Maximum Torque Per Ampere Control Research Articles

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.

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.

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.

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.

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.

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.

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.

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.

Maximum torque per ampere controlled induction motor drive with reduced DC link capacitor

ABSTRACT This paper presents a three-phase induction motor (IM) drive comprising a single-phase Pulse Width Modulated (PWM) converter with an active power decoupling (APD) as an active front-end converter (AFEC) to reduce the size of a DC link capacitor. Consequently, film capacitors can be used in place of bulky electrolytic capacitors that improve the power density, reliability, and cost of AFECs. A control scheme for an APD circuit is developed to mitigate the ripple power, and to control the three-phase IM, a maximum torque per ampere (MTPA) control scheme is implemented. A Simulink model of the proposed system rated for 3.73 kW, 200 V, and 50 Hz three-phase IM drive and its equivalent prototype model are developed in a laboratory and the APD and the MTPA control schemes are implemented with the help of STM32F407VG, a 32-bit microcontroller and dSPACE 1104, respectively. This paper demonstrates the experimental verification of the concepts for APD and MTPA control. Further, a significant reduction in motor current at starting/light load conditions is observed that leads to lower energy requirements. The prospective application of these schemes includes railway traction drive, electric vehicles, and so on, where compactness, reliability, and lower energy requirements are the prime concerns.

Permanent Magnet Flux Linkage Analysis and Maximum Torque per Ampere (MTPA) Control of High Saturation IPMSM

The maximum torque per ampere (MTPA) control is significant for improving the efficiency of the interior permanent magnet synchronous motor (IPMSM). However, for the high saturation IPMSM, the change of the permanent magnet (PM) flux linkage is more complicated, which can cause the MTPA control to deviate from the optimal solution. Therefore, an improved MTPA control method for the high saturation IPMSM is proposed in this paper. Compared with other methods, the proposed method improves the conventional models of flux linkage and torque by analyzing the nonlinear variation of the PM flux linkage with the dq-axis currents. Subsequently, an expression suitable for the MTPA control of high saturated IPMSM is derived based on the improved models. The proposed parameter fitting models are then fitted using data from 11 operating points and incorporated into the MTPA optimization algorithm to obtain the MTPA curve. Finally, the effectiveness of the proposed method in enhancing the control accuracy of the MTPA angle is verified through simulations and experiments.

Improved Current and MTPA Control Characteristics Using FEM-Based Inductance Maps for Vector-Controlled IPM Motor

Some major problems in the motor drive are the overshoot or undershoot of transient response characteristics and a parameter mismatch due to magnetic saturation. This study proposed a 3D inductance map combined with a maximum-torque-per-ampere (MTPA) map based on a finite-element (FE) motor model considering a cross-coupling magnetic saturation impact to overcome this problem. The proposed FE motor model has a high accuracy of no-load back electromotive force (e.m.f.) around 98.3% compared to the measurement results. Then, nine scenarios of vector control combinations of inductance maps and current supply variations of β 0°, 45°, and MTPA were investigated. As a result, the transient response improvement for β 0°, 45°, and MTPA without the map and with Ld and Lq maps is 63%, 10%, and 15%, respectively. Moreover, for the steady-state response, the average torque improvement between MTPA and Idref 0 A control is 9.21%, 8.97%, and 8.98% for the no-map, ave-map, and 3D-inductance-map conditions, respectively. The MTPA trajectory characteristic was also updated to illustrate the actual MTPA condition compared to the conventional MTPA control. In detail, the proposed method has reduced the parameter mismatch for the current control loop in the transient state and improved the MTPA control trajectory for the steady-state response. Finally, the improvement of vector control characteristics of the proposed method was verified by an FE simulation and experimental measurement results.

인공 신경망을 이용한 PMSM의 MTPA 운전점 개선

In order to minimize copper loss of Permanent Magnet Synchronous Motor(PMSM), Maximum Torque Per Ampere(MTPA) control is essential. The MTPA control method utilizing mathematical models requires accurate information of parameters, but it is difficult to perform an accurate MTPA because the parameters may vary with temperature and load. Therefore, this paper proposes the new MTPA control method using ADALINE(Adaptive Linear Neuron), one of the Artificial Neural Network(ANN). In the proposed method, the locus of the stator current relative to the dSUPγ/SUP -axis current is estimated using ADALINE, and the MTPA operating point is determined through the estimated locus. This method is resistant to fluctuations in motor parameters and is easy to implement.

