Maximum Torque Per Ampere Tracking Research Articles

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.

A sensorless stable V/f control of SPMSM based on constant power factor control with a novel MTPA tracking

The paper presents a sensorless stable V/f control strategy of surface permanent magnet synchronous motor (SPMSM), where the maximum torque per ampere (MTPA) condition is satisfied by controlling the d-axis current to zero. However, to directly control the d-axis current, it is necessary to know the exact rotor position, which is not possible in sensorless V/f control. Based on this fact, a constant power factor (CPF) control loop in voltage vector reference frame dvqv with a novel MTPA tracking according to a look-up table (LUT) was developed. The LUT was created based on a set of experimental measurements to store the motor power factor where MTPA is reached. The proposed stable V/f control strategy shows an accurate MTPA tracking of SPMSM in the entire operational range verified by experiments.

Second Harmonic Seamless Splicing Technique Based on Maximum Active-Voltage Vector for Online MTPA Tracking Control of SynRM

Maximum-torque-per-ampere (MTPA) control strategy is widely employed to achieve the optimal efficiency control of synchronous reluctance machines (SynRMs). However, the control efficiency of the conventional method that the optimal current distribution angle is directly calculated based on the knowledge of the machine parameters is seriously affected by the highly nonlinear and time-varying characteristics of SynRMs. Therefore, in order to effectively resolve this problem, a novel MTPA control scheme based on the second harmonic splicing technique is proposed in this article. Differing from the conventional method, the proposed solution utilizes the transient response current slopes of fundamental maximum active-voltage vector to splice a specific second harmonic signal that contains the optimal current distribution angle. After selecting two available and different splicing coefficients in each sector to guarantee the continuity of the spliced second harmonic signal, the optimal current distribution angle can be obtained accurately without any machine parameters through a simple signal demodulation, which significantly enhances the robustness to machine parameter variations. Furthermore, the influence of rotor position acquisition errors caused by the position sensor's limited accuracy and installation misalignment is analyzed in detail. Finally, the experimental results demonstrate the effectiveness and feasibility of the proposed MTPA control scheme.

MTPA Tracking Control of Sensorless IPMSM Based on Square-Wave Voltage Signal Injection

This article proposes an online maximum torque-per-Ampere (MTPA) control of an interior permanent-magnet synchronous motor (IPMSM) based on the square-wave voltage signal injection. Because the proposed method does not rely on a position sensor, it is applicable to sensorless IPMSMs. The proposed algorithm consists of a dynamic inductance estimator, frequency-adaptive flux observer, and an MTPA tracking controller. The proposed inductance estimation utilizes the pulsating square-wave voltage injection, which can maximize the injection frequency, and the dynamic performance can be preserved during the signal injection. Through the online flux and inductance estimation, the magnetic saturation of the IPMSM and the temperature variation can be fully considered in the MTPA control. The conventional rotor position estimator is replaced with the MTPA tracking controller, which does not rely on offline commissioning parameters. The proposed algorithm can operate under both the torque control and speed control mode, and accurate torque control on MTPA curve can be achieved. The simulation and experimental results demonstrate that the proposed method accurately tracks the MTPA point up to 200% of the rated torque in the mid- and high-speed region.

Intelligent Maximum Torque per Ampere Tracking Control of Synchronous Reluctance Motor Using Recurrent Legendre Fuzzy Neural Network

In order to construct a high-performance synchronous reluctance motor (SynRM) drive system, an intelligent maximum torque per ampere (MTPA) tracking control using a recurrent Legendre fuzzy neural network (RLFNN) is proposed in this study. First, a traditional MTPA (TMTPA) control system based on FOC is introduced. Since the reluctance torque of the SynRM is highly nonlinear and time-varying, the MTPA tracking control is very difficult to achieve by using the TMTPA control in practical applications. Then, an adaptive computed current (ACC) speed control using the proposed RLFNN for the MTPA tracking control of a SynRM drive system, which does not use a lookup table and can effectively obtain the optimal current angle command of MTPA online, is described in detail. The ACC speed control is applied to generate the stator current magnitude command, and an adaptation law is proposed to online adapt the value of a lumped uncertainty in the ACC control. Moreover, the adaptation law is derived using the Lyapunov stability theorem to guarantee the asymptotic stability of the ACC speed control. Furthermore, the proposed RLFNN is employed to produce the incremental command of the current angle. In addition, the ACC speed control and RLFNN are implemented in a TMS320F28075 32-bit floating-point digital signal processor for a 4 kW SynRM drive system. Finally, the robustness and effectiveness of the proposed intelligent MTPA tracking control are verified by some experimental results.

