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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 efficient maximum-torque-per-square-ampere (MTPSA) control for the interior permanent magnet synchronous machines (IPMSMs). The objective of the MTPSA control is to find the optimal current angle, denoted as MTPSA angle, to maximize the ratio of the output torque to the square of the stator current. The proposed MTPSA control is equivalent to the maximum-torque-per-ampere (MTPA) control, but it can eliminate the need of machine parameters and thus is independent of parameter variation. This article first derives the MTPSA control objective from the machine model considering cross-coupling inductances. Then, computation-efficient gradient descent algorithm is employed to detect the MTPSA angle from the derived objective. The proposed MTPSA control is based on available measurements without the need of machine parameters and invasive signal injection, which has not been simultaneously achieved in existing MTPA controls. The proposed control is validated with simulations, experiments, and comparisons with existing approaches on a laboratory IPMSM.

This article proposes a current injection-based simultaneous stator winding and permanent magnet (PM) temperature tracking technique for dual three-phase permanent magnet synchronous machines (PMSMs). The estimation models involving winding and PM temperatures are derived for different control strategies with the cancelation of inductances. To improve the tracking performance, a Kalman filter is used for simultaneous winding and PM temperature estimation. Compared with the existing methods, the proposed simultaneous winding and PM temperature estimation technique is independent of the voltage-source nonlinearity effect and is applicable to various machine operating conditions. The main features of the proposed method are underscored by the cancelation of inductance and the elimination of the need for a lookup table. The test results on a laboratory dual three-phase PMSM are used to validate the proposed method under different speed and torque 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.

Developing a permanent magnet synchronous machine (PMSM) for direct-drive electric vehicle (EV) has challenges such as obtaining high torque density and low torque ripple. The PMSM should have high pole numbers owing to low-speed operation, thereby increasing the use of rare earth magnets and cost. Therefore, in this article a consequent pole (CP) rotor topology is proposed in which the permanent magnet (PM) volume is reduced when compared with conventional surface PMSM (SPMSM). However, replacing south poles in an SPMSM with induced steel poles can increase torque ripple and reduce torque density. In order to improve torque density in a CP PMSM, structural modifications such as multilayer windings and non-ferromagnetic barriers have been proposed in the literature. These modifications increased the torque density while increasing the torque ripple. Therefore, this article proposes a novel two-level optimization method based on gradient descent algorithm, to address the challenges of improving torque density and reducing torque ripple simultaneously in a CP PMSM. Initially, an expression for the magnet pole arc angle is derived for CP PMSM based on magnetic equivalent circuit. A two-level optimization is performed on a baseline CP PMSM to determine the optimal magnet pole arc. The torque production and torque ripples of the optimized design are validated by simulation and experimental results.

Accurate determination of losses and parameters in wide speed, torque, and temperature conditions in interior permanent-magnet synchronous motor (IPMSM) used in electric vehicles (EVs) enables improved modeling of torque and efficiency, thus leading to enhanced design and control performance. This article develops a novel and non-invasive method toward the determination of machine parameters such as stator resistance, inductances, and PM flux linkage by considering the effects of saturation, cross-saturation, time harmonics, and temperature. The fundamental and harmonic losses are determined and their effects on the parameters are also incorporated. A coupled analytical and experimental procedure that involves solving the mathematical models for parameter, loss, and temperature determination using online terminal measurements has been developed. A lumped parameter thermal network (LPTN) model has been used to derive the stator core temperature, and the fundamental and harmonic copper and core losses have been solved considering the effects of the operating temperature. The effect of time harmonics is also included in the loss models. The results from the improved PMSM model using the derived parameters and the accuracy of the results from the developed method have been validated through experimental investigations on a laboratory traction IPMSM prototype.

The accurate control of interior permanent magnet synchronous machine (IPMSM) and drive in electric vehicle applications is vital for achieving superior performance over a wide range of speeds and loads. Many control methods such as loss minimization and maximum efficiency (ME) have been developed to improve the efficiency of the motor–drive, by mainly considering the controllable fundamental losses. This article includes the effect of stator harmonic iron losses caused primarily by inverter sideband time harmonics that contribute to a significant amount of controllable electrical losses in IPMSMs. The sideband harmonic iron losses have been analytically modeled using a novel dq –axis model incorporating harmonic iron loss resistance. Subsequently, the harmonic iron losses have been included in an offline procedure used to determine optimal current advance angle for increased motor efficiency. The improved IPMSM losses and subsequently, the analytical efficiency models have been derived by considering varying motor parameters due to saturation and cross–saturation effects. The accuracy of the developed model and the improved ME control using the optimal current angle have been validated using numerical simulations and experimental investigations on a laboratory IPMSM.

