Maximum Torque Per Ampere Research Articles

Active Disturbance Rejection Control for Flux Weakening in Interior Permanent Magnet Synchronous Motor Based on Full Speed Range

To address the impact of load disturbances on the full-speed-range control of an interior permanent magnet synchronous motor (PMSM), an active disturbance rejection control (ADRC) method is proposed. The speed loop employs phased field-weakening control (FW) based on ADRC, while the current loop utilizes proportional-integral-derivative (PID) control. Starting from the motor parameters, the Lagrange multiplier method was used to derive the critical speeds for the maximum torque per ampere (MTPA) and maximum torque per voltage (MTPV) ratios, and the timing for the field-weakening control was analyzed. A full-speed-range control model of the motor was established, and an ADRC-based speed loop controller was designed to achieve smooth transitions between high speeds and anti-disturbance solid capabilities. Based on the proposed control strategy, a 21 kW PMSM was used as the research object, and a full-speed-range control simulation model was developed in MATLAB/SIMULINK to verify the strategy. Compared to the traditional PID control, the simulation results demonstrate that the proposed strategy effectively observes and compensates for load disturbances, significantly reducing initial torque oscillations under three different operating conditions. After a sudden load increase, torque oscillations were reduced by 16%, with the stator current reaching steady state 0.03 s faster, response speed improving by 0.02 s, smooth transitions between speed ranges, and enhanced anti-disturbance performance.

Adaptive Current Angle Compensation Control Based on the Difference in Inductance for the Interior PMSM of Vehicles

Achieving good performance in terms of a fast and accurate maximum torque per ampere (MTPA) control method depends on both accurate parameter estimation and a sophisticated control strategy. However, it often requires a complex and long computational process. This paper proposes an efficient control method using the relationship of torque and current angle for maximum torque per ampere control of the interior permanent magnet synchronous motor (IPMSM) for vehicle application. It was found that it is not necessary for the control method to determine the inductance in the d-q axes; the identification of the difference between each axis is enough. Furthermore, this paper presents a simple and effective procedure to estimate the difference in inductance online, where the linear iron loss calculation method is also designed to support the above process. The proposed control method was experimentally validated on a 5 kW prototype by a TMS320F28335 microcontroller and DSPACE synchronized with a personal computer. The results show that the control process has faster and more accurate performance than the conventional method.

Maximum torque per ampere control of permanent magnet reluctance hybrid rotor dual stator synchronous motor based on sliding mode speed controller

AbstractThis paper proposes a maximum torque per ampere (MTPA) control method for a permanent magnet reluctance hybrid rotor dual stator synchronous motor (PMRHRDSSM) based on a sliding mode speed controller, in response to the complex and special electromagnetic relationship of the motor. The paper focuses on the special electromagnetic relationship of PMRHRDSSM with stator winding series structure. Firstly, the trajectory equation of PMRHRDSSM MTPA stator current vector is derived, and based on the relationship between PMRHRDSSM torque and reluctance dq‐axis current, a PMRHRDSSM current controller that meets MTPA constraints is designed. Afterwards, a PMRHRDSSM sliding mode speed controller was designed with input speed error and output reference torque. Finally, an experimental platform for the proposed control method was established, and the control method was experimentally validated.

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.

Design Of Maximum Torque Per Ampere Control Method In Squirrel Cage Three-Phase Induction Motor

Improving the performance of three-phase induction motors is currently carried out by various control methods. One of them is controlling a three-phase induction motor using the Maximum Torque Per Ampere (MTPA) method. This paper focuses on the study of modeling specific motor models using the MTPA method. The purpose of the study is to prove that with the squirrel cage motor model, the speed can be increased above its rating. The MTPA method is a method of controlling a three-phase induction motor by controlling the current from the torque speed. Modeling is tested to see the responsiveness of the modeled system. The experimental results were tested using two-speed references and the system showed that MTPA control induction motors can improve the performance of three-phase induction motors. The results from the design show that the MTPA method can increase the performance of three-phase induction motors to reach 84.4%. The results of this study can be used as one way to model induction motors.

