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This book provides extensive information about advanced control techniques in electric drives. Multiple control and estimation methods are studied for position and speed tracking in different drives. Artificial intelligence tools, such as fuzzy logic and neural networks, are used for specific applications using electric drives.

History of engineering & technology --- PMSM drive --- current control --- deadbeat predictive control --- equivalent input disturbance --- BSAII --- Euclidean distance --- energy management --- E-REV --- overhead transmission line --- UAV inspection --- safe distance --- multi-source data fusion --- adaptive threshold --- permanent magnet synchronous motor --- second-order sliding mode control --- cascade control --- robustness --- PMSM --- model predictive control --- parameter identification --- hybrid electric vehicles (HEVs) --- mode transition --- adaptive sliding mode control (A-SMC) --- clutch actuator --- PI observer --- fractional order proportional-integral-differential (FOPID) --- indirect vector control --- position control of motor --- induction motor --- sensorless control --- sliding mode observer --- RBFNN-based self-tuning PID controller --- I-f startup strategy --- PMLSM --- position sensorless control --- high-frequency square-wave voltage injection --- FIR filter --- maglev train --- automotive electric powertrain --- rotor position sensor --- resolver --- inductive position sensor --- eddy current position sensor --- Hall sensor --- magnetoresistive position sensor --- Hall sensors --- brushless direct current motor drive system --- power electronics --- industrial application --- integrated electric drive system --- electromechanical coupling --- harmonic torque reduction strategy --- quantized --- nonlinear systems --- time delay --- lyapunov approach --- real-time implementation --- neural fuzzy controller --- I-f control strategy --- fractional order control --- synergetic control --- sliding mode control --- motor drives --- advanced control --- power converters --- estimation --- sensor --- artificial intelligence --- PMSM drive --- current control --- deadbeat predictive control --- equivalent input disturbance --- BSAII --- Euclidean distance --- energy management --- E-REV --- overhead transmission line --- UAV inspection --- safe distance --- multi-source data fusion --- adaptive threshold --- permanent magnet synchronous motor --- second-order sliding mode control --- cascade control --- robustness --- PMSM --- model predictive control --- parameter identification --- hybrid electric vehicles (HEVs) --- mode transition --- adaptive sliding mode control (A-SMC) --- clutch actuator --- PI observer --- fractional order proportional-integral-differential (FOPID) --- indirect vector control --- position control of motor --- induction motor --- sensorless control --- sliding mode observer --- RBFNN-based self-tuning PID controller --- I-f startup strategy --- PMLSM --- position sensorless control --- high-frequency square-wave voltage injection --- FIR filter --- maglev train --- automotive electric powertrain --- rotor position sensor --- resolver --- inductive position sensor --- eddy current position sensor --- Hall sensor --- magnetoresistive position sensor --- Hall sensors --- brushless direct current motor drive system --- power electronics --- industrial application --- integrated electric drive system --- electromechanical coupling --- harmonic torque reduction strategy --- quantized --- nonlinear systems --- time delay --- lyapunov approach --- real-time implementation --- neural fuzzy controller --- I-f control strategy --- fractional order control --- synergetic control --- sliding mode control --- motor drives --- advanced control --- power converters --- estimation --- sensor --- artificial intelligence

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book provides extensive information about advanced control techniques in electric drives. Multiple control and estimation methods are studied for position and speed tracking in different drives. Artificial intelligence tools, such as fuzzy logic and neural networks, are used for specific applications using electric drives.

History of engineering & technology --- PMSM drive --- current control --- deadbeat predictive control --- equivalent input disturbance --- BSAII --- Euclidean distance --- energy management --- E-REV --- overhead transmission line --- UAV inspection --- safe distance --- multi-source data fusion --- adaptive threshold --- permanent magnet synchronous motor --- second-order sliding mode control --- cascade control --- robustness --- PMSM --- model predictive control --- parameter identification --- hybrid electric vehicles (HEVs) --- mode transition --- adaptive sliding mode control (A-SMC) --- clutch actuator --- PI observer --- fractional order proportional-integral-differential (FOPID) --- indirect vector control --- position control of motor --- induction motor --- sensorless control --- sliding mode observer --- RBFNN-based self-tuning PID controller --- I-f startup strategy --- PMLSM --- position sensorless control --- high-frequency square-wave voltage injection --- FIR filter --- maglev train --- automotive electric powertrain --- rotor position sensor --- resolver --- inductive position sensor --- eddy current position sensor --- Hall sensor --- magnetoresistive position sensor --- Hall sensors --- brushless direct current motor drive system --- power electronics --- industrial application --- integrated electric drive system --- electromechanical coupling --- harmonic torque reduction strategy --- quantized --- nonlinear systems --- time delay --- lyapunov approach --- real-time implementation --- neural fuzzy controller --- I-f control strategy --- fractional order control --- synergetic control --- sliding mode control --- motor drives --- advanced control --- power converters --- estimation --- sensor --- artificial intelligence