This article proposes improved mathematical models for torque and system efficiency used toward obtaining accurate current advance angle for maximizing the efficiency of an interior permanent magnet (IPM) synchronous motor. First, improved torque and efficiency calculation procedure that consider the effects of parameter variations, such as inductance, stator resistance and PM flux linkage simultaneously, and motor and inverter losses, have been developed from a combination of analytical models and practical experiments. Subsequently, an offline search procedure has been utilized to determine the optimal current angle using the improved dq -axis-based models. The novelty of the efficiency model is that the method uses preliminary noninvasive experimental tests to consider the saturation and temperature effects simultaneously and successfully determine the relationship between stator and rotor temperatures by using only controller command voltages and currents. Experimental investigations are performed on a laboratory IPM for validating the developed control method through interpolation of improved look-up tables with the derived current angle values for varying speed, torque, and temperature conditions. The effectiveness of the proposed method in improving efficiency is also verified and compared with maximum efficiency and maximum torque per ampere methods using experimental sweep tests.

Rotor magnet condition is important to maintain a stable permanent magnet synchronous motor (PMSM) operation. In this paper, Vold–Kalman filtering order tracking (VKF-OT) and dynamic Bayesian network (DBN) are employed for the real-time rotor demagnetization detection from the torque ripple. First, a torque ripple model of the PMSM considering electromagnetic noise is proposed, and the torque variation is studied to determine the effect of the demagnetization on the torque ripple, which indicates that it is feasible to detect the magnet demagnetization by analyzing the torque ripple. Then the torque is processed by wavelet transform to eliminate the electromagnetic disturbances. Second, the VKF-OT is introduced to track the order of the torque ripple of the PMSM to extract the torque ripple characteristics as the feature reflecting changes in magnet status. Third, the feature is employed to train the DBN for the rotor magnet demagnetization detection and prediction during motor operation. The proposed approach is a noninvasive and an online method that can be embedded in the physical motor controller. The validation results demonstrate that this method can detect the uniform demagnetization over a wide motor speed range.

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.

Induction machines are a popular choice for tractive applications due to inherent cost savings and performance benefits driving industry to search for an optimal rotor bar design. Induction machines suffer from low torque densities due to larger size and increased losses incurred in the rotor bars making these the performance objectives to be improved through optimization. Communicating through objective functions (OFs), a performance model to rapidly evaluate design parameters coupled with genetic algorithm (GA) can be used to produce an optimal rotor bar; however, conventional OF modeling may introduce function bias or complex coefficient calculations leading to dominated objectives, stalling and premature convergence leading to an unoptimized solution. In this paper, the rotor bar of a squirrel cage induction machine (SCIM) is modeled by a permeance based equivalent circuit model (ECM) creating a link between the rotor slot geometry and equivalent circuit parameters. The model considering skin and slotting effect as well as slot, zigzag, tooth top and overhang leakage reactance effects coupled with a multi- objective GA through novel hyperbolic tangent based OFs to optimize the rotor bar geometry. The optimal rotor bar shape proposed offers increased output torque and reduced total machine losses resulting in a higher operating efficiency.

As a computationally efficient tool for the machine’s steady–state performance prediction, equivalent circuit model (ECM) of induction machines (IMs) has been an established option in literature. The results and performance predictions obtained from ECM are significantly affected by: (i) the leakage reactances as the function of the geometry of the machine’s rotor and stator slots (ii) the skin, proximity, and slotting effects and (iii) the saturation of the core. Simultaneous consideration of these effects has been ignored in conventional ECM of IMs for simplicity. In this paper, a novel permeance-based ECM is proposed and developed based on the dimensions of the stator and rotor slots to simultaneously incorporate leakage zig–zag, tooth top and overhang reactances into modeling steps. Saturation, slotting, proximity and skin effects are also fully taken into account to improve the accuracy of the modeling and performance prediction compared to the conventional ECM. Finite element analysis is used to verify the accuracy of the proposed ECM when compared to the conventional ECM based on the steady state performance characteristics such as torque, electromagnetic loss, and efficiency predictions.

