed of the proposed control is improved by 48% and 3.5% compared to the PI-based control. For IPMSM, the results show that the proposed control produces less d-axis current than the latter control. Moreover, the control is implemented and simulated in electric vehicle model, which is constructed using SimPowerSystems and SimDriveline library in Simulink by the author with off-the-shelf components. The results show that the proposed controller can be a potential replacement of the existing control schemes, such as PID, fuzzy logic, or others, and provides adequate traction control in EV application (Published By University of Alabama Libraries