Interior Permanent Magnet Synchronous Motor Research Articles

Hierarchical predictive optimal control for range extension of EV with ANN based torque control for IPMSM drives

This study presents a novel methodology to enhance the energy efficiency of Electric Vehicles (EVs) while maintaining dynamic stability and driving comfort, even on uneven roads, using onboard vehicle measurements. The approach involves a hierarchical control scheme that integrates a model predictive controller with a torque vectoring algorithm to optimize torque demand and accurately anticipate road-specific torque requirements. The proposed control is designed and implemented on an EV with Interior Permanent Magnet Synchronous Motors (IPMSM) on four wheel drives. The optimal torque control is realised through an Artificial Neural Network (ANN) - based motor torque control scheme. The design is validated through tests in real-world driving scenarios. In comparison with conventional methods, the proposed method shows a 37% increase in energy efficiency across different test conditions, thereby resulting in an increase in EV driving range. These advancements are realised without substantial modifications to the EV’s drivetrain, representing a significant step forward in sustainable and efficient electric mobility.

Rapid Prediction of Magnetic and Temperature Field Based on Hybrid Subdomain Method and Finite-Difference Method for the Interior Permanent Magnet Synchronous Motor

Rapid Prediction of Magnetic and Temperature Field Based on Hybrid Subdomain Method and Finite-Difference Method for the Interior Permanent Magnet Synchronous Motor

Design of adaptive speed controllers for matrix‐converter‐based interior permanent magnet synchronous motor drive systems

AbstractInterior permanent magnet synchronous motors (IPMSMs) which are driven by matrix converters have many advantages, including one‐stage power conversion, high efficiency, bidirectional power transfer, near unity input power factor, and low input current harmonics. However, the virtual DC‐link voltages of matrix‐converters vary from 0.866 to and the current commutations of matrix‐converters create serious three‐phase stator harmonic currents as well. Moreover, matrix‐converter‐based IPMSM drive systems, in general, have very large external loads, which require advanced control methods. To solve these problems, two adaptive controllers, including a model reference adaptive controller and a self‐tuning controller, are investigated in this article for matrix‐converter PMSM drive systems. From the experimental results, the proposed two adaptive speed controllers provide excellent dynamic responses, which are superior to PI speed controllers, including faster transient responses, better tracking abilities, and greater robustness. As a result, this proposed matrix‐converter‐based IPMSM drive system is very suitable in industrial applications.

Sideband Electromagnetic Vibrations in Interior PMSM With High Frequency Pulsating Injection Sensorless Control

Sideband Electromagnetic Vibrations in Interior PMSM With High Frequency Pulsating Injection Sensorless Control

Noise Reduction in an Interior Permanent Magnet Synchronous Motor through Structural Modifications

Noise Reduction in an Interior Permanent Magnet Synchronous Motor through Structural Modifications

Optimal Design of an Interior Permanent Magnet Synchronous Motor for Electric Vehicle Applications Using a Machine Learning-Based Surrogate Model

This paper presents an innovative design for an interior permanent magnet synchronous motor (IPMSM), targeting enhanced performance for electric vehicle (EV) applications. The proposed motor features a double V-shaped rotor structure with irregular ferrite magnets embedded in the slots between the permanent magnets. This design significantly enhances torque performance. Furthermore, a machine learning-based surrogate model is developed by integrating fine and coarse mesh data. Optimized using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), this surrogate model effectively reduces computational time compared to traditional finite element analysis (FEA).

Research on TOGI‐EFLL flux observer for IPMSM sensorless control

AbstractFor the purpose of enhancing the performance of interior permanent magnet synchronous motors (IPMSMs) sensorless control, a flux observer based on a third‐order generalized integrator with enhanced frequency‐locked loop (TOGI‐EFLL) is introduced in this paper. Compared with the traditional second‐order generalized integrator with frequency‐locked loop (SOGI‐FLL), the proposed TOGI‐EFLL can effectively mitigate the direct current (DC) bias stemming from non‐ideal factors, such as the inverter non‐linearities and detection errors, without introducing additional parameters. Initially, the active flux observer model and the limitations of the conventional SOGI‐FLL are presented. Subsequently, the proposed flux observer based on TOGI‐EFLL has been intensively investigated. Furthermore, the design of the damping factor and the digital implementation of the algorithm are developed to ensure seamless integration into digital systems. Finally, the effectiveness of the proposed sensorless control strategy is validated through the comprehensive experimental results.

