Search Results (81)

Synchronous Reluctance Motors (SynRM) have attracted much attention due to their advantages of simple structure and low cost. However, due to factors such as magnetic saturation and temperature changes, the parameters of SynRM exhibit nonlinear characteristics. Existing Maximum Torque per Ampere (MTPA) control strategies often do not fully consider the impact of nonlinear changes in motor parameters, making it difficult to achieve accurate MTPA control and resulting in reduced motor efficiency. This article analyzes the control errors caused by the nonlinear changes in inductance of SynRM and proposes an error compensation strategy based on virtual DC signal injection MTPA control. The error expression is reconstructed to achieve error compensation and improve the accuracy of MTPA control. The effectiveness of the proposed control strategy is verified by building a simulation model and a motor experimental platform. The experimental results show that the control strategy proposed in this paper can achieve a maximum current optimization rate of 5.01% while ensuring fast system responsiveness. Full article

This paper presents explicit algebraic methods for approximating optimal $dq$-axis current references in permanent magnet synchronous motors (PMSMs) under given torque commands. The proposed approach addresses three key optimal control strategies: maximum torque per ampere (MTPA), maximum torque per voltage (MTPV), and loss-minimization control. For MTPA operation, a closed-form explicit formula is derived to approximate the d-axis current that minimizes copper losses. For MTPV operation, an analytical expression is developed to approximate the optimal current vector, effectively addressing iron losses in the high-speed region. Furthermore, a simplified formulation for loss-minimization control is proposed to enhance overall efficiency by balancing both copper and iron losses. These formulas are computationally efficient and eliminate the need for iterative numerical procedures while maintaining high accuracy. Supplementary expressions are also provided to facilitate practical implementation under current and voltage constraints. The mathematical fidelity and computational efficiency of the proposed formulas are rigorously validated through numerical simulations using representative PMSM models. The results demonstrate that the proposed explicit approximations closely match the true numerical optimal trajectories, offering a practical alternative to complex iterative methods without the need for extensive experimental characterization. Full article

Surface-mounted permanent magnet synchronous motors (SPMSMs) are widely used in high-performance electric vehicles due to their power density; however, conventional field-oriented control (FOC) relies on simplified models in which electromagnetic torque is described as a function of the quadrature current component, together with constant parameters and idealized trajectories in the $i_d-i_q$ plane, limiting adaptability and reducing efficiency and operating range under real conditions. This work introduces a flux linkage vector decomposition approach for SPMSMs, in which the permanent-magnet flux is decomposed into d- and q-axis components under core saturation and integrated into an extended field-oriented control framework. An extended FOC strategy is proposed that incorporates flux linkage vector decomposition, nonlinear magnetic saturation, cross-coupling effects, and nonlinear dependencies of electrical parameters, along with resolver angle correction and dynamic modulation index management. These enhancements modify torque and voltage trajectories by shifting the voltage-limit center and improving the definition of the MTPA, FW, and MTPV regions to better match real motor behavior, enabling performance improvements. Experimental validation on an automotive powertrain using a vehicle control unit (VCU) and precalculated lookup tables (LUTs) demonstrates improvements of up to 13.5% in low-speed torque, 13.7% in high-speed power, and efficiency gains of 4–8% across operating conditions. Full article

Permanent magnet synchronous machines (PMSMs) are widely used in high-performance drive systems. However, parasitic torque ripple remains a critical limitation, causing acoustic noise, mechanical vibration, and speed fluctuations. This study presents a compact, model-based torque control strategy for surface-mounted PMSMs (SPMSMs) that suppresses torque ripple by generating a structured current reference. Grounded in the magnetic co-energy principle, the proposed method utilizes a deterministic analytical model to compensate for cogging torque and inductance harmonics, avoiding computationally intensive iterative estimators. A primary contribution involves adapting the harmonic injection profile to varying loads and magnetic saturation levels. Comprehensive finite element analysis (FEA) co-simulations demonstrate that the proposed method reduces torque ripple by approximately 87.5% and speed ripple by over 90% at 1500 RPM compared to conventional maximum torque per ampere (MTPA) strategies. Furthermore, extended dynamic analysis confirms superior robustness during start-up, transients, and low-speed operation (100 RPM), maintaining high control authority even under deep magnetic saturation (2.0 p.u.). Performance evaluations verify that this significant enhancement in torque quality is achieved with a negligible increase in total power losses (~2.1%), presenting a computationally feasible solution for industrial embedded platforms. Full article

In response to the “carbon peak and carbon neutrality” strategy, industrial energy conservation has become increasingly important. Interior Permanent Magnet Synchronous Motors (IPMSMs) exhibit significant potential for efficient flux-weakening control due to their asymmetric rotor reluctance. However, conventional control strategies often cause instability during transitions across speed zones. This paper proposes a novel adaptive fuzzy-based smooth transition strategy to address this issue. First, a composite control framework integrating Maximum Torque per Ampere (MTPA) and leading-angle control is established to enhance flux-weakening capability. Then, within this framework, adaptive fuzzy controllers are designed for different weakening zones, incorporating a Lyapunov-based parameter adaptation mechanism for real-time compensation. Simulation results demonstrate that the proposed strategy achieves smooth switching across the entire speed range of IPMSMs. Quantitatively, it reduces speed overshoot by 5–15%, suppresses torque ripple by over 10%, and virtually eliminates switching current pikes compared to conventional methods, thereby significantly improving system dynamic performance and operational reliability. Full article