Torque fault compensation in electric vehicle switched reluctance motor drives: A jellyfish search optimization method

AbstractIn this paper, an enhanced indirect instantaneous‐torque‐control is proposed based on the torque sharing function approach of switched reluctance motor drives for electric vehicles by employing the jelly fish search. The major goal is to attain vehicle desires that include minimal torque ripple, maximum torque per ampere (MTPA), and huge performance and extend speed limit. First, a simplest analytic design is developed a determine more proficient turn‐on angle for the torque product. Second, an altered torque sharing function (TSF) is used for compensating the faults of torque tracking. The proposed technique is calculated to represent an accurate switched reluctance motor and its magnetized features. They have worked to create the machine model and execute the necessary transmits. The torque fault is evaluated and compensated inside the torque sharing function. The adapting TSF is compensates for the torque fault with receiving the phase because it is the minimal flux rate connecting variation. Finally, the jellyfish search technique is accepted to determine the optimal control parameters. The proposed strategies are done in MATLAB and its performance is contrasted with different existing strategies. According to the simulation result, the proposed strategy‐based accuracy is 94.2% at 50 iteration and 80% at 100th iteration which is higher than the existing methods. From this analyses, it proved that the proposed technique gives superior performance to existing one.

Maximum Torque Control of Permanent Magnet-Assisted Synchronous Reluctance Motor Using Fuzzy PI

Abstract This paper proposes a fuzzy PI-based Maximum Torque Per Ampere (MTPA) control for Permanent Magnet-Assisted Synchronous Reluctance Motor (PMASynRM). The aim is to address issues such as overshooting and slow response in the operation of the PMASynRM by optimizing MTPA control under traditional PI using a fuzzy PI control algorithm. This approach enhances the system’s responsiveness and disturbance rejection capabilities. The article builds a simulation model for the maximum torque-to-current ratio control of PMASynRM using fuzzy PI control in MATLAB/Simulink, comparing it with traditional PI control. Simulation results indicate that the fuzzy PI motor control system exhibits lower overshoot, faster response speed, and better robustness compared to traditional PI control.

Optimal control strategies for PMSM with a decoupling super twisting SMC and inductance estimation in the presence of saturation

This paper deals with optimal control strategies robustified by a decoupling super-twisting sliding mode control (ST-SMC) for permanent magnet synchronous machines (PMSM). In general, ST-SMC is a robust method for controlling systems and guarantees asymptotic convergence in cases where the upper bound of model uncertainties such as disturbances and parametric uncertainties is not known a priori, if the upper bound of the derivative is known. The proposed optimal control strategy is designed for a constant torque reference whose control is implemented in two control regions: maximum torque per ampere (MTPA) and flux-weakening control. In the proposed analysis, the operating point of the motor can also be in the saturation region, which makes the estimation of Ld and Lq in the proposed optimization procedure of particular interest and also important for the decoupling control implemented with ST-SMC. To compensate for typical parameter variations, adaptive parameter estimation is introduced into the control system using an extended Kalman filter (EKF) in combination with a bivariate polynomial. In order to be able to make an assessment of the control performance of the ST-SMC, a comparison with a conventional PI controller is shown at the end of the paper. Measured results using hardware in the loop (HIL) to validate the results and their detailed discussion and analysis are included.

A Study Article of Advancing Electric Motor Performance through Maximum Torque Per Ampere (MTPA) Control

Abstract: Electric motor performance can be significantly enhanced through the implementation of Maximum Torque per Ampere control. This advanced control technique allows for optimizing the motor operation by maximizing the torque produced per unit of current. By implementing MTPA control, electric motors can achieve higher efficiency, reduced energy consumption, and improved overall performance. This paper explores the principles and benefits of MTPA control and provides insights into its application across various electric motor systems. The implementation of Maximum Torque per Ampere control has garnered significant attention in the field of electric motor performance enhancement. This advanced control technique offers a promising opportunity to optimize motor operation and achieve higher efficiency. By maximizing the torque produced per unit of current, MTPA control not only reduces energy consumption but also improves the overall performance of electric motors. Furthermore, the application of MTPA control has shown promising results across various electric motor systems, making it a versatile and impactful advancement in the field.