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This Special Issue deals with improvements in the energy efficiency of electric devices, machines, and drives, which are achieved through improvements in the design, modelling, control, and operation of the system. Properly sized and placed coils of a welding transformer can reduce the required iron core size and improve the efficiency of the welding system operation. New structures of the single-phase field excited flux switching machine improve its performance in terms of torque, while having higher back-EMF and unbalanced electromagnetic forces. A properly designed rotor notch reduces the torque ripple and cogging torque of interior permanent magnet motors for the drive platform of electric vehicles, resulting in lower vibrations and noise. In the field of modelling, the torque estimation of a Halbach array surface permanent magnet motor with a non-overlapping winding layout was improved by introducing an analytical two-dimensional subdomain model. A general method for determining the magnetically nonlinear two-axis dynamic models of rotary and linear synchronous reluctance machines and synchronous permanent magnet machines is introduced that considers the effects of slotting, mutual interaction between the slots and permanent magnets, saturation, cross saturation, and end effects. Advanced modern control solutions, such as neural network-based model reference adaptive control, fuzzy control, senseless control, torque/speed tracking control derived from the 3D non-holonomic integrator, including drift terms, maximum torque per ampere, and maximum efficiency characteristics, are applied to improve drive performance and overall system operation.

History of engineering & technology --- interior permanent magnet synchronous motor --- torque ripple --- cogging torque --- electric vehicle --- notch --- mathematical model --- Halbach Array --- surface permanent magnet --- magnetic vector potential --- torque --- in-wheel electric vehicle --- independent 4-wheel drive --- torque distribution --- fuzzy control --- traction control --- active yawrate control --- energy efficiency --- industry --- water circuits --- OpenModelica --- optimisation --- induction motor --- speed estimation --- model reference adaptive system --- kalman filter --- luenberger observer --- flux switching machine --- modular rotor --- non-overlap winding --- magnetic flux analysis --- iron losses --- copper loss --- stress analysis --- finite element method --- magnetic loss --- maximum efficiency (ME) characteristic --- maximum torque per ampere (MTPA) characteristic --- modeling --- permanent magnet synchronous machine (PMSM) --- sensorless control --- synchronous machines --- dynamic models --- nonlinear magnetics --- parameter estimation --- DC-DC converter --- resistance spot welding --- transformer --- efficiency --- dynamic power loss --- design --- induction machines --- nonlinear control --- torque/speed control --- interior permanent magnet synchronous motor --- torque ripple --- cogging torque --- electric vehicle --- notch --- mathematical model --- Halbach Array --- surface permanent magnet --- magnetic vector potential --- torque --- in-wheel electric vehicle --- independent 4-wheel drive --- torque distribution --- fuzzy control --- traction control --- active yawrate control --- energy efficiency --- industry --- water circuits --- OpenModelica --- optimisation --- induction motor --- speed estimation --- model reference adaptive system --- kalman filter --- luenberger observer --- flux switching machine --- modular rotor --- non-overlap winding --- magnetic flux analysis --- iron losses --- copper loss --- stress analysis --- finite element method --- magnetic loss --- maximum efficiency (ME) characteristic --- maximum torque per ampere (MTPA) characteristic --- modeling --- permanent magnet synchronous machine (PMSM) --- sensorless control --- synchronous machines --- dynamic models --- nonlinear magnetics --- parameter estimation --- DC-DC converter --- resistance spot welding --- transformer --- efficiency --- dynamic power loss --- design --- induction machines --- nonlinear control --- torque/speed control

