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Multireference frame based asymmetric six-phase interior permanent magnet motor modeling and control strategy under single open-phase fault are investigated in this article. The motor modeling under healthy operation is firstly established based on a dual dq -axis synchronous rotating frame. With this dual dq -axis frame, the motor modeling considering the magnetic saturation effect under open-phase fault has been derived. By introducing a dual-direction rotating frame, the stator current under single open-phase fault can be treated as the sum of a positive current sequence and a negative current sequence. With this dual-direction rotating frame, the two current sequences can be transformed into two dc components for fault-tolerant operation. Fault-tolerant control schemes with maximum torque per ampere for copper loss minimization and torque maximization are developed, respectively. Finally, the validity of the proposed modeling and control are evaluated by experiments under both steady and transient scenarios.

This article proposes an optimized current harmonic minimization (CHM) approach for dual three-phase permanent magnet synchronous machines (PMSMs) with consideration of inverter voltage limit. The current harmonic model is derived to analyze the dominant current harmonic components in dual three-phase PMSM drives. Dual reference frame (DRF) model is proposed to convert the current harmonics into dc components in the new DRFs, and PI controllers are employed to control voltages to minimize the dc components. This article will prove that current harmonics can be minimized by using the DRF model. Since CHM requires additional voltages, inverter voltage limit must be considered especially at high speeds. Hence, inverter voltage limit is considered to derive the theoretical control strategy, in which minimal copper loss is selected as the design objective to reduce current harmonic with limited voltage. The proposed approach is supported by theoretical analysis and proof, and it does not require inverter voltage and machine parameters. Moreover, the proposed approach is compared with an existing method to show the performance improvement and evaluated with extensive tests on a laboratory prototype under both steady-state and transient conditions.

For dual three-phase interior permanent magnet synchronous machines (DT-IPMSMs), open-phase fault (OPF) can result in significant average torque reduction and harmonics in the output torque and speed, which prevent the machines from a reliable and safe operation. Indeed, these adverse effects are mainly due to significant harmonics in the stator currents caused by OPF. This article investigates fault-tolerant control (FTC) of DT-IPMSM under OPF and proposes a computation-efficient FTC solution to maximize the average torque and minimize the fault-induced torque and speed ripples. In the proposed FTC, the open-phase model is first derived, and optimal stator currents are then derived to achieve maximized average torque and minimized fault-induced torque harmonics. The computation efficiency enables the proposed solution, the capability of FTC, under both the steady-state and transient conditions. Moreover, the proposed FTC can eliminate the harmonic current components in the torque contributing frame and, thus, reduce the harmonic losses, and nonlinear inductance maps are employed to consider magnetic saturation. The proposed FTC is compared with existing methods and evaluated with experiments on a laboratory DT-IPMSM under various operating conditions.

Comprehensive parameters testing and analysis are critical to high-performance modeling and control of permanent magnet synchronous machines (PMSMs). In this article, a novel decoupled approach for dual three-phase PMSM parameter estimation including winding resistance, machine inductances, and PM flux linkage is proposed for comprehensive parameter testing. An improved machine model considering magnetic saturation and inverter nonlinearity is proposed at first, in which a quadratic equation is employed to model the nonlinear variation of machine inductances and inverter voltage distortion is also modeled. Thereafter, a novel decoupled estimation model is proposed to decouple multiparameter estimation into four simplified estimations using least squares method. This decoupled model can effectively reduce the cross influences between parameters and improve the computation efficiency. Moreover, it is capable of dealing with massive redundant measurements for accurate and computation-efficient parameter estimations, which is especially suitable for obtaining machine parameters over a wide operation range during machine testing, such as inductance maps under different operating conditions.

Accurate temperature information is crucial to dual three-phase permanent magnet synchronous machine (DT-PMSM) drives. Therefore, this article proposes two efficient models for permanent magnet temperature estimation of DT-PMSMs. The proposed models are derived through current injection in the reference frame that does not contribute to torque production. Through current injection, the proposed models can fully explore the two sets of machine equations to cancel winding resistance and machine inductances. To improve the estimation performance, inverter nonlinearity is compensated in the first model and cancelled in the second model. In comparison to existing methods, the proposed approach is computationally efficient and robust to parameter variation, magnetic saturation, and inverter nonlinearity. Moreover, the current injection will not affect the machine torque production and control performance. The proposed estimation approach is evaluated on a laboratory DT-PMSM under various operating conditions.