Study on Performance Improvement through Reducing Axial Force of Ferrite Double-Layer Spoke-Type Permanent Magnet Synchronous Motor with Core Skew

Recently, due to the price fluctuation and supply instability of rare earth mineral resources, there has been a lot of development of electric motors using non-rare-earth permanent magnets. As a result, motors using Dy-free permanent magnets and ferrite permanent magnets are being researched, and, in particular, ferrite permanent magnets often utilize spoke-type structures, which are magnetic flux concentrators, to compensate for their low coercivity and residual flux density. However, in general, spoke-type PMSMs do not use much reluctance torque, so double-layer spoke-type PMSMs have been studied for their more efficient design. Unlike general spoke-type PMSMs, double-layer spoke-type PMSMs can utilize high reluctance torque by increasing the difference between d-axis and q-axis reluctance. However, as the difference in magnetic resistance increases, vibration and noise are generated, which adversely affects the mechanical part and shortens the life of the motor. Although this problem seemed to be solved by applying core skew in the previous study, it was confirmed that the axial force caused by the axial leakage flux occurred in the maximum torque per ampere (MTPA) control section and the torque ripple was increased. Therefore, in this paper, a model that can apply symmetrical core skew and reduce axial force is proposed. First, the causes of the axial force generated in previous studies were analyzed. Based on the analysis of these causes, a new symmetrical core skew structure was proposed, and its justification was verified through FEA.

A FEA-Based Fast AC Steady-State Algorithm for a Voltage-Driven PMSM by a Novel Voltage-Flux-Driven Model

Finite element analysis (FEA) has been used more frequently than ever before in electrical machine design covering different disciplines such as electromagnetics, rotor dynamics, thermodynamics etc. The accuracy and speed of FEA are in high demands, especially when the time-stepping FEA is employed in the electromagnetic design of the machine. In this paper, to accelerate numerical transient in FEA of a voltage-driven permanent magnet synchronous machine (PMSM), a fast AC steady-state algorithm has been proposed, in which the voltage supply is converted into the stator flux linkage and the machine can be regarded as driven by the flux linkage directly. The electromagnetic transient is eliminated by injecting additional voltage signals to compensate the oscillating stator flux linkage in transient and the time-stepping error caused by the backward Euler in FEA. And the additional voltage signals will finally disappear after the steady state is achieved within about a half electrical time period. In addition, the maximum torque per ampere (MTPA) control logic can also be realized by adjusting the initial phase angle of the voltage supply based on the vector diagram. The simulation speed of the proposed method in this paper was compared to other traditional models and the accuracy was verified by experimental results.

MTPA Control for DC-Biased Hybrid Excitation Machine Using MTPA Control Law and Virtual Signal Injection

This paper proposes an overall maximum torque per ampere (MTPA) control for dc-biased hybrid excitation machine (dc-biased HEM) using MTPA control law and virtual signal injection. The mathematical model of the machine is first analyzed in synchronous rotating reference frame. According to the characteristic of the mathematical model, a control strategy is proposed and consists of two parts, i.e., an MTPA control law and a virtual dc-biased signal injection. The MTPA control law is employed to calculate the dominant current references while ensuring the rapid dynamic performance. The virtual dc-biased signal injection method is a correction scheme for MTPA current deviation caused by parameter variations. Unlike conventional signal injection techniques, this signal injection method considers the nonlinearity of inductance and does not involve any filters. Thus, it can extract MTPA criterion more accurately and easily. In general, simulation and experimental results validate that the control strategy combined with MTPA control law and virtual signal injection can achieve accurate MTPA operation and rapid dynamic magnetization capability for the dc-biased HEM in real time.

Neural Network With Cloud-Based Training for MTPA, Flux-Weakening, and MTPV Control of IPM Motors and Drives

An interior permanent magnet (IPM) motor is a prime electric motor used in electric vehicles (EVs), robots, and electric drones. In these applications, maximum torque per ampere (MTPA), flux-weakening, and maximum torque per volt (MTPV) techniques play a critical role in the efficient and reliable torque control of an IPM motor. Although several approaches have been proposed and developed for this purpose, each has its specific limitations. The objective of this paper is to develop a neural network (NN) method to determine MTPA, flux-weakening, and MTPV operating points for the most efficient torque control of the motor over its full speed range. The NN is trained offline by using the Levenberg-Marquardt backpropagation algorithm, which avoids the disadvantages associated with online NN training. A cloud computing system is proposed for routine offline NN training, which enables the lifetime adaptivity and learning capabilities of the offline-trained NN and overcomes the computational challenges related to online NN training. In addition, for the proposed NN mechanism, training data are collected and stored in a highly random manner, which makes it much more feasible and efficient to implement lifetime adaptivity than any other methods. The proposed method is evaluated via both simulation and hardware experiments, which shows the great performance of the NN-based MTPA, MTPV, and flux-weakening control for an IPM motor over its full speed range. Overall, the proposed method can achieve a fast and accurate current reference generation with a simple NN structure, for optimal torque control of an IPM motor.

