• Title, Summary, Keyword: IPMSM Drive

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Development of IPMSM Motor Drive for NEV (NEV용 IPMSM 모터 드라이브 개발)

  • Lee, Jin-Woo;Mok, Hyung-Soo;Kim, Sang-Hoon;Lee, Yong-Gue;Choe, You-Young
    • Proceedings of the KIPE Conference
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    • pp.444-445
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    • 2010
  • This paper deals with the development of an IPMSM motor drive for NEVs. The drive system consists of 7kW IPMSM motor, DSP-based controller, and MOSFET-based inverter. The controller provides the same accelerator function as the conventional vehicle for an easy NEV drive.

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Maximum Torque Control of IPMSM Drive with Field Weakening Control (약계자 제어에 의한 IPMSM 드라이브의 최대토크 제어)

  • Chung, Dong-Hwa;Kim, Jong-Gwan;Park, Gi-Tae;Cha, Young-Doo
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.19 no.8
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    • pp.85-93
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    • 2005
  • Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is posed maximum torque control of IPMSM for high speed drive. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. The proposed control algorithm is applied to IPMSM drive system for high speed drive, the operating characteristics controlled by maximum torque control are examined in detail by experiment.

Efficiency Optimization Control of IPMSM Drive using Multi AFLC (다중 AFLC를 이용한 IPMSM 드라이브의 효율 최적화 제어)

  • Choi, Jung-Sik;Ko, Jae-Sub;Chung, Dong-Hwa
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.59 no.3
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    • pp.279-287
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    • 2010
  • Interior permanent magnet synchronous motor(IPMSM) adjustable speed drives offer significant advantages over induction motor drives in a wide variety of industrial applications such as high power density, high efficiency, improved dynamic performance and reliability. This paper proposes efficiency optimization control of IPMSM drive using adaptive fuzzy learning controller(AFLC). In order to optimize the efficiency the loss minimization algorithm is developed based on motor model and operating condition. The d-axis armature current is utilized to minimize the losses of the IPMSM in a closed loop vector control environment. The design of the current based on adaptive fuzzy control using model reference and the estimation of the speed based on neural network using ANN controller. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM. The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AFLC. Also, this paper proposes speed control of IPMSM using AFLC1, current control of AFLC2 and AFLC3, and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled AFLC, the operating characteristics controlled by efficiency optimization control are examined in detail.

HIPI Controller of IPMSM Drive using ALM-FNN Control (적응학습 퍼지뉴로 제어를 이용한 IPMSM 드라이브의 HIPI 제어기)

  • Kim, Do-Yeon;Ko, Jae-Sub;Choi, Jung-Sik;Jung, Chul-Ho;Jung, Byung-Jin;Chung, Dong-Hwa
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • pp.420-423
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    • 2009
  • The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

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HIPI Controller of IPMSM Drive using ALM-FNN (ALM-FNN을 이용한 IPMSM 드라이브의 HIPI 제어기)

  • Ko, Jae-Sub;Choi, Jung-Sik;Chung, Dong-Hwa
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.23 no.8
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    • pp.57-66
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    • 2009
  • The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper proposes hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme, The validity of the proposed controller is verified by results at different dynamic operating conditions.

Maximum Torque Control of IPMSM for Electric Vehicle Drive (전기자동차 구동을 위한 IPMSM의 최대 토크제어)

  • 이홍균;이정철;정동화
    • The Transactions of the Korean Institute of Power Electronics
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    • v.8 no.3
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    • pp.221-229
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    • 2003
  • Interior permanent magnet synchronous motor (IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM for electric vehicle drive. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current ${^i}_d$ for maximum torque operation is derived. The proposed control algorithm is applied to IPMSM drive system for electric vehicle drive, the operating characteristics controlled by maximum torque control are examined in detail by simulation.

Maximum Torque Control of IPMSM Drive with LM-FNN Controller (LM-FNN 제어기에 의한 IPMSM 드라이브의 최대토크 제어)

  • Nam Su-Myung;Choi Jung-Sik;Chung Dong-Hwa
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.55 no.2
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    • pp.89-97
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    • 2006
  • Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using learning mechanism-fuzzy neural network(LM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_{d}$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using LM-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using LM-FNN and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the LM-FNN and ANN controller.

Maximum Torque Control of IPMSM Drive with ALM-FNN Controller (ALM-FNN 제어기에 의한 IPMSM 드라이브의 최대토크 제어)

  • Chung, Dong-Hwa
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.55 no.3
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    • pp.110-114
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    • 2006
  • Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. In this paper maximum torque control of IPMSM drive using artificial intelligent(AI) controller is proposed. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AI controller. This paper is proposed speed control of IPMSM using adaptive learning mechanism fuzzy neural network(ALM-FNN) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled ALM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the experimental results to verify the effectiveness of AI controller.

Maximum Torque Control of IPMSM Drive with LM-FNN Controller (LM-FNN 제어기에 의한 IPMSM 드라이브의 최대토크 제어)

  • Nam, Su-Myeong;Ko, Jae-Sub;Choi, Jung-Sik;Chung, Dong-Hwa
    • Proceedings of the KIEE Conference
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    • pp.566-569
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    • 2005
  • Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using artificial intelligent(AI) controller. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AI controller. This paper is proposed speed control of IPMSM using learning mechanism fuzzy neural network(LM-FNN) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also. this paper is proposed the experimental results to verify the effectiveness of AI controller.

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