This paper investigates open-phase fault modeling and fault-tolerant control (FTC) of dual three-phase permanent magnet synchronous machines (DT-PMSMs). A comprehensive fault model that considers both the permanent magnet torque and reluctance torque under the open-phase fault is proposed first. This model shows that under open-phase fault the average torque of DT-PMSM will decrease, while torque ripple will increase significantly. Then, a novel optimized FTC approach is developed based on the proposed model, in which genetic algorithm (GA) is applied to optimize the stator currents to maximize the average torque and minimize the torque ripple under open-phase fault. The proposed fault model and GA-based FTC are applicable to both surface-mounted and interior DT-PMSMs. However, existing approaches neglecting the reluctance torque are only applicable to surfaced-mounted DT-PMSMs. Moreover, the proposed approach is simple in implementation as it employs the original control structure and it is capable of smooth switching between the healthy operation and FTC without inducing noticeable torque pulses. The proposed approach is demonstrated with design examples, compared with existing one and validated with experiments on a laboratory interior DT-PMSM.

Torque ripple has been a critical issue for high-performance applications using permanent magnet synchronous machines (PMSMs). An efficient approach to minimize torque ripple is to control the stator current to follow an optimized current reference, which will produce an extra torque ripple to cancel the existing one. This paper proposes a multiple reference frame (MRF) based controller for torque ripple minimization (TRM), in which the measured speed ripple is explored as the feedback control signal. The proposed MRF-based controller consists of a TRM controller whose task is to find the optimal current reference and a current controller whose task is to control the actual current to follow the optimized current reference. In TRM controller, the control of reference current magnitude and phase angle is decoupled, and proportional integral (PI) controller is able to achieve TRM control. In current controller, MRF is adopted to convert harmonic current control into dc current control; thus, PI controller is able to achieve harmonic current control with the use of MRF. Compared with existing approaches, the proposed controller is capable of TRM under both steady-state and transient conditions. The proposed controller is experimentally evaluated on a laboratory PMSM drive system.

Permanent magnet temperature (PMT) is crucial to high-performance control and condition monitoring of permanent magnet synchronous machines (PMSMs). This paper proposes a noninvasive PMT estimation approach based on the PMSM steady-state equation. First, a linear temperature model, dependent solely on the PMT, is derived from the steady-state equation and the PM thermal model. Thus, the PMT can be directly estimated from the measurements using the derived linear model. In order to improve the estimation performance, a linear state-space model is developed based on the derived model, and the Kalman filter is employed for PMT estimation. The inverter nonlinearity is considered and compensated in the proposed model to improve the estimation performance. Compared with the existing methods, the proposed approach is noninvasive and computationally efficient. More importantly, the derived model does not involve machine parameters such as winding resistance and self and mutual inductances, and thus, the proposed approach is independent of winding temperature rise, magnetic saturation, and cross-coupling effect. The proposed approach is evaluated with extensive experiments under various speed and load conditions.

This paper explores the use of speed harmonic for accurate and fast maximum-torque-per-ampere (MTPA) control of interior permanent magnet synchronous machines (IPMSMs). A novel MTPA angle calculation approach is proposed, in which the MTPA angle is directly calculated from the phase angle of the speed harmonic that is induced by an injected harmonic current. At first, the relation between the speed harmonic and machine parameters is derived from the IPMSM model, which shows that the phase angle of the induced speed harmonic can be utilized to cancel the machine parameters in existing MTPA equation. Thus, a new MTPA equation is derived, which does not involve machine parameters for MTPA angle calculation. Compared with existing methods, the proposed approach is independent from the machine and drive nonlinearities. Moreover, the MTPA angle is directly calculated from the derived MTPA equation, so the proposed approach is fast and computationally efficient. Thus, the proposed approach is suitable for both on-line applications and building off-line lookup tables of MTPA angles for IPMSMs. The proposed approach is experimentally evaluated on a laboratory IPMSM drive system.