An enhanced predictive current control technique for interior permanent magnet synchronous motor drives with extended voltage space vectors for electric vehicles

SummaryPermanent magnet synchronous motors (PMSM) are widely employed in the application of electric vehicles (EVs) due to their simplicity of operation. Model predictive current control (MPCC) is an advanced technique used to control the PMSM owing advantages like multi‐variable cost function and good dynamic performance. Cost function of predictive current control (PCC) does not require the flux weighting factor; hence, it is simple in the selection of suitable voltage vector (VV). The conventional PCC (C‐PCC) applied to interior PMSM (IPMSM) contains more torque and flux ripples as it includes only one set of voltage vectors for all speed ranges. In proposed PCC (P‐PCC), the magnitude and location of voltage vectors is to be selected as large and small VVs to reduce torque ripples. The P‐PCC in this article utilizes two set of extended voltage vectors (large and small VVs) based on the applied speed change in dynamic conditions and hence reduces the ripple content. Incorporating maximum torque per ampere (MTPA) control in this article serves the purpose of optimizing the machine performance. By adding MTPA to the proposed method, it is aimed to enhance the machine performance with less ripples and improved torque response. Simulation results are presented for conventional and P‐PCC to highlight the effectiveness and efficacy of the P‐PCC. The P‐PCC is experimentally verified with 3.7 kW PMSM using d‐SPACE controller.

Nonlinear Magnetic Model of IPMSM Based on the Frozen Permeability Technique Utilized in Improved MTPA Control

In this paper, the enhanced nonlinear magnetic model of the low voltage interior permanent magnet synchronous machine (IPMSM) is developed using the frozen permeability (FP) technique in finite element analysis (FEA) FEMM 4.2 software. The magnetic model is derived by obtaining flux saturation maps for a wide range of dq stator currents. Furthermore, the FEA FP technique accounts for the corresponding offset in the flux maps due to the excitation of the permanent magnets, and well as for fitting the coefficients for the curve-fitting procedure. In order to demonstrate the usefulness of the proposed magnetic model, a nonlinear control strategy based on the maximum torque per ampere (MTPA) optimal algorithm for IPMSM is employed. The magnetic model and the MTPA control strategy are validated through a variety of computer simulations based on FEMM 4.2 and MATLAB R2023a software, as well as on a real IPMSM electric vehicle (EV) traction drive experimental setup.

Excitation Control of Brushless Induction Excited Synchronous Motor with Induction Machine Operating in Deep-Plugging Mode

Abstract The popularity of electrified transportation is rising at a sharp pace due to environmental concerns over internal combustion (IC) engines. Researchers are nowadays looking for a brushless and permanent magnet (PM)-less solution for electric vehicle (EV) motors. Wound-field synchronous motor (WFSM) is a potential solution for EVs and is being used in Renault Zoe EV and BMW iX3 e-Drive models. A Brushless Induction excited Synchronous Motor (BINSYM) is a WFSM where the exciter, an induction machine (IM), is embedded inside the synchronous machine (SM) frame. Two machines (SM and IM) are configured for different numbers of poles to achieve magnetic decoupling, which facilitates independent control of both machines. The purpose of IM is to maintain the excitation requirement of SM. The IM is controlled in deep-plugging mode at a constant slip frequency over the entire speed range to minimise its reactive power demand. The maximum torque per ampere (MTPA) and root mean square (rms) current minimisation algorithms are used to control the SM. Simulation of the BINSYM-based system under dynamic conditions (MTPA with varying field current and load transient) has been carried out in MATLAB/Simulink to validate the control strategies. Experimental findings from the laboratory prototype machine closely match the simulation results.