Maximum torque per ampere control with direct voltage control for IPMSM drive systems

This paper proposes an analytical method to determine maximum torque per ampere (MTPA) trajectories in the voltage plane for interior permanent magnet synchronous machines (IPMSMs). The MTPA is formulated as an optimization problem and its solution is obtained within a closed-form function, from the current and voltage planes. In consequent, the MTPA tracking control strategy with the novel closed-loop direct voltage control is developed for the IPMSM drive systems. Comparison studies against the well-known conventional current regulation-based MTPA tracking control strategy illustrate the superiority of the developed strategy in various aspects as well as its efficient MTPA tracking capability. Furthermore, it also shows more robustness to the IPMSM’s parameter variations than conventional strategy from voltage constraint point of view.

MTPA Trajectory Tracking Control with On-line MRAS Parameter Identification for an IPMSM

The maximum torque per ampere (MTPA) control is capable of obtaining its maximal ratio of torque to current in a control system of interior permanent magnet synchronous motor (IPMSM). However, when its electrical parameters change with the actual operating conditions, the resulting MTPA trajectory will deflect from the optimal one. To solve this problem, a modified model reference adaptive system (MRAS) method is investigated for the parameter identification of the rotor flux linkage and the stator q-axis inductance, after a tradeoff between the MTPA trajectory derivation degree with parameter change and the rank-deficiency problem in the identification model. In this method, a full-rank estimator and its gain matrix are designed according to the Popov Hyper Stability Theorem. And the current operating point is updated using the identified parameters in order for the real-time tracking of MTPA trajectory. Simulation and experimental results verify that the proposed method enhances remarkably the MTPA tracking control effect and the system’s torque-current characteristics for an IPMSM.

Automatic MTPA Tracking in IPMSM Drives: Loop Dynamics, Design, and Auto-Tuning

Maximum Torque Per Ampere (MTPA) based on motor parameters is a common approach to achieve high efficiency and torque density in Interior Permanent Magnet Synchronous Machine Drives (IPMSMs). However, uncertainty (e.g., due to identification errors, magnetic saturation, or temperature variation) results in undesired deviation from the optimal operating trajectory. To solve this problem, MTPA tracking methods have been proposed, which exploit signal injection to search the minimum current point for a certain load torque in a closed-loop fashion. Closed-form design of the MTPA tracking loop dynamics has never been addressed in past literature and represents the main topic of this paper. A recent and efficient tracking method has been considered for the analysis and case study, i.e., [14]. Nonlinear small-signal gain of the loop can be calculated in closed form, leading to two valuable results. Dynamics can be programmed by optimal design of the tracking regulator, and online adaptation can be applied, making the designed MTPA tracking dynamics invariant with the operating point. A straightforward and effective solution is proposed for the regulator design, which allows us to obtain the desired bandwidth and first-order tracking response in the whole range of operation, being also suitable for auto-tuning and online adaptation. The method has been studied analytically and in simulation, also considering the influence of noise and parametric uncertainties. Finally the technique has been implemented on the hardware of a commercial industrial drive, proving the effectiveness of the proposal. The concepts described in this paper, design approach and adaptation strategy, analyzed here for the first time, are general and can be applied to any control scheme implementing closed-loop MTPA tracking.

On Accuracy of Virtual Signal Injection based MTPA Operation of Interior Permanent Magnet Synchronous Machine Drives

This correspondence analyzes the accuracy of maximum torque per ampere (MTPA) operations of interior permanent magnet machines based on the technique described in [T. Sun, J. Wang, and X. Chen, “Maximum Torque Per Ampere (MTPA) Control for Interior Permanent Magnet Synchronous Machine Drives Based on Virtual Signal Injection,’’ IEEE Trans. Power Electron., vol. 30, no. 9, pp. 5036-5045, Sep. 2015] in responses to a few inquiries made by the readers. It is shown that due to parameter variations with stator currents, any technique for MTPA tracking based on piecewise constant parameter assumption, i.e., the machine parameters are assumed as constants during the calculation of $\partial {T_e}/\partial \beta $ , would result in tracking error even though the machine parameters are obtained from lookup table or online machine parameter estimations. The error is dependent on machine nonlinear characteristics and operating conditions. It is also shown that for the prototype interior permanent magnet synchronous machine the virtual signal injection control technique described in the paper mentioned above yields a better tracking accuracy.

Maximum Torque per Ampere (MTPA) Control of an IPM Machine Based on Signal Injection Considering Inductance Saturation

The aim of this study was to develop a new method to operate an interior permanent magnet synchronous machine (IPMSM) on the maximum torque per ampere (MTPA) condition. The characteristics of the MTPA condition were analyzed and the MTPA condition was derived based on the input electric power. The proposed method injects a small current signal used for tracking the MTPA operating point along with the fundamental current for torque generation. This method does not require any machine parameters or premade lookup table. The frequency of the injected signal is several hundred hertz, and the performance of the MTPA tracking is almost free from load torque disturbance. The feasibility of the proposed method was verified under various operating conditions with computer simulation and testing with an 11 kW IPMSM drive system.