Sensorless DTSMC of a three‐level VSI fed PMSM drive

Eldigair, Yousif; Beig, Abdul R.; Alsawalhi, Jamal Y.

doi:10.1049/iet-pel.2018.5523

Cited by 7 publications

(7 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Vsinα and Vcosα components are then converted into digital signals using ADC converters, and the rotor position can then be obtained by solving the tan −1 equation as given in (25). The overall workflow of the angular computation is visualized in Figure 3, which shows the flow of the signals from the Hall elements to the differential amplifiers.…”

Section: Four-element Hall-effect Rotary Encodermentioning

confidence: 99%

Intelligent Fault Detection in Hall-Effect Rotary Encoders for Industry 4.0 Applications

et al. 2022

View full text Add to dashboard Cite

Sensors are the foundational components of any smart machine system and are invaluable in all modern technologies. Consequently, faults and errors in sensors can have a significant negative impact on the setup. Intelligent, lightweight, and accurate fault diagnosis and mitigation lie at the crux of modern industries. This study aimed to conceptualize a germane solution in the domain of fault detection, focusing on Hall-effect rotary encoders. Position monitoring through rotary encoders is essential to the safety and seamless functioning of industrial equipment such as lifts and hoists, and commercial systems such as automobiles. This work used multi-strategy learners to accurately diagnose quadrature and offset faults in Hall-effect rotary encoders. The obtained dataset was then run through a lightweight ensemble classifier to train a robust fault detection model. The complete mechanism was simulated through interconnected models simulated in a MATLAB Simulink™ environment. In real time, the developed fault detection algorithm was embedded in an FPGA controller and tested with a 1 kW PMSM drive system. The resulting system is computationally inexpensive and achieves an accuracy of 95.8%, making it a feasible solution for industrial implementation.

show abstract

Section: Four-element Hall-effect Rotary Encodermentioning

confidence: 99%

Intelligent Fault Detection in Hall-Effect Rotary Encoders for Industry 4.0 Applications

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Recently there has been an upsurge of the interest in six-phase PMSMs because of their potential use in Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs) traction systems [22][23]. The wide use of VSI-fed PMSMs in the actuation of industrial mechatronic systems and particularly in the traction of electric vehicles has made the associated nonlinear control problem be a challenge and recent results towards its solution can be found in [24][25][26][27][28][29]. It has been also aimed to generalize the use of such nonlinear control methods to more types of electric motors (asynchronous, brushless DC or reluctance motors) and to the associated power electronics (converters, inverters) [30][31].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear optimal control for VSI-fed six-phase PMSMs in the traction of electric vehicles

Rigatos,

Abbaszadeh,

Hamida

et al. 2024

Preprint

View full text Add to dashboard Cite

The need for high power in electric vehicles has motivated the use of multi-phase electric motors in the associated traction systems. In this article, a nonlinear optimal control approach is developed for voltage-source inverter-fed six-phase Permanent Magnet Synchronous Motors which can be used in electric vehicles' traction. The dynamic model of the VSI-fed six-phase PMSM undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization is based on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system a stabilizing optimal (H-infinity) feedback controller is designed. This controller stands for the solution to the nonlinear optimal control problem under model uncertainty and external perturbations. To compute the controller's feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The differential flatness properties of the state-space model of the six-phase PMSM are also proven, thus allowing to solve the setpoints definition problem in the motor's functioning. To estimate non-measurable state variables and to implement sensorless control for the dynamic model of the six-phase PMSMs, the H-infinity Kalman Filter is used as a robust state estimator. It is shown that under the proposed control scheme fast and accurate tracking of reference setpoints is achieved with moderate variations of the control inputs.

show abstract

“…However, such control methods may come against limitations related to the nonlinear dynamics of the VSI-PMSM system and its functioning under variable operating conditions. The wide use of VSI-fed PMSMs in the actuation of industrial mechatronic systems and particularly in the traction of electric vehicles or in electric ships’ propulsion has made the associated nonlinear control problem a challenge, and recent results toward its solution can be found in Li and Kennel (2021), Li et al (2022), Wang et al (2022), Eldigair et al (2020), Sandre-Hernandez et al (2019), Zhang et al (2022), Xu et al (2020) and Xiao et al (2019). It has been also aimed to generalize the use of such nonlinear control methods to more types of electric motors (asynchronous or multi-phase motors) and to the associated power electronics (converters, inverters) (Rigatos et al , 2022b, 2022c).…”

Section: Introductionmentioning

confidence: 99%

A nonlinear optimal control approach for voltage source inverter-fed three-phase PMSMs