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This Special Issue deals with improvements in the energy efficiency of electric devices, machines, and drives, which are achieved through improvements in the design, modelling, control, and operation of the system. Properly sized and placed coils of a welding transformer can reduce the required iron core size and improve the efficiency of the welding system operation. New structures of the single-phase field excited flux switching machine improve its performance in terms of torque, while having higher back-EMF and unbalanced electromagnetic forces. A properly designed rotor notch reduces the torque ripple and cogging torque of interior permanent magnet motors for the drive platform of electric vehicles, resulting in lower vibrations and noise. In the field of modelling, the torque estimation of a Halbach array surface permanent magnet motor with a non-overlapping winding layout was improved by introducing an analytical two-dimensional subdomain model. A general method for determining the magnetically nonlinear two-axis dynamic models of rotary and linear synchronous reluctance machines and synchronous permanent magnet machines is introduced that considers the effects of slotting, mutual interaction between the slots and permanent magnets, saturation, cross saturation, and end effects. Advanced modern control solutions, such as neural network-based model reference adaptive control, fuzzy control, senseless control, torque/speed tracking control derived from the 3D non-holonomic integrator, including drift terms, maximum torque per ampere, and maximum efficiency characteristics, are applied to improve drive performance and overall system operation.

History of engineering & technology --- interior permanent magnet synchronous motor --- torque ripple --- cogging torque --- electric vehicle --- notch --- mathematical model --- Halbach Array --- surface permanent magnet --- magnetic vector potential --- torque --- in-wheel electric vehicle --- independent 4-wheel drive --- torque distribution --- fuzzy control --- traction control --- active yawrate control --- energy efficiency --- industry --- water circuits --- OpenModelica --- optimisation --- induction motor --- speed estimation --- model reference adaptive system --- kalman filter --- luenberger observer --- flux switching machine --- modular rotor --- non-overlap winding --- magnetic flux analysis --- iron losses --- copper loss --- stress analysis --- finite element method --- magnetic loss --- maximum efficiency (ME) characteristic --- maximum torque per ampere (MTPA) characteristic --- modeling --- permanent magnet synchronous machine (PMSM) --- sensorless control --- synchronous machines --- dynamic models --- nonlinear magnetics --- parameter estimation --- DC-DC converter --- resistance spot welding --- transformer --- efficiency --- dynamic power loss --- design --- induction machines --- nonlinear control --- torque/speed control

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This Special Issue deals with improvements in the energy efficiency of electric devices, machines, and drives, which are achieved through improvements in the design, modelling, control, and operation of the system. Properly sized and placed coils of a welding transformer can reduce the required iron core size and improve the efficiency of the welding system operation. New structures of the single-phase field excited flux switching machine improve its performance in terms of torque, while having higher back-EMF and unbalanced electromagnetic forces. A properly designed rotor notch reduces the torque ripple and cogging torque of interior permanent magnet motors for the drive platform of electric vehicles, resulting in lower vibrations and noise. In the field of modelling, the torque estimation of a Halbach array surface permanent magnet motor with a non-overlapping winding layout was improved by introducing an analytical two-dimensional subdomain model. A general method for determining the magnetically nonlinear two-axis dynamic models of rotary and linear synchronous reluctance machines and synchronous permanent magnet machines is introduced that considers the effects of slotting, mutual interaction between the slots and permanent magnets, saturation, cross saturation, and end effects. Advanced modern control solutions, such as neural network-based model reference adaptive control, fuzzy control, senseless control, torque/speed tracking control derived from the 3D non-holonomic integrator, including drift terms, maximum torque per ampere, and maximum efficiency characteristics, are applied to improve drive performance and overall system operation.

interior permanent magnet synchronous motor --- torque ripple --- cogging torque --- electric vehicle --- notch --- mathematical model --- Halbach Array --- surface permanent magnet --- magnetic vector potential --- torque --- in-wheel electric vehicle --- independent 4-wheel drive --- torque distribution --- fuzzy control --- traction control --- active yawrate control --- energy efficiency --- industry --- water circuits --- OpenModelica --- optimisation --- induction motor --- speed estimation --- model reference adaptive system --- kalman filter --- luenberger observer --- flux switching machine --- modular rotor --- non-overlap winding --- magnetic flux analysis --- iron losses --- copper loss --- stress analysis --- finite element method --- magnetic loss --- maximum efficiency (ME) characteristic --- maximum torque per ampere (MTPA) characteristic --- modeling --- permanent magnet synchronous machine (PMSM) --- sensorless control --- synchronous machines --- dynamic models --- nonlinear magnetics --- parameter estimation --- DC-DC converter --- resistance spot welding --- transformer --- efficiency --- dynamic power loss --- design --- induction machines --- nonlinear control --- torque/speed control