Weight, torque, and efficiency of induction machines (IMs) are directly affected by their stator winding configuration. To evaluate this, this paper presents the electromagnetic (EM) performance comparison of four squirrel cage IMs using different winding configurations, namely, integral slot distributed winding (ISDW), fractional slot concentrated winding (FSCW), integral slot concentrated winding (ISCW) and integer slot concentric winding (ISCW2). The same active volumes with identical electric and magnetic loading constraints were assigned for all IMs with the same materials. The weight, torque, EM losses, and efficiency values in both maximum torque per ampere (MTPA) and field weakening regions were assessed. The results indicate that the ISCW2 IM possessed the best overall performance and characteristics in terms of torque, torque density and efficiency in a wide speed range among the investigated IMs; except its lower developed torque compared to the ISDW IM in MTPA region. To resolve this issue, a winding layout optimization was carried out via a winding function-based analysis to improve the torque performance of the ISCW2 IM in MTPA region as well.

Asymmetrical star-delta winding interior permanent magnet synchronous motor (IPMSM) is introduced as a capable option in supporting higher torque and lower torque ripple characteristics compared to the symmetrical star-delta winding IPMSM. This is at the expense of having higher radial electromagnetic (EM) force and potential vibration-related concerns including high acceleration. EM force and vibration reduction in the asymmetrical star-delta winding IPMSMs have not been well addressed in the literature so far. In order to improve the EM force and acceleration characteristics of the asymmetrical star-delta winding IPMSM while keeping its developed torque within the desired ranges, various stator and rotor geometrical parameters are defined and are changed individually. A sensitivity analysis is utilized to introduce the most effective geometrical design variables for the highlighted objectives. The reduction in the EM force, through the Maxwell-Stress tensor method, and the acceleration on the outer surface of the motor housing of the improved asymmetrical star-delta winding IPMSM structure over a base asymmetrical star-delta winding IPMSM model are investigated and reported via EM and structural simulations.

Integrated battery charging (IBC)—multiplexing the motor windings as line inductors for charging electric vehicle battery packs—can improve the onboard charging capability without increasing the weight and cost. However, during the charging operation, currents flowing in the stator winding definitely generate a magnetic field, which may demagnetize the permanent magnets (PMs) in the PM traction motors. In this paper, the demagnetization effects of IBC current on magnets in interior PM machines are compressively investigated. In this paper, a recursive algorithm to update the PM magnetization states by using a parallelogram hysteresis model at different demagnetization levels is applied. The PM temperature is also considered for establishing this model. By coupling this algorithm to the finite element analysis, the demagnetization transit at different demagnetization levels can be assessed. By decomposing the flux density of each node within the magnets along its magnetization direction, irreversible demagnetization can be accurately evaluated. Impacts from both the pulsating and rotating demagnetization magnetic fields during the IBC operation are assessed and compared.

Emerging demands in sustainable energy and power conversion applications are calling for high frequency and high efficiency switching devices. Gallium nitride (GaN) as one type of wide band...

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 (PM) synchronous machines (PMSMs) with concentrated windings (CW) exhibit high content of space harmonics leading to non–sinusoidal distribution of PM flux linkage and phase inductances in addition to the non-sinusoidal wave shape of the induced electromotive force. The ideal single reference frame-based PMSM model considers these parameters to be sinusoidal and does not include the effect of harmonics. Hence, computation of electromagnetic torque using ideal model can lead to deviation from the actual waveform. In this paper, a novel analytical model for electromagnetic torque has been derived using multiple reference frames (MRF) incorporating non-sinusoidal aspects of CW PMSM. Initially, the PM flux linkage and inductances in abc frame are extended by incorporating higher order harmonics. Then, the extended model is transformed into dq –axis using MRF rotating at speeds of dominant harmonics in PM flux linkages and inductances, the fundamental being the electrical rotor frequency. Based on this MRF model, a comprehensive electromagnetic torque model for the CW PMSM is derived. Simulation and experiments are conducted on a CW PMSM to validate the proposed model under different operating conditions.

To prevent motor failures caused by thermal overloading, accurate knowledge of stator winding temperature is of significance. The proposed stator winding temperature tracking is a stator resistance-based estimation technique for dual three-phase permanent magnet synchronous machines. In the proposed approach, a dual DC signal-injection-based method is developed to determine winding temperature accurately, which is capable of cancelling the voltage-source inverter non-linearity effect with no interference with torque output. Meanwhile, the proposed method is not affected by magnetic saturation because of no inductance terms involved. The Kalman filter is employed to improve the performance of winding temperature estimation. Moreover, the proposed approach is independent of operating conditions and can be implemented in a standard motor drive with a minimum computational cost. The experimental results validate the proposed approach on a laboratory dual three-phase interior permanent magnet synchronous motor under various speeds and load conditions.