Rigatos

Abbaszadeh

Marignetti

et al. 2023

COMPEL

View full text Add to dashboard Cite

Purpose Voltage source inverter-fed permanent magnet synchronous motors (VSI-PMSMs) are widely used in industrial actuation and mechatronic systems in water pumping stations, as well as in the traction of transportation systems (such as electric vehicles and electric trains or ships with electric propulsion). The dynamic model of VSI-PMSMs is multivariable and exhibits complicated nonlinear dynamics. The inverters’ currents, which are generated through a pulsewidth modulation process, are used to control the stator currents of the PMSM, which in turn control the rotational speed of this electric machine. So far, several nonlinear control schemes for VSI-PMSMs have been developed, having as primary objectives the precise tracking of setpoints by the system’s state variables and robustness to parametric changes or external perturbations. However, little has been done for the solution of the associated nonlinear optimal control problem. The purpose of this study/paper is to provide a novel nonlinear optimal control method for VSI-fed three-phase PMSMs. Design/methodology/approach The present article proposes a nonlinear optimal control approach for VSI-PMSMs. The nonlinear dynamic model of VSI-PMSMs undergoes approximate linearization around a temporary operating point, which is recomputed at each iteration of the control method. This temporary operating point is defined by the present value of the voltage source inverter-fed PMSM state vector and by the last sampled value of the motor’s control input vector. The linearization relies on Taylor series expansion and the calculation of the system’s Jacobian matrices. For the approximately linearized model of the voltage source inverter-fed PMSM, an H-infinity feedback controller is designed. For the computation of the controller’s feedback gains, an algebraic Riccati equation is iteratively solved at each time-step of the control method. The global asymptotic stability properties of the control method are proven through Lyapunov analysis. Finally, to implement state estimation-based control for this system, the H-infinity Kalman filter is proposed as a state observer. The proposed control method achieves fast and accurate tracking of the reference setpoints of the VSI-fed PMSM under moderate variations of the control inputs. Findings The proposed H-infinity controller provides the solution to the optimal control problem for the VSI-PMSM system under model uncertainty and external perturbations. Actually, this controller represents a min–max differential game taking place between the control inputs, which try to minimize a cost function that contains a quadratic term of the state vector’s tracking error, the model uncertainty, and exogenous disturbance terms, which try to maximize this cost function. To select the feedback gains of the stabilizing feedback controller, an algebraic Riccati equation is repetitively solved at each time-step of the control algorithm. To analyze the stability properties of the control scheme, the Lyapunov method is used. It is proven that the VSI-PMSM loop has the H-infinity tracking performance property, which signifies robustness against model uncertainty and disturbances. Moreover, under moderate conditions, the global asymptotic stability properties of this control scheme are proven. The proposed control method achieves fast tracking of reference setpoints by the VSI-PMSM state variables, while keeping also moderate the variations of the control inputs. The latter property indicates that energy consumption by the VSI-PMSM control loop can be minimized. Practical implications The proposed nonlinear optimal control method for the VSI-PMSM system exhibits several advantages: Comparing to global linearization-based control methods, such as Lie algebra-based control or differential flatness theory-based control, the nonlinear optimal control scheme avoids complicated state variable transformations (diffeomorphisms). Besides, its control inputs are applied directly to the initial nonlinear model of the VSI-PMSM system, and thus inverse transformations and the related singularity problems are also avoided. Compared with backstepping control, the nonlinear optimal control scheme does not require the state-space description of the controlled system to be found in the triangular (backstepping integral) form. Compared with sliding-mode control, there is no need to define in an often intuitive manner the sliding surfaces of the controlled system. Finally, compared with local model-based control, the article’s nonlinear optimal control method avoids linearization around multiple operating points and does not need the solution of multiple Riccati equations or LMIs. As a result of this, the nonlinear optimal control method requires less computational effort. Social implications Voltage source inverter-fed permanent magnet synchronous motors (VSI-PMSMs) are widely used in industrial actuation and mechatronic systems in water pumping stations, as well as in the traction of transportation systems (such as electric vehicles and electric trains or ships with electric propulsion), The solution of the associated nonlinear control problem enables reliable and precise functioning of VSI-fd PMSMs. This in turn has a positive impact in all related industrial applications and in tasks of electric traction and propulsion where VSI-fed PMSMs are used. It is particularly important for electric transportation systems and for the wide use of electric vehicles as expected by green policies which aim at deploying electromotion and at achieving the Net Zero objective. Originality/value Unlike past approaches, in the new nonlinear optimal control method, linearization is performed around a temporary operating point, which is defined by the present value of the system’s state vector and by the last sampled value of the control input vector and not at points that belong to the desirable trajectory (setpoints). Besides, the Riccati equation, which is used for computing the feedback gains of the controller, is new, as is the global stability proof for this control method. Comparing with nonlinear model predictive control, which is a popular approach for treating the optimal control problem in industry, the new nonlinear optimal (H-infinity) control scheme is of proven global stability, and the convergence of its iterative search for the optimum does not depend on initial conditions and trials with multiple sets of controller parameters. It is also noteworthy that the nonlinear optimal control method is applicable to a wider class of dynamical systems than approaches based on the solution of state-dependent Riccati equations (SDRE). The SDRE approaches can be applied only to dynamical systems that can be transformed to the linear parameter varying form. Besides, the nonlinear optimal control method performs better than nonlinear optimal control schemes which use approximation of the solution of the Hamilton–Jacobi–Bellman equation by Galerkin series expansions.

show abstract

Sensorless DTSMC of a three‐level VSI fed PMSM drive

Cited by 7 publications

References 33 publications

Intelligent Fault Detection in Hall-Effect Rotary Encoders for Industry 4.0 Applications

Intelligent Fault Detection in Hall-Effect Rotary Encoders for Industry 4.0 Applications

Nonlinear optimal control for VSI-fed six-phase PMSMs in the traction of electric vehicles

A nonlinear optimal control approach for voltage source inverter-fed three-phase PMSMs

Contact Info

Product

Resources

About