The Development and Application of MTPA Calibration Method Based on INCA FLOW and MATLAB

Article The Development and Application of MTPA Calibration Method Based on INCA FLOW and MATLAB Zhijun Liu 1,2, Renyi Huang 1,*, Xiaoyan Zhuo 1, Kailiang Chen 1, and Guanglan Li 1 1 Liuzhou Saike Technology Development Co., Ltd., Liuzhou 545005, China 2 Liuzhou Key Laboratory of Electrified Powertrain Electronic Control, Liuzhou 545005, China * Correspondence: renyi.huang@foxmail.com Received: 20 July 2023 Accepted: 6 November 2023 Published: 28 November 2023 Abstract: In industrial applications, the maximum torque per ampere (MTPA) control algorithm typically employs an offline look-up table (LUT) method instead of an online MTPA control method to reduce the online computational resources. However, the LUT method has some drawbacks, such as heavy testing workload, longer cycles, and cumbersome data processing, significantly diminishing the efficiency of MTPA data acquisition. To address the limitations of the LUT method, this study proposes an automatic MTPA calibration method combining INCA FLOW and MATLAB. The calibration efficiency and data accuracy are improved by utilizing INCA FLOW for automatic MTPA testing and MATLAB for data processing. An experimental test bench was constructed to evaluate the proposed method. The experimental results demonstrate that this method efficiently performs MTPA data testing and visualizes the results. Compared with the traditional manual MTPA calibration method, this method achieves a 320% improvement in calibration efficiency. The main technical contribution of this study is the introduction of the automatic MTPA calibration method that not only optimizes data accuracy but also enhances calibration efficiency.

Regularization-Theory-Based Fast Torque Tracking Method for Interior Permanent Magnet Synchronous Machines

With the rapid growth of interior permanent magnet synchronous machines in electric vehicle applications, there is a need to generate torque tracking look-up tables, that can both track the torque command and implement maximum torque per ampere (MTPA)/maximum torque per volt (MTPV). So far, most torque tracking methods require a large amount of test points, giving rise to long test time and workloads. This paper proposes a fast torque tracking MTPA/MTPV look-up table generating method to improve the efficiency. The proposed method is based on a machine learning regularization theory, using a L1/L2 regularization to establish a data-driven torque tracking model. Then a Lagrange dual principle is introduced to solve the unknown parameters, so that the look-up tables of optimal d-q axis currents are yielded by a global optimization solver. Experimental results show that the proposed method can generate the look-up tables with the same accuracy as classical methods, but requires less test points and testing time. As a result, the testing work loads are reduced, as the time cost is only 10-15% of the classical methods.

Investigation of AC Copper Loss Considering Effect of Field and Armature Excitation on IPMSM With Hairpin Winding

As the torque density of traction motors for electric vehicles (EVs) increases, winding technology with a large conductor area, such as hairpin winding, is widely used. However, it has a disadvantage of large AC copper loss affected by the skin and proximity effect. Therefore, the AC copper loss should be considered for deriving characteristics of IPMSM. This paper deals with the maximum torque per ampere (MTPA) and flux-weakening control characteristics of the IPMSM considering AC copper loss. As the AC copper loss is caused by armature and field excitation, a separation process of AC copper loss by each cause is proposed. By using the process, the separated AC copper loss can be analyzed according to the current vector and rotational speed. However, it is inefficient to calculate the AC copper loss according to rotational speed using transient analysis. Therefore, a computationally efficient method of calculating AC copper loss based on magneto-static analysis is presented. In addition, advanced <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d, q</i> -axis equivalent model considering AC copper loss is proposed to analyze MTPA and flux-weakening control characteristics of IPMSM. By using the proposed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d, q</i> -axis equivalent model, the IPMSM can be designed considering the AC copper loss efficiently and accurately.

Fractional-Order Extremum Seeking Method for Maximum Torque per Ampere Control of Permanent Magnet Synchronous Motor

Maximum torque per ampere (MTPA) control of internal permanent magnet synchronous motors (IPMSM) has become integral to high-efficiency motor drives. To minimize the influence of the traditional model-based analytical solution method on the MTPA control strategy due to the parameter variations during the motor operation, an online search MTPA method without model-based fractional-order extremum seeking control (FO-ESC) is proposed. Compared with the traditional integer-order ESC method, the Oustaloup approximation-based fractional-order calculus provides additional factors and possibilities for optimizing controller parameters to improve control performance. At the same time, the proposed approach does not require machine parameters and is thus not influenced by machine and drive nonlinearities. Simulation results show that the proposed method can ensure robust MTPA control under different loading conditions in real-time and improve the system’s dynamic response speed and steady-state accuracy.