Conference Paper

Nested-loop neural network vector control of permanent magnet synchronous motors

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Abstract

With the improvement of battery technology over the past two decades and automotive technology advances, more and more vehicle manufacturers have joined in the race to produce new generation of affordable, high-performance Electric Drive Vehicles (EDVs). Permanent Magnet Synchronous Motors (PMSMs) are at the top of AC motors in high performance drive systems for EDVs. Traditionally, a PMSM is controlled with standard decoupled d-q vector control mechanisms. However, recent studies indicate that such mechanisms show serious limitations. This paper investigates how to mitigate such problems using a nested-loop neural network architecture to control a PMSM. The neural network implements a dynamic programming algorithm and is trained using backpropagation through time. The performance of the neural controller is studied for typical vector control conditions and compared with conventional vector control methods, which demonstrates the neural vector control strategy proposed in this paper is effective. Even in a highly dynamic switching environment, the neural vector controller shows strong ability to track rapidly changing reference commands, tolerate system disturbances, and satisfy control requirements for complex EDV drive needs.

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... However, only a few studies have investigated the challenges encountered in power electronic pulse width modulation (PWM) with the current control through the ADP-based controller [13]. Some studies have [13,14] proposed and validated the vector control of a grid-connected rectifier/inverter using ANN and backpropagation through the time weight updating rule. ...
... .(14). Single line diagram of DSTATCOM with nonlinear loads. ...
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Full-text available
Background & Objective Harmonic amplification is one of the primary issues in power system networks. The objective of this study is to manage the harmonic event and its significant effects on power quality. A new control approach that uses Artificial Intelligence (AI) is proposed and applied to a Distribution Static Synchronous Compensator (DSTATCOM). DSTATCOM is a FACTS device that can achieve highly effective reactive power compensation to reduce and/or damp the harmonic amplification in power system networks. Results & Conclusion Simulation results are obtained using the MATLAB/Simulink package. The validity and effectiveness of using the AI approach are proven based on the DSTATCOM FACTs device with linear and nonlinear loads. Analysis results are discussed.
... Combining parametric structure with incremental optimization forms a new class of ADP called adaptive critic design (ACD) that approximate the optimal cost [12]- [13]. Heuristic dynamic programing (HDP) is the simplest form of ACDs and has been studied in different applications, such as vector control of a grid-connected converter [14], power system stability [15], and permanent magnet synchronous motor drive [16]. ...
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... Combining parametric structure with incremental optimization forms a new class of ADP called adaptive critic design (ACD) that approximate the optimal cost [7]- [8]. Heuristic dynamic programing (HDP) is the simplest form of ACDs and has been studied in different applications, such as vector control of a grid-connected converter [9], power system stability [10], and permanent magnet synchronous motor drive [11]. ...
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... Combining parametric structure with incremental optimization forms a new class of ADP called adaptive critic design (ACD) that approximate the optimal cost [7]- [8]. Heuristic dynamic programing (HDP) is the simplest form of ACDs and has been studied in different applications, such as vector control of a grid-connected converter [9], power system stability [10], and permanent magnet synchronous motor drive [11]. ...
Preprint
Full-text available
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... Yet, only a few papers have investigated the power electronics pulse width modulation (PWM) current control through the ADP based controller concerning the difficulty involved as mentioned in [39]. References [39]− [42] proposed and validated the vector control of a grid-connected rectifier/inverter using an artificial neural network and back-propagation through time weights updating rule. However, the system was not implemented for harmonic reduction applications and the current controller lacks the online learning capability. ...
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In this paper, a new predictive current controller for a permanent magnet synchronous motor (PMSM) considering delays is presented. In a full digital current control system for a PMSM, there are inevitable delays in calculating and applying the inverter output voltages to the motor terminals. A predictive current controller implemented in a full digital system has serious problems such as the oscillation and large overshoot. A discussion of compensation methods to cope with the nonlinearities of the real system is also presented. The proposed current controller has been analyzed, and the experimental results are shown to prove the feasibility and effectiveness of the proposed predictive current controller using a prototype 750 W PMSM servo drive system.