The 3-phase windings of interior permanent magnet synchronous machines (IPMSMs) used in electric vehicles (EVs) for traction can also be utilized for charging a battery. This integrated charging technology eliminates the on-board charger, leading to a significant reduction in the overall weight and cost of the EV. However, during integrated charging, the induced magnetic fields across the IPMSM windings are unbalanced, which could lead to addition of harmonic current components at the battery side, demagnetization, noise, and vibrations. This paper provides a novel design solution by implementing asymmetrical damper bars in the IPMSM rotor to mitigate unbalanced magnetic fields during integrated charging, and, thus, overcome the aforementioned issues. However, the bars introduced could affect the useful torque production of the machine during traction. Therefore, a magnetic equivalent circuit model based differential evolutionary algorithm is proposed and implemented to optimize the IPMSM rotor structure with dampers to achieve balanced magnetic fields during integrated charging operation and satisfactory traction performance. A comprehensive performance analysis of the optimally designed traction IPMSM equipped with integrated charging capability under both operating conditions is presented in this paper using finite element analysis.

Permanent magnet synchronous machines (PMSMs) have become highly favored propulsion devices due to their exceptional merits, such as high efficiency and torque density. To operate the motor and drive in an efficient region, maximum torque per ampere control has drawn a great deal of interest among loss minimization strategies. Due to the presence of high nonlinearity and sensitivity to machine parameters, MTPA control strategy requires high robustness and reliability. This paper presents a comprehensive review of the present–day technological developments related to MTPA techniques for PMSM drives. The problems associated with MTPA techniques of PMSM, such as magnetic saturation effect, cross–coupling effect, temperature effect, are systematically summarized to outline the challenges in optimal current angle searching and stator current minimization. Additionally, in terms of machine parameter dependency, the MTPA techniques of PMSM are categorized into machine parameter–dependent and machine parameter independent. Furthermore, the recent advances of MTPA techniques are assessed, and the distinctive features of different methodologies are highlighted.

This paper investigates a novel current injection-based multi-parameter estimation technique for dual three-phase permanent magnet synchronous machine (PMSM) considering the magnetic saturation and temperature effects simultaneously. One set of currents is injected in harmonic subspace, which does not interfere with average torque production in the fundamental subspace to obtain the stator resistance under different temperature conditions. For each injection operation, the temperature effects on the resistance and permanent magnet flux linkage are considered and modelled. Meanwhile, this proposed method employs high order polynomial surface to fit the self-and cross-saturation effects. The analytical model achieved from the proposed estimation scheme satisfies both the light and heavy saturation regions. The proposed approach is validated through experimental studies on a laboratory dual three-phase interior PMSM.

This paper examines recent optimization attempts of Permanent Magnet Synchronous Machine (PMSM) design involving the utilization of innovative materials. Recent attempts at material based enhancements to PMSM design are divided into several sections based on key machine components. In the area of core design, the replacement of electromagnetic steel with new material is highlighted. With regard to winding design, several materials have been examined as replacement for the conductive copper used as the traditional winding material. The use of enhanced materials for next generation magnets is also investigated in this paper. Additionally, the utilization of novel materials for the weight intensive PMSM motor housing, cooling channels, and rotor shaft are investigated. Lastly, the utilization of enhanced materials for PMSM insulation of enhanced thermal performance is examined. Overall, this paper will highlight the strong potential of advanced materials to greatly enhance PMSM design and their viability for use in traction applications.

Harmonic currents of electric vehicle (EV) chargers could jeopardize the power quality of distribution systems and add to the transformer’s losses, thus degrading its lifetime. This paper assesses and mitigates the impacts of different EV chargers on distribution transformers and the voltage quality of distribution systems. The effect of state-of-charge (SOC) of the EV battery is considered through applying weighted arithmetic mean to accurately assess the impacts of EV harmonic currents on aging and losses of the EV interfacing transformer. The voltage quality of the IEEE 33-bus distribution system, supplying several EV parking lots, is also assessed at different charging levels using a fast-decoupled harmonic power flow. A new optimal harmonic power flow algorithm—that incorporates photovoltaic-based distribution generation units (DGs)—is developed to enhance the voltage quality of distribution systems, and elongate the lifetime of the substation transformer. The effectiveness of the proposed mitigation method is confirmed using the IEEE 33-bus distribution system, hosting several EV charging stations and photovoltaic-based DGs.