Adaptive QSMO-Based Sensorless Drive for IPM Motor with NN-Based Transient Position Error Compensation

In commercial electrical equipment, the popular sensorless drive scheme for the interior permanent magnet synchronous motor, based on the quasi-sliding mode observer (QSMO) and phase-locked loop (PLL), still faces challenges such as position errors and limited applicability across a wide speed range. To address these problems, this paper analyzes the frequency domain model of the QSMO. A QSMO-based parameter adaptation method is proposed to adjust the boundary layer and widen the speed operating range, considering the QSMO bandwidth. A QSMO-based phase lag compensation method is proposed to mitigate steady-state position errors, considering the QSMO phase lag. Then, the PLL model is analyzed to select the estimated speed difference for transient position error compensation. Specifically, a transient position error compensator based on a feedback time delay neural network (FB-TDNN) is proposed. Based on the back propagation learning algorithm, the specific structure and optimal parameters of the FB-TDNN are determined during the offline training process. The proposed parameter adaptation method and two position error compensation methods were validated through simulations in simulated wide-speed operation scenarios, including sudden speed changes. Overall, the proposed scheme fully mitigates steady-state position errors, substantially mitigates transient position errors, and exhibits good stability across a wide speed range.

Effects of air gap eccentricity on different rotor structures for PMSM in electric vehicles

In addition to research related to static eccentricity and dynamic eccentricity examining fault and diagnostic methods in various types of motors, there are also studies conducted for motors with non-uniform air gaps similar to the condition. In these studies, improvements and changes in motor performance for such types of motors can be observed. In this study, the effects of the rotor structures determined in the study and the air gap shape, which is effective by changing the eccentricity ratio, on the motor performance of the interior permanent magnet synchronous motor designed for electric vehicle applications are examined. Besides the elliptical rotor structure, which is widely researched in dynamic eccentricity studies, these eccentric motor structures also include novel rectangular and polygonal eccentric rotor structures. Motor models with non-uniform air gap structures are designed in two dimensions and subjected to simulation and analysis studies using the finite element method. At the end of the study, along with the parameters identified for motor performance, the harmonic components of the stator current, radial air gap flux density and the output torque obtained through Fast Fourier Transform analysis have been provided.

The improvement of field-oriented control performance for double stator IPMSM based on NFC powered by dual photovoltaic solar panels

This paper presents a proposed method Neuro Fuzzy Control (NFC)-Field Oriente Control (FOC)-Space Vector Modulation (SVM) using IP controller for a five-level NPC inverter-Double Stator Interior Permanent Magnet Synchronous Motor (DSIPMSM) supplied by two photovoltaic solar panels Maximum Power Point Tracking (MPPT) Fuzzy Sliding Mode Control (FSMC). The torque generated and the magnetic flux of the DSIPMSM may be independently controlled thanks to FOC, while IP controllers are used to minimize dq axis current errors to zero. A boost converter is made up of an inductor, a capacitor, and a separate input-output connection. A MPPT approach based on the FSMC algorithm is used to extract the maximum amount of energy from the solar panel while controlling the inverter duty cycle. The NFC tool is an extremely potent instrument that bridges the gaps created by the fuzzy logic controller. The proposed method’s worth was demonstrated by the simulation results in terms of durability, decoupling between the d-q axis, and dynamic performance.

A fuzzy coefficient deep flux weakening algorithm for IPMSM without out-of-control

A fuzzy coefficient q-axis current increment flux weakening (FCCIFW) control method is proposed in interior permanent magnet synchronous motor (IPMSM) drives. The proposed FCCIFW not only simplifies the calculation of flux weakening coefficient according to the derived formula, but also avoids the saturation of current regulator. In FCCIFW, the theoretical calculation formula of conversion coefficient is derived firstly, and then the fuzzy rule base is established according to the formula. FCCIFW not only refrains the use of complex flux weakening calculation formula or fixed control parameters, but also refrains the problem of out-of-control in the process of deep flux weakening control, so as to improve the overall performance in the process of flux weakening. The results show that the proposed method has an effective and correct calculation process and results, Compared with different control methods in the operation process, it shows that the proposed method has more stable control effect, which has great application value in engineering.