Model-based maximum torque per ampere (MTPA) control methods of interior permanent magnet synchronous motors (IPMSM) often suffer from poor robustness. To address this issue, a new MTPA control method based on current angle searching with sliding-mode extremum seeking is proposed. Based on Lyapunov’s criterion, the stability of the proposed MTPA method is proven. By analyzing the formation and switching process of a sliding-mode surface, the convergence speed and control accuracy of the proposed MTPA are derived. Compared with the conventional MTPA method, based on the sinusoidal excitation extremum search algorithm, the proposed method does not require either a sinusoidal excitation signal or high-pass and low-pass filters. The effectiveness of the proposed method is verified by experiment. Full article

This study proposes a compensation method for operating region variations in in-wheel PMSMs, which are widely used in small mobility applications such as e-scooters and e-bikes. As motor temperature increases during operation, electrical parameters such as inductance vary, leading to unstable control. To address this, a Single-Layer Backpropagation Neural Network (SLBPNN) is used to estimate inductance variations in real-time. The proposed algorithm adjusts the motor’s operating point to maintain stable performance under thermal stress. Simulation results using MATLAB 2024b confirm the model’s effectiveness by estimating inductance from voltage, current, speed, and position inputs. Experimental validation further demonstrates that the proposed method compensates for the shift in the operating region due to temperature changes, improving the overall motor efficiency. Full article

To promote energy efficiency and support sustainable electric transportation, this study addresses the challenge of real-time and energy-optimal control of permanent magnet synchronous motors (PMSMs) in electric vehicles operating under variable load conditions, proposing a novel Laguerre-based model predictive control (MPC) strategy integrated with maximum torque per ampere (MTPA) operation. Traditional MPC methods often suffer from limited prediction horizons and high computational burden when handling strong coupling and time-varying loads, compromising real-time performance. To overcome these limitations, a Laguerre function approximation is employed to model the dynamic evolution of control increments using a set of orthogonal basis functions, effectively reducing the control dimensionality while accelerating convergence. Furthermore, to enhance energy efficiency, the MTPA strategy is embedded by reformulating the current allocation process using d- and q-axis current variables and deriving equivalent reference currents to simplify the optimization structure. A cost function is designed to simultaneously ensure current accuracy and achieve maximum torque per unit current. Simulation results under typical electric vehicle conditions demonstrate that the proposed Laguerre-MTPA MPC controller significantly improves steady-state performance, reduces energy consumption, and ensures faster response to load disturbances compared to traditional MTPA-based control schemes. This work provides a practical and scalable control framework for energy-saving applications in sustainable electric transportation systems. Full article

This paper presents a comprehensive overview of permanent magnet synchronous motors (PMSMs), including their classifications, applications, and vector control strategies. It explores various control techniques, including maximum torque per ampere (MTPA), maximum current (MC), field weakening (FW), maximum torque per voltage (MTPV), sensorless control, and parameter identification, as discussed in this paper. These methods address key challenges in PMSM control, such as improving motor efficiency and accurately estimating rotor position and speed. Additionally, this paper presents the PMSM parameters due to many factors such as electric current, phase angle, saturation, and temperature. The survey findings provide a deeper understanding of PMSMs’ control strategies, aiding in the more efficient and reliable motor studies. Full article

A systematic and highly efficient current commands generator for an interior permanent magnet synchronous motor (IPMSM) in electric vehicles is proposed. This paper integrates maximum torque per ampere (MTPA), maximum power control (MPC), and maximum torque per voltage (MTPV) criteria for optimal efficiency, and systematically establishes an optimal current control commands workflow. A rapid current commands mapping technique and an automatic high efficiency of all speed range current command generator are proposed. The automatically generated commands table can be effectively applied in a motor controller to reduce the energy consumption of an electric vehicle for all operating speed range. A graphical user interface (GUI) tool for the generator, which can automatically produce the current command (look-up tables, LUT) in an Excel format, is designed. High-speed field-weakening and zero-torque cruising (ZTC) in electric vehicles are also thoughtfully considered. By using the proposed method, motor controller designers can more rapidly adjust required motor current command tables and speed up the development period. Both GUI simulation and experimental results show the effectiveness and feasibility of the proposed method. Full article