Multi–phase LLC resonant converters provide high power density, increased efficiency, good thermal distribution, and enables interleaving to drastically reduce the output current ripple. In addition, phase shedding capability at reduced output current levels allows for high efficiency over a wide operating range. However, these topologies are susceptible to component tolerances that create significant current imbalances between the phases. This paper presents a thorough evaluation of the star– connected transformer with floating star point, switched controlled capacitor and common capacitor LLC converter topologies and control techniques to mitigate the load–sharing issues instigated by the component mismatches while examining their scalability, interleaving, and phase shedding capability. The phase–shedding capability of each topology is evaluated using the first harmonic approximation (FHA) model to derive the gain characteristics of the configurations at any number of active phases. In addition, the current–sharing performance of each configuration is analyzed by modeling the multi–phase LLC resonant converter topologies with their respective phase– balancing control methodologies.

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.

A stator inter-turn fault occurring in one of the phases of a three-phase induction motor (IM) gives rise to high harmonics distortion in air-gap flux density, increased torque ripple, temperature rise in the stator windings, and mechanical vibrations due to varying magnetic forces and magnetic noise. The fault leads to a change in the electromagnetic field generated when compared to that during the normal motor operation. An incipient stator fault leads to variation of machine’s parameters, causing malfunction of the motor drive. Hence, it is of significant importance to detect the incipient fault before complete motor breakdown occurs. In this paper, a novel magnetic flux reference predictive method for control has been presented by using a harmonic compensation block in coordination with deep neural network (DNN) as a feedforward method to continue safe operation of motor after occurrence of incipient stator fault. This method takes into account both time and space harmonics discrepancies produced due to the fault. The proposed method has been implemented on a 7.5 hp IM using online observer of unhealthy conditions and compensated using DNN predictive methodology.

This paper investigates torque ripple minimization for permanent-magnet synchronous machines (PMSM), and proposes a novel analytical solution of optimal stator current design for torque ripple minimization. The proposed design is theoretically proven to be able to minimize the torque ripple with minimal machine losses. Moreover, the optimal stator current is computed from analytical expression, which is computationally efficient. Therefore, the proposed approach is applicable for torque ripple minimization under both transient state and steady state. However, existing approaches usually employ optimization algorithm to optimize the stator current, which is computationally complex and involves iterative computation, so their applicability is limited under transient state, because the optimal stator current must be adaptively updated with respect to operating conditions. Moreover, magnetic saturation is considered in the proposed approach by employing a novel linear model to model the relation between the inductance and the stator current under maximum torque per ampere (MTPA) control. In this way, the proposed analytical solution does not involve inductance, and thus, the influence of magnetic saturation can be effectively reduced. The proposed approach is validated on a laboratory PMSM drive system under both transient state and steady state.

Optimal stator current design has been widely investigated for torque ripple minimization of permanent magnet synchronous machines (PMSMs). The optimal current design requires accurate machine parameters including the permanent magnet flux and dq -axis inductances, which are varying during machine operation due to machine uncertainty. Therefore, this paper investigates how these machine parameter variations influence the optimal stator current design, and hence the torque ripple minimization performance. At first, torque ripple model-based analytical solution for optimal current design is introduced in this paper, which can theoretically reduce the torque ripple to zero. Then, machine parameter variations of a laboratory interior PMSM are tested and analyzed. It is found that the magnet flux under no load can be reduced by more than 10% from room temperature to the maximal operation temperature, and the inductance term ( $L_d$ - $L_q$ ) can be reduced by more than 50% from no load to full load. Afterwards, analytical equations are derived to quantify the resultant torque ripples due to the variations of magnet flux, dq -axis inductances, and the cogging torque. Finally, the numerical and experimental studies are conducted to investigate the resultant torque ripples under different percentages of parameter variations.

To develop a reliable permanent-magnet synchronous machine (PMSM) controller for electric vehicle application, detection of permanent-magnet (PM) demagnetization conditions is of significance. This paper explores the use of torque ripple for online PM demagnetization fault diagnosis using continuous wavelet transforms (CWT) and grey system theory (GST). First, a torque-ripple-based rotor flux linkage detection model considering electromagnetic noises is proposed, which employs CWT filtering, wavelet ridge spectrum, and torque ripple energy extraction. This model is able to reveal the torque variation and eliminate the effect of electromagnetic interferences. Second, GST is employed to facilitate the detection of demagnetization ratios and torque ripple energy pulsations caused by demagnetization. Third, a current regulation strategy is proposed to minimize the torque ripples induced by PM demagnetization, which contributes to making the approach feasible to interior PMSM (IPMSM). Furthermore, the proposed real-time irreversible demagnetization detection approach can identify the demagnetization fault under different operating conditions. The proposed approach and current regulation strategy are experimentally verified on a down-scaled laboratory IPMSM.