Novel deadbeat direct torque and flux control for interior permanent magnet synchronous motor

Novel deadbeat direct torque and flux control for interior permanent magnet synchronous motor

Improved MTPA and MTPV Optimal Criteria Analysis Based on IPMSM Nonlinear Flux-Linkage Model

The use of interior permanent-magnet synchronous machines (IPMSMs) is prevalent in automotive and vehicle traction applications due to their high efficiency over a wide speed range. Given the high-power-density requirements of automotive IPMSMs, it is imperative to consider the effect of nonlinearities, such as saturation and cross-coupling, on the motor model. The aforementioned nonlinearities render conventional linear motor models incapable of accurately describing the operating characteristics of the IPMSM, including the maximum torque per ampere (MTPA) trajectory, the flux-weakening (FW) trajectory, and the maximum torque per volt (MTPV) trajectory. With respect to the linear motor model, the nonlinear flux-linkage model is gradually receiving attention from researchers. This modeling method represents the nonlinear behavior of the motor through the direct establishment of a bidirectional mapping relationship between flux-linkage and current. It is capable of naturally incorporating the effects of magnetic saturation and cross-coupling factors. However, the analysis of the current trajectory optimal criteria based on this model has not yet been reported. In this paper, the optimal criteria for the MTPA and MTPV current trajectories are analyzed based on the nonlinear flux-linkage model of IPMSMs. Firstly, the nonlinear flux-linkage model of the tested IPMSM is established by the experimental calibration method. The mathematical analytical expressions of the MTPA and MTPV optimal criteria are then analyzed by constructing and solving optimal problems with different objectives. Finally, the current command table applicable to actual motor control is constructed by calculating the current command for different operating conditions according to the optimal criteria proposed in this paper. The validity and feasibility of the optimal criteria proposed in this paper are verified through experimental tests on different operating conditions.

Modeling and Study of Different Magnet Topologies in Rotor of Low Rating IPMSMs

A study and performance analysis of magnet positions in different topology on the surface of rotor in permanent magnet synchronous motors (PMSMs) based on finite element method is observed here. A 3-phase interior PMSM is numerically simulated with ANSYS Maxwell 2018.1. Differently positioned permanent magnets improve the performance of PMSMs. Apart from handling nonlinear equations, FEM is used for simulation. ANSYS is used to analyze PMSM performance under variable conditions. This proposal examines a three-phase, 0.55 kW PMSM at 220 V, 50 Hz. Here rotor topologies of five types, namely, (i) spoke/tangential, (ii) saturable bridge / u-shape, (iii) V-shape, (iv) radial, and (v) segmented bridge permanent magnet rotor are taken for observation. The motive of this study is to analyze the performance of PMSMs in different rotor designs with different magnet positions. All topologies have been modeled and simulated with ANSYS. Each topology is compared in terms of electromagnetic and mechanical parameters. The 2D model is used to model the distribution of magnetic fields and the performance of operating parameters under transient and steady-state conditions. Magnetic flux, and efficiency are heavily influenced by the rotor shape with the volume of magnet. A study of radial force distribution and mechanical stress across rotor surface is also discussed. Motor performance is affected by the design of PMs.

Multi-objective structure optimization for interior permanent magnet synchronous motors under complex operating conditions

Multi-objective structure optimization for interior permanent magnet synchronous motors under complex operating conditions

Optimization Design of Permanent Magnet Synchronous Motor Based on Multi-Objective Artificial Hummingbird Algorithm