Interior-mounted permanent magnet (IPM) machines have been widely used in recent years due to their high efficiency, high torque/power densities, and so on. These machines can produce reluctance torque whereas their surface-mounted (SPM) counterparts cannot. Hence, IPMs are attractive in industrial applications that require high torque density. ${\mathrm{I}}_{\mathrm{d}}=0$ control is commonly adopted to drive permanent magnet (PM) machines, and the strategy is attractive due to its simplicity. However, although it is suitable for SPMs, adopting it in IPMs sacrifices the reluctance torque that can be obtained from the machine. Hence, it is vital to control IPMs using the maximum torque per ampere (MTPA) strategy. This paper adopts the MTPA strategy for a 4.1 kW prototype IPM machine. Test system configuration is discussed step by step by paying particular attention to potential practical issues and inspirational discussions on their solutions. The issues associated with misaligned rotor positions or whistling problems pertinent to inappropriate power conversion strategies are addressed to overcome such issues in practical IPM drives. Comprehensive discussions and extensive comparisons of well-matched simulation and experimental results of both ${\mathrm{I}}_{\mathrm{d}}=0$- and MTPA-controlled drives at different evaluation metrics will be quite insightful to achieve efficiency-optimized IPM drives. Full article

This research presents a method for improving the regenerative efficiency of interior permanent magnet synchronous motors (IPMSMs) used in traction applications such as electric vehicles. In conventional powertrain control, the maximum torque per ampere (MTPA) strategy is commonly applied in the constant-torque region. However, this approach does not account for the combined losses of both the motor and inverter. In this study, overall system efficiency is investigated, and an improved current combination is proposed to minimize total losses. The single switching method is employed in the inverter due to its simplicity and its ability to reduce inverter losses. Simulations incorporating both motor and inverter losses were performed for two driving conditions around the MTPA current point. The results show that the optimal current combination slightly deviates from the MTPA point and leads to a slight improvement in efficiency. Experimental results under the two steady-state driving torque and angular velocity conditions confirm that the optimized current combination enhances system efficiency. Furthermore, simulations based on the Urban Dynamometer Driving Schedule predict an increase in recovered energy of approximately 1%. The proposed control strategy is simple, easy to implement, and enables the powertrain to operate with highly efficient current references. Full article

In order to improve the output torque/current utilization of five-phase interior permanent magnet synchronous motor (FP-IPMSM) when running below base speed, a multi-dimensional maximum torque per ampere (MTPA) control strategy based on virtual signal injection (VSI) is proposed. Firstly, the mathematical model of FP-IPMSM containing third harmonic is derived, and the double-plane vector control is constructed. Secondly, the MTPA current is calculated according to the output torque, and the MTPA current trajectory of fundamental and harmonic planes is given. Thirdly, the dual-plane MTPA control strategy based on VSI is discussed. Finally, the effectiveness of the proposed control strategy is verified by simulation. Full article

The proliferation of electric vehicle (EV) racing competitions, such as Formula electric vehicle (FEV) competitions, has intensified the quest for high-performance electric propulsion systems. High-speed permanent magnet synchronous motors (PMSMs) for FEVs necessitate an optimized control strategy that adeptly manages the complex interplay between electromagnetic torque production and minimal power loss, ensuring peak operational efficiency and performance stability across the full speed range. This paper delves into the optimization of high-speed PMSM, pivotal for its application in FEVs. It begins with a thorough overview of the FEV motor’s basic principles, followed by the derivation of a detailed mathematical model that lays the groundwork for subsequent analyses. Utilizing MATLAB/Simulink, a simulation model of the motor drive system was constructed. The proposed strategy synergizes the principles of maximum torque per ampere (MTPA) with the flux weakening control technique instead of conventional zero direct axis current (ZDAC), aiming to push the boundaries of motor performance while navigating the inherent limitations of high-speed operation. Covariance matrix adaptation evolution strategy (CMA-ES) was deployed to determine the optimal d-q axis current ratio achieving maximum operating torque without overdesign problems. The implementation of the optimized control strategy was rigorously tested on the simulation model, with subsequent validation conducted on a real test bench setup. The outcomes of the proposed technique reveal that the tailored control strategy significantly elevates motor torque performance by almost 22%, marking a pivotal advancement in the domain of high-speed PMSM. Full article

This study focuses on the experimental determination of the lumped parameters of a Spoke-Type Axial-Flux Permanent Magnet (STAFPM) motor. This type of motor offers high specific torque and is well-suited for transportation applications. The studied STAFPM motor uses Ferrite magnets, which are more environmentally friendly and economical than rare earth magnets. The identification of the lumped electromechanical model parameters is carried out using static torque measurements on a dedicated test bench. The torque measurements are performed in two stages: with and without magnets mounted in the rotor. The no-load flux is determined separately by no-load tests. Together, these tests identify the key parameters of the lumped parameter model, such as self- and mutual inductances, cogging torque, and no-load flux. These parameters are then used to complement the DQ model, commonly used in electric motor analysis. While the DQ model predicts average torque well, it cannot reproduce torque ripples. The lumped parameter model, validated by three-phase DC testing, provides an accurate representation of the motor’s behavior, including torque ripples. This study also applies Maximum Torque Per Ampere (MTPA) control strategies and offers a practical alternative to 3D Finite Element Analysis (FEA), thus aiding the design of STAFPM motors. Full article