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This paper investigates the performance of an interior permanent magnet synchronous motor (IPMSM) drive over wide speed range for high precision industrial applications. The scheme incorporates the maximum torque per ampere (MTPA) operation in constant torque region and the flux-weakening operation in constant power region in order to expand the operating limits for an IPMSM. Improved mathematical expressions are derived to analyze the performances of the IPMSM. The power ratings of the motor and the inverter are considered. The effects of motor parameters particularly, the saliency ratio (X<sub>q</sub>/X<sub>d</sub>) on the voltage limit constraint and the power capability of the inverter are also investigated. The efficacy of the above mentioned drive system and the improved steady-state analysis are evaluated by both experimental and computer simulation results. The complete drive is implemented in real-time using digital signal processor (DSP) controller board DS 1102 on a laboratory 1 hp interior permanent magnet synchronous motor
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This paper investigates the performance of an interior permanent magnet synchronous motor (IPMSM) drive over wide speed range for high-precision industrial applications. The scheme incorporates the maximum torque per ampere (MTPA) operation in constant torque region and the flux-weakening operation in constant power region in order to expand the operating limits for an IPMSM. Improved mathematical expressions are derived to analyze the performances of the IPMSM. The power ratings of the motor and the inverter are considered. The effects of motor parameters particularly, the saliency ratio (Xq/Xd) on the voltage limit constraint, and the power capability of the inverter are also investigated. The efficacy of the above-mentioned drive system and the improved steady-state analysis are evaluated by both experimental and computer simulation results. The complete drive is implemented in real time using digital signal processor (DSP) controller board DS 1102 on a laboratory 1 hp interior permanent magnet synchronous motor.
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This paper presents a novel sensorless control strategy for a salient-pole permanent-magnet synchronous motor (PMSM). A new model of a salient-pole PMSM using an extended electromotive force (EMF) in the rotating reference frame is utilized to estimate both position and speed. The extended EMF is estimated by a least-order observer, and the estimation position error is obtained from the extended EMF. Both estimated position and speed are corrected so that the position error becomes zero. The proposed system is very simple and the design procedure is easy and clear. Several experimental drive tests are demonstrated and the experimental results show the effectiveness of the proposed sensorless control system.
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In a world where environment protection and energy conservation are growing concerns, the development of electric vehicles (EV) and hybrid electric vehicles (HEV) has taken on an accelerated pace. The dream of having commercially viable EVs and HEVs is becoming a reality. EVs and HEVs are gradually available in the market. This paper will provide an overview of the present status of electric and hybrid vehicles worldwide and their state of the art, with emphasis on the engineering philosophy and key technologies. The importance of the integration of technologies of automobile, electric motor drive, electronics, energy storage, and controls and also the importance of the integration of society strength from government, industry, research institutions, electric power utilities, and transportation authorities are addressed. The challenge of EV commercialization is discussed
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A new learning algorithm for multilayer feedforward networks, RPROP, is proposed. To overcome the inherent disadvantages of pure gradient-descent, RPROP performs a local adaptation of the weight-updates according to the behaviour of the errorfunction. In substantial difference to other adaptive techniques, the effect of the RPROP adaptation process is not blurred by the unforseeable influence of the size of the derivative but only dependent on the temporal behaviour of its sign. This leads to an efficient and transparent adaptation process. The promising capabilities of RPROP are shown in comparison to other wellknown adaptive techniques. I.
Energy Management and Control of Electrical Drives in Hybrid Electrical Vehicles
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J. Ottosson, "Energy Management and Control of Electrical Drives in Hybrid Electrical Vehicles," Department of Industrial Electrical Engineering and Automation, Lund University, Sweden, 2007.
Implementation of a Speed Field Oriented Control of 3-Phase PMSM Motor using TMS320F240
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E. Simon, "Implementation of a Speed Field Oriented Control of 3-Phase PMSM Motor using TMS320F240," Application Report, SPRA588, Texas Instruments, 1999.
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  • P Brunelle
P. Brunelle, " Hybrid Electric Vehicle (HEV) Power Tran Using Battery Model, " The MathWork, January 2007.