The interior permanent magnet synchronous motor (IPMSM) is known for its high output torque, strong overload capacity, and high power density, making it a popular choice in the electric vehicle industry. This paper proposes an improved multi-objective artificial hummingbird algorithm that combines chaotic mapping, adaptive weights, and dynamic crowding entropy. An optimization strategy that combines the Taguchi method with the Improved Multi-Objective Artificial Hummingbird Algorithm (IMOAHA), is proposed to minimize torque ripple and back electromotive force in the interior permanent magnet synchronous motor while simultaneously increasing the average torque of the motor. Taking the 8-pole 48-slot interior permanent magnet synchronous motor as an example, the optimization objectives include back electromotive force, average torque, and torque ripple. The rotor-related structural parameters are used as optimization variables. First, the Taguchi method is employed to identify parameters that significantly influence the optimization objectives. Subsequently, response surface fitting is used to establish the relationship between the optimization objectives and parameters. Finally, the multi-objective artificial hummingbird algorithm is utilized for optimization. By comparing the finite element analysis of the motor models before and after optimization, it is evident that the improved multi-objective artificial hummingbird algorithm can effectively enhance the performance of the interior permanent magnet synchronous motor.

Design and implementation of an encoder calibration system for improved resolution and accuracy in IPMSM drive with embedded software

ABSTRACT This paper presents an encoder calibration system to enhance resolution and accuracy in an interior permanent magnet synchronous motor (IPMSM) drive, along with custom embedded software. The system implements closed-loop control with the IPMSM drive, adjusting the encoder resolution through gear ratio adjustments. Communication between the human-machine interface (HMI) and the DSP’s internal 28× CPU is achieved via digital communication RS-422 interface. The embedded software on the 28× CPU processes real-time data and displays calibration information on the HMI. Firmware integration includes external analog/digital converters, comparators, digital communication interfaces, high-accuracy encoders, original encoders, and additional gear ratio adjustments, with computed compensation values stored in EEPROM. The TMS-320F-28335 digital signal processor serves as the control core, enabling encoder signal processing, embedded software execution, HMI operation, and IPMSM drive control. The experimental results validate the practicality of the proposed digitization method, demonstrating its effective applicability in industrial control systems.

Design, Analysis, and Comparison of Electric Vehicle Drive Motor Rotors Using Injection-Molded Carbon-Fiber-Reinforced Plastics

Due to their excellent mechanical strength, corrosion resistance, and ease of processing, carbon fiber and carbon-fiber-reinforced plastics are finding wide application in diverse fields, including aerospace, industry, and automobiles. This research explores the feasibility of integrating carbon fiber solutions into the rotors of 85-kilowatt electric vehicle interior permanent magnet synchronous motors. Two novel configurations are proposed: a carbon fiber wire-wound rotor and a carbon fiber injection-molded rotor. A finite element analysis compares the performance of these models against a basic designed rotor, considering factors like no-load back electromotive force, no-load voltage harmonics, cogging torque, load torque, torque ripple, efficiency, and manufacturing cost. Additionally, a comprehensive analysis of system efficiency and energy loss based on hypothetical electric vehicle parameters is presented. Finally, mechanical strength simulations assess the feasibility of the proposed carbon fiber composite rotor designs.

Analysis of electromagnetic vibration of IPM motor based on vector control for electric propulsion ships

AbstractAn overall investigation of the electromagnetic force, vibration, and average torque of the Interior Permanent Magnet Synchronous Motors (IPMSM) in the dq model for electric propulsion ships is carried out, and the electromagnetic vibration characteristics of the PMSM under the vector control strategy is explored. Firstly, the space and frequency characteristics of the electromagnetic force of the dq model motor are derived using the Maxwell stress tensor method, and the influence of the dq‐axes magnetic field on the electromagnetic force under different loads is discussed in detail. Secondly, the finite element method is used to verify the influence of dq‐axes currents on motor electromagnetic force, vibration, and average torque. Finally, the experiments are conducted on an 8‐pole 48‐slot IPMSM, and the results are consistent with the theoretical analysis and simulation results. The results indicate that the electromagnetic vibration of the PMSM for electric propulsion ships increases with the increase of the current iq and decreases with the increase of the current id. The electromagnetic vibration of the motor can be reduced by selecting the appropriate dq‐axes current under the output torque constraint.

Dynamic and Steady-state Performance of a Line-Start Interior Permanent Magnet Synchronous Motor

Dynamic and Steady-state Performance of a Line-Start Interior Permanent Magnet Synchronous Motor