Rotor magnet flux linkage is critical to monitor the state of the permanent magnet in a permanent magnet synchronous machine (PMSM). This paper proposes a novel online magnet flux-linkage estimation approach by using measured speed harmonics. The proposed approach is based on the PMSM's mechanical equation, so it is not influenced by magnetic saturation, inverter nonlinearity, and changes in machine parameters. The interaction of magnet flux linkage and harmonic current can produce torque harmonic, and thus speed harmonic. Therefore, we explore the use of speed harmonic for magnet flux-linkage estimation. At first, the torque and speed harmonic models are proposed. Then, the mathematical relationship between magnet flux linkage and speed harmonic is developed. Based on this model, a novel magnet flux-linkage estimation approach is proposed, which can eliminate the influence of the cogging torque and spatial harmonics in magnet flux-linkage estimation. The proposed approach is validated on a PMSM drive system under different loads and speeds.

Thermal overload protection techniques commonly use a simplified 1st order thermal model, which does not provide accurate stator winding temperature prediction and causes frequent undesirable stoppage of the motor in the processes. This paper proposes a higher order lumped parameter thermal network model to accurately predict stator winding temperature. First, the comparison of the predicted stator winding temperature from a 1st order thermal model with a higher order thermal model is performed. Second, a comparison between the actual and the predicted stator winding temperature rise is verified for a 20 hp totally enclosed fan-cooled copper rotor induction motor that has no rotor fins on its short-circuit ring to enhance heat dissipation compared with an aluminum rotor induction motor.

Convection coefficient in the end-winding is a critical thermal parameter in Lumped Parameter Thermal Network (LPTN) model solution for an accurate motor winding temperature prediction. However, it is a challenging task to determine this convection coefficient due to complex heat and air circulation characteristics in the end-winding region. Until now, all researches focus on Totally Enclosed Fan-cooled (TEFC) Aluminum Rotor Induction Motor (ARIM) with a rotor having fins on its end-rings. But Copper Rotor Induction Motor (CRIM) has a rotor that does not have any fins on its end-rings. Hence, this research will determine convection coefficient in the end-region of Copper Rotor Induction Motor (CRIM) that has smooth rotor end. A Computational Fluid Dynamic (CFD) technique along-with a Lumped Parameter Thermal Network (LPTN) model is proposed to determine this convection coefficient. Thermal experiments on a 20-hp Copper Rotor Induction Motor (CRIM) are conducted to validate this proposed approach.

Due to high torque and power density, permanent magnet synchronous motor usually faces significant challenges for thermal stability. Moreover, it becomes difficult to keep thermal stability within the motor because the magnets that are embedded in the rotor or mounted on the rotor surface are susceptible to heat. Therefore, thermal investigation is one of the mandatory procedures during design phase of the permanent magnet synchronous motor to ensure thermal stability. In this paper, a universal lumped parameter thermal network model has been proposed for thermal design of all types of permanent magnet synchronous motors which can be used for wide range of winding configurations and any position of magnets in the rotor. The proposed analytical thermal model has been used to check the thermal performance of both newly designed interior and surface mounted permanent magnet synchronous motor prototypes for future electric vehicle application. Further, a numerical thermal model has been proposed also to check temperature distribution throughout all parts of both motors and for comparison.

In this paper, supercapacitors and grid-tie inverters are compared as means of integrating regenerative braking functionality into elevator systems. In dynamic braking, a conventional motor drive is unable to utilize energy during braking periods because it is powered by a rectifier in which energy flows in only one direction. Typically, braking resistors are used to dissipate any excess energy generated that can result in a breakdown of the device if left uncontrolled. Alternatively, supercapacitors or grid-tie inverters can be installed to the DC-link and the energy either stored for future use or fed to the power grid, thus preventing energy waste. Models for these two regenerative braking methods are constructed and simulated in the Simulink environment in order to compare their energy efficiencies under several unique elevator usage patterns. In usage patterns that allow the motor to generate energy within a long duration, the simulation results show the supercapacitor option is less of an improvement in energy efficiency than the grid-tie method due to energy flowing through two energy conversion devices. On the contrary, in usage patterns that limit regeneration within short bursts, the grid-tie inverter option is less efficient than the supercapacitor method due to output current limitations.