Torque ripple has been a critical issue in permanent magnet synchronous machines (PMSMs). After PMSMs are designed, an efficient way for torque ripple minimization is to inject an optimized harmonic current into the machine to produce an additional torque ripple to cancel existing torque ripple resulted from the imperfection of machine design and manufacturing. This paper proposes a testing-based approach for optimal harmonic current design by using the speed harmonics. In particular, two testing solutions (TS), TS-A and TS-B, are proposed. In TS-A, two test signals are injected into the machine, and the optimal harmonic current is calculated from the test signals as well as the measured speed harmonics. In TS-B, two test signals are injected and adjusted to achieve the designed objective in terms of speed harmonics, and the optimal harmonic current is calculated from only the test signals. These two solutions can find the optimal harmonic current to minimize the torque ripple with minimal machine losses. Moreover, machine parameters are not required in the optimal harmonic current design, so the proposed solutions are not affected by the machine and drive nonlinearities. Compared with existing approaches, the proposed solutions have advantages in terms of computation efficiency and simple implementation. The proposed solutions are evaluated on a laboratory PMSM drive system.

Torque ripple modeling and minimization for interior permanent magnet synchronous machines (IPMSMs) requires accurate information of the inductances, which vary nonlinearly due to magnetic saturation. However, existing approaches fail to consider the magnetic saturation and, thus, their performance are limited under different load conditions. Therefore, this paper improves the torque ripple model by considering magnetic saturation, and employs this model for the optimal current design to improve the performance of torque ripple minimization for IPMSMs under different load conditions. At first, numerical studies are performed to analyze and understand how magnetic saturation affects the torque ripples in IPMSMs. Then, a novel torque ripple model for IPMSMs is developed, in which the inductance term is replaced by exploring the machine electrical model. This improved torque ripple model is computationally efficient and it can provide fast and accurate torque ripple prediction. Based on this model, a genetic algorithm (GA)-based optimal stator current design approach is proposed to minimize the torque ripple in IPMSMs. The proposed GA-based approach can adaptively optimize the stator current under different load conditions, which can guarantee the robust performance of torque ripple minimization under different saturation levels. The proposed approach is validated through an experimental test on a laboratory IPMSM drive system.

For interior permanent magnet synchronous machines (IPMSMs), maximum torque per ampere (MTPA) control aims to find the MTPA angle to maximize the control objective (the ratio of output torque to stator current). This article proposes a novel online polynomial curve fitting technique for fast and accurate MTPA angle detection, which is motivated by the fact that the objective increases before MTPA angle and decreases after MTPA angle. This article proposes a polynomial-based objective model and identifies the polynomial parameters from a few test data for direct MTPA angle calculation. The proposed approach can avoid the time-consuming search process resulting in fast detection speed in comparison to existing search-based methods. In implementation, the current angle is set to a few test values to obtain the data for online curve fitting and MTPA angle calculation, in which there is no need of machine inductances and PM flux linkage. Moreover, the proposed polynomial model is analyzed to obtain the number of test data required for fast and accurate MTPA angle detection. The proposed approach is validated with extensive experiments and comparisons with existing methods on a laboratory IPMSM.

This paper examines two of the primary power supply architectures being predominantly used for wireless electric vehicle (EV) charging, namely the series LC (SLC) resonant and the hybrid series–parallel ( LCL ) resonant full-bridge inverter topologies. The study of both of these topologies is presented in the context of designing a 3-kW primary-side controlled stationary wireless EV charger with nominal operating parameters of 30-kHz center frequency, a range of coupling in the neighborhood of 0.18–0.26, and a parallel secondary pick-up with partial series coil compensation. A comparison of both architectures is made in terms of their design methodology, physical size, cost, complexity, and efficiency. It is found that the SLC architecture is 2.45% less costly than the LCL topology. On the other hand, it is observed that the LCL architecture achieves almost 10% higher peak efficiency at rated load and minimum coupling. The study also showed that the SLC topology suffers from poor light load efficiency, while the LCL topology maintains very high efficiency over its full range of coupling and loading. The study also revealed that the capacitor voltage stress is significantly higher in the SLC topology. Finally, it is also shown that the control complexity of the SLC architecture is higher than that of the LCL architecture because of its sensitivity to changes in the reflected secondary impedance, which result in loss of constant current source and ZVS operation unless a suitable combination of parameters are modulated by the closed-loop controller.