Optimization Control of Canned Electric Valve Permanent Magnet Synchronous Motor

The traditional canned electric valve consists of an induction motor and a reducer, which need to be matched with the position sensor to achieve precise control of valve position. The position sensor and reducer are not only easily damaged in high-temperature liquids, but also the slip rate of the induction motor is greatly affected by the liquid temperature, which makes it difficult to achieve accurate control. To address the above problems, this paper introduces a new topology of canned electric valve permanent magnet synchronous motor (CEV-PMSM), and a new maximum torque per ampere (MTPA) model is proposed. The new MTPA control equation considering the canned sleeve parameters is derived theoretically. By comparing it with id = 0 control and ideal MTPA control strategy, it is proved that the new MTPA model reflects the electric valve operation characteristics more realistically. In order to achieve sensorless control of the electric valve, and to achieve fast response and high-precision control under external disturbances and parameter uncertainties, the proposed control scheme combines sensorless control and two-degree-of-freedom (2-DOF) control. Consequently, the proposed control scheme can effectively improve the static and dynamic performances of the CEV-PMSM, as well as adjust the tracking and anti-disturbance performances independently. Finally, a 2 kW 100 r/min prototype was manufactured and corresponding experiments were conducted to verify the accuracy of the analysis.

Efficient Maximum Torque Per Ampere (MTPA) Control of Interior PMSM Using Sparse Bayesian Based Offline Data-Driven Model With Online Magnet Temperature Compensation

The maximum torque per ampere (MTPA) is popular control strategy for interior permanent synchronous machines (PMSMs) and MTPA point is dependent on the magnetic saturation and magnet temperature. This paper proposes a novel MTPA control method combining offline model and online compensation model for interior PMSM control. In the proposed approach, an offline sparse Bayesian based data driven model is derived from the machine equations to consider magnetic saturation, and an online compensation model is proposed to compensate the magnet temperature. The MTPA point can be derived by combining both the offline and online models, in which both saturation and temperature effects are considered to ensure the performance of MTPA point tracking. Compared with the offline methods, the proposed approach employs the sparse vector to represent the MTPA model with less computation and memory consumption and considers the temperature effect with better robustness. Compared with the online methods, the proposed approach only compensates the offline model with online temperature effect, which is less sensitive to noise and uncertainties and involves less computation. The proposed approach is validated with comparisons and experiments on a laboratory interior PMSM drives.

Improved MTPA Control for Variable-Flux Memory Machine With Operating Envelope Prediction-Based MS Manipulation

This article proposes an improved maximum torque per ampere (MTPA) control method for variable-flux memory machine (VFMM) with operating envelop prediction-based magnetization state (MS) manipulation. The proposed method can achieve the MTPA control under the voltage limitation and simplify the MS adjustment process for expanding the operating region. The mathematical model of the studied VFMM is established to calculate the reference current for MTPA control online as well as to predict the operating envelop at each MS. According to the calculated operating envelop, the proposed MS manipulation method can separate the magnetization and demagnetization processes by setting two MS manipulation boundaries correspondingly, which is easily implementable and can avoid frequent MS manipulation processes. Besides, the inductance characteristics of the machine are measured to improve the model accuracy and control performance. Experiments are carried out on a VFMM prototype to validate the feasibility and effectiveness of the proposed method.

Topology Optimization Framework for Simultaneously Determining the Optimal Structural Design and Current Phase Angle of the IPMSMs for the MTPA Control

Although it is crucial to design the magnetic flux path and the maximum torque per ampere (MTPA) current reference under the current limitation, it is challenging to simultaneously consider these features in developing an interior permanent magnet synchronous motors (IPMSM) due to complicated coupling effects. In this article, to overcome the above issue, the motor-design parameters are estimated by conducting electromagnetic finite element (FE) analysis two times at every iteration of topology optimization. Then, the MTPA current phase angle can be analytically expressed in terms of an elementwise relative density (i.e., design variable in topology optimization). In addition, the structural safety is assessed by conducting the structural FE analysis under design-dependent loads to reflect a high-speed rotation. The proposed two-stage topology optimization enables us to simultaneously optimize both a structural design and current phase angle to achieve the maximum electromagnetic performance. Structural safety and manufacturability are also considered to obtain a practically meaningful design. With two different types of permanent magnets, the optimized IPMSMs are obtained and manufactured to validate the proposed method. Simulation and experimental results demonstrate the validity and potential of this work.