Stator slot shifting is widely implemented in fractional–slot wound permanent magnet synchronous machines for reduction of high spatial harmonic contents resulting in improved efficiency and flux–weakening performance. Existing method involves using twice the number of stator slots present thereby resulting in a winding topology with a coil pitch of 2. However, in this process, many slot–pole combinations, especially with odd slot numbers are neglected. Therefore, this paper proposes a procedure for stator slot shifting for n–phase fractional–slot wound machines considering all feasible slot–pole combinations. The slot–plot combinations are analyzed for performance attributes including winding factor, total harmonic distortion, minimum cogging torque and maximum torque per unit winding losses. Further, a non–dominated sorting genetic algorithm is used for optimal slot–pole selection for each phase number. The resultant machine performance characteristics of a sample best design candidate is verified using experimental data and finite element analysis.

Replacing half of the number of poles in a conventional surface permanent magnet synchronous machine (PMSM) reduces the use of rare earth materials delivering similar performance. However, in such a consequent pole configuration certain slot–pole numbers deliver high magnitudes of even order harmonics in the induced EMF waveforms leading to unbalanced magnetic force. Further, utilizing concentrated windings (CW) in the stator adds to this space harmonic content. In literature, slot–pole combinations were selected based on fundamental winding factor, cogging torque and net force on the machine, neglecting space harmonics content in inductance and induced EMF waveforms. Motivated by the drawbacks in the existing methods, in this paper, a novel inductance harmonics factor and EMF harmonics factor have been modelled using winding function method for a consequent pole multiphase CW PMSM. Furthermore, a gradient descent algorithm–based approach is implemented to optimally select slot–pole combination, with reduced inductance and EMF harmonics, for three–, five– and six–phase FSCW PMSM, with little prior knowledge about structural information of the machine. The inductance and induced EMF harmonics for optimal slot–pole combinations obtained from the algorithm are verified using finite element and experimental analysis.

Accurate and comprehensive control of interior permanent magnet synchronous machine (IPMSM) over a wide speed and load range is of paramount importance for a superior performance of the traction motor and its drive in electric vehicles. Many control methods such as loss minimization and maximum efficiency considering motor and inverter controllable losses have been developed in literature to improve the efficiency of the motor – drive. Stator harmonic iron losses contribute to a significant amount of controllable electrical losses in PMSM. In this paper, a novel dq–axis based harmonic iron loss model has been initially developed to consider the harmonic iron losses due to time harmonics from a sine pulse width modulated inverter. Subsequently, the model has been used in an offline procedure towards determining optimal current advance angle for improving the efficiency of an IPMSM. The improved PMSM loss model and subsequently, the analytical efficiency models have been derived by considering the varying motor parameters. The accuracy of the developed harmonic iron loss model has been validated using numerical simulations and experimental investigations on a laboratory 4.25 kW scaled– down traction IPMSM. The effectiveness of the control method using the improved model in increasing the efficiency has also been validated experimentally.

Accurate determination of stator flux linkage is important for advanced control techniques such as loss minimization to determine the optimal current distribution considering saturation, cross-saturation and temperature effects in the motor. In order to derive a precise flux linkage map in the direct and quadrature axes, this paper presents a method to determine the stator flux linkage using differential evolution algorithm (DE). A conventional two-axis model is modified to incorporate inverter non-linearity, magnetic saturation and cross-saturation. Based on the non-linearity, a fitness function is derived to optimize through DE and using the optimized results, flux linkage contour is estimated as a function of $d-$ and $q-$ axis currents and speed. The novelty of this paper is to estimate flux linkage including the non-linearity functions such as saturation, cross-saturation, temperature variation and dead-time distortion considering the demagnetizing current of the motor $(i_{d}\neq 0)$ and quantifying all the non-linearity factors with DE. An improved penalty function is developed to track the VSI non-linearity, saturation, cross-saturation and temperature. The effectiveness of the developed method is verified on a 4.25 kW laboratory interior permanent magnet synchronous motor (IPMSM)prototype.

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.

Inverter-fed motor drive operating an unbalanced induction motor (IM) has high harmonic content which inflicts large torque ripple on the load. Dead short circuit and incipient or partial short circuit in motor stator windings lead to asymmetry in the machine parameters. Consequently, an imbalance in the voltage supply worsens the condition deteriorating the optimal performance of the drive-based motor due to the injection of both increased time and spatial harmonics. It is of primary importance that these discrepancies are taken care of while modeling a more fault tolerant, reduced harmonics drive system. This paper proposes a novel control strategy to minimize torque ripple by considering the time harmonics produced due to imbalance in inverter voltage and parameters of the faulty IM, and the estimated space harmonics from the measured magnetic flux density in a transient magnetic phenomenon. The proposed control strategy has been implemented on an unbalanced aluminum-rotor IM with online monitoring of unhealthy conditions and feeding it to the harmonic compensation block of the drive system.