Dynamic Direct Voltage MTPA Current Sensorless Drives for Interior PMSM-Based Electric Vehicles

This research presents a current sensorless dynamic direct voltage method based on the maximum torque per ampere (MTPA) technique to control the rotor speed of interior permanent magnet synchronous motors (IPMSMs) for electric vehicle (EV) applications. It considers the dynamic model of the machine and generates a particular pair of voltage amplitude and its angle to track the speed profile of the driving cycle. The proposed control strategy contributes by eliminating the need for a current sensor, avoiding cascaded PI controllers, and overcoming the limitations of transient states. Consequently, the measurement noise and equipment failure do not affect the control loop, the tuning of a single PI controller becomes much simpler than two cascaded PI controllers, and the absence of MTPA tracking and current or voltage overshooting at transient states cannot limit the performance of the control technique. Additionally, the aforementioned modifications improve the response time of the proposed strategy and make it nimble enough for EV applications. A comparative analysis is carried out on the proposed current sensorless dynamic direct voltage MTPA control, simplified dynamic direct voltage control (S-DDVC), and the field oriented control (FOC) models. The outcomes confirm that the introduced model substantially reduces the inrush current and voltage. Experimental results with quantitative tracking and energy consumption assessments reveal that the proposed method demands 9.7% lower energy than the FOC counterpart in urban driving plans by operating IPMSM in high efficiency region.

Direct Voltage MTPA Speed Control of IPMSM-Based Electric Vehicles

A simple maximum torque per ampere (MTPA) method is designed for interior permanent magnet synchronous motors (IPMSMs) with no current control. The proposed method tracks the rotor speed by finding the best pair of voltage angle and amplitude for each motor’s speed and torque condition. This is achieved without stand for any current control loop and using a single controller, which makes the technology simple to a great extent, contrary to the majority of methodologies in the literature. Moreover, a thorough insight analysis is provided to determine analytically the control gains, which simplifies control and tuning and makes it a suitable contender for the development of low-cost PMSM drives. To illustrate the capability of the suggested control method, a comparative study is conducted using the popular MTPA vector control strategy. Experimental results for various situations reveal the ability of the suggested MTPA controller in steady-state, standstill, and transient conditions. Additionally, to quantitatively assess the MTPA trajectory tracking accuracy, both control methods are compared using an efficiency metric. Besides, the US06 standard driving cycle is implemented experimentally to validate the proposed method for electric vehicle applications.

Parameter identification for MTPA control based on a nonlinear d-q dynamic IPMSM model

PurposeSmall highly saturated interior permanent magnet- synchronous machines (IPMSMs) show a very nonlinear behaviour. Such machines are mostly controlled with a closed-loop cascade control, which is based on a d-q two-axis dynamic model with constant concentrated parameters to calculate the control parameters. This paper aims to present the identification of a complete current- and rotor position-dependent d-q dynamic model, which is derived by using a finite element method (FEM) simulation. The machine’s constant parameters are determined for an operation on the maximum torque per ampere (MTPA) curve. The obtained MTPA control performance was evaluated on the complete FEM-based nonlinear d-q model.Design/methodology/approachA FEM model was used to determine the nonlinear properties of the complete d-q dynamic model of the IPMSM. Furthermore, a fitting procedure based on the nonlinear MTPA curve is proposed to determine adequate constant parameters for MTPA operation of the IPMSM.FindingsThe current-dependent d-q dynamic model of the machine models the relevant dynamic behaviour of the complete current- and rotor position-dependent FEM-based d-q dynamic model. The most adequate control response was achieved while using the constant parameters fitted to the nonlinear MTPA curve by using the proposed method.Originality/valueThe effect on the motor’s steady-state and dynamic behaviour of differently complex d-q dynamic models was evaluated. A workflow to obtain constant set of parameters for the decoupled operation in the MTPA region was developed and their effect on the control response was analysed.