The study of the interaction between an interior permanent magnet (IPM) motor and a pulsewidth modulated (PWM) converter is increasingly becoming important, especially in the case of high-speed drives owing to the losses caused by modulation. Considering the significance of machine–converter interaction, this paper proposes a novel method to calculate magnet eddy current losses in an IPM used in traction applications by incorporating both PWM harmonics as well as rotor geometry and design parameters. The voltage harmonics from the PWM are incorporated into a series of steps in order to calculate the stator magnetomotive force (MMF) using the modified winding function theory. The rotor MMF and, subsequently, the magnet losses are computed using a magnetic circuit model incorporating the harmonics from the stator MMF as well as the flux barrier and the rotor geometry. The results have been demonstrated analytically for various cases of modulation and PWM input parameters to study the dependence of magnet losses on converter properties. The analytical results have been validated by finite-element analysis and experimental investigations.

To develop a high-performance and reliable permanent-magnet synchronous machine (PMSM) drive for electric vehicle (EV) applications, accurate knowledge of the PMSM parameters is of significance. This paper investigates online estimation of PMSM parameters and voltage source inverter (VSI) nonlinearity using current injection method in which magnetic saturation is also considered. First, a novel dc component-based current injection model considering VSI nonlinearity is proposed, which employs the dc components of dq -axis currents and voltages for PMSM parameter and VSI-distorted voltage estimation. This method can eliminate the influence of rotor position error on VSI nonlinearity estimation. Second, a simplified linear equation is employed to model the cross- and self-saturation of the dq -axis inductances during current injection, which can facilitate the estimation of the inductance variations induced by magnetic saturation. Third, a novel current compensation strategy is proposed to minimize the torque ripples caused by current injection, which contributes to making our approach applicable to both surface and interior PMSMs. Therefore, the proposed online parameter estimation approach can estimate the winding resistance, rotor flux, VSI-distorted voltage, and the varying dq -axis inductances under different operating conditions. The proposed approach is experimentally validated on a down-scaled laboratory interior PMSM prototyped for direct-drive EV powertrain.

Integrated charging technology in electric vehicles is expected to reduce the overall cost as well as the weight of the vehicle, while leading to fast charging capability in the vehicle. Understanding the above, this paper puts an effort to exclusively investigate interior permanent magnet synchronous machine (IPMSM) drive incorporating damper bars in rotor for integrated charging application in electric vehicles. First, motivation for the employment of IPMSM with damper bars for integrated charging is provided and justified. Thereafter, a novel parameter determination method based on dq -axis theory to determine the parameters of a laboratory IPMSM with dampers is proposed and experimentally validated. The determined parameters are then employed to design, control, and compare the performance of an integrated charging system incorporating an IPMSM drive with and without damper bars. The developed system is then experimentally tested under both vehicle-to-grid and grid-to-vehicle modes, and results elicited from the investigations are discussed.

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.

Integrated charging, multiplexing the motor windings for battery charging in electric vehicles, can improve the onboard fast charging capability without increasing the weight and cost. However, during the charging operation, the magnets in the traction motor have a risk of irreversible demagnetization caused by the charging currents. This paper investigates the demagnetization effects of charging current on magnets in interior permanent magnet machines. By using numerical analysis and circuit-coupled simulation, the demagnetization effects during integrated charging are evaluated.

Current injection-based on-line parameter estimation for the permanent magnet synchronous motor (PMSM) has been widely investigated in the literature. This paper aims to investigate how different current injection and machine operating conditions influence the accuracy of this approach. In particular, the influences from factors including current injection time, the amplitude of the injected current, motor speed, load torque and stator winding temperature are investigated to understand the estimation performance. The current injection-based estimation approach is implemented on an existing traction PMSM through both simulations and experimental tests. The results will demonstrate how to select current injection conditions appropriately to ensure the estimation performance.

This paper proposes a noninvasive Kalman filter based simultaneous stator winding and permanent magnet (PM) temperature estimation approach for permanent magnet synchronous machines (PMSMs). An estimation model involving the winding and PM temperatures is firstly derived from the machine model with machine inductances being cancelled. Thus, the winding and PM temperatures can be directly estimated from the measurements available in the drive system by using the derived model without the need of inductances. To improve the estimation performance, a state-space model is developed from the derived model and Kalman filter is employed for simultaneous winding and PM temperature estimation. Compared with existing approaches, the proposed approach is noninvasive and independent from machine inductance variation and it is able to provide accurate estimation of winding and PM temperature simultaneously. The proposed approach is validated on a laboratory PMSM drive system.