The multiobjective optimization design of dual three-phase permanent magnet synchronous hub motors (PMSHMs) is challenging due to the high dimension and huge computation cost of finite-element analysis (FEA). A new multiobjective optimization strategy is proposed for dual three-phase PMSHMs in this article. All design parameters are divided into two subspaces according to the Pearson sensitivity analysis results to improve optimization efficiency. A new training method is adopted to improve the accuracy of the approximate model. By improving a multiobjective intelligent optimization algorithm, nondominated sorting genetic algorithm (NSGA) III, a new algorithm is proposed, which will greatly shorten optimization time. It is found that the proposed optimization method can significantly improve the performance, such as smaller torque ripple and higher maximum torque for the investigated PMSHM, while the computation resources are reduced. A prototype based on the optimization results is manufactured, and experiments are conducted on the platform to verify the accuracy of the optimization results and the FEA. The effectiveness of optimization and the accuracy of the simulation are verified by the experimental results. 

Sequential Subspace Optimization Design of a Dual Three-Phase Permanent Magnet Synchronous Hub Motor Based on NSGA III

The multiobjective optimization design of dual three-phase permanent magnet synchronous hub motors (PMSHMs) is challenging due to the high dimension and huge computation cost of finite-element analysis (FEA). A new multiobjective optimization strategy is proposed for dual three-phase PMSHMs in this article. All design parameters are divided into two subspaces according to the Pearson sensitivity analysis results to improve optimization efficiency. A new training method is adopted to improve the accuracy of the approximate model. By improving a multiobjective intelligent optimization algorithm, nondominated sorting genetic algorithm (NSGA) III, a new algorithm is proposed, which will greatly shorten optimization time. It is found that the proposed optimization method can significantly improve the performance, such as smaller torque ripple and higher maximum torque for the investigated PMSHM, while the computation resources are reduced. A prototype based on the optimization results is manufactured, and experiments are conducted on the platform to verify the accuracy of the optimization results and the FEA. The effectiveness of optimization and the accuracy of the simulation are verified by the experimental results.

The square-wave voltage signal injection into the estimated d-axis is an effective and novel sensorless control scheme for interior permanent magnet synchronous motor at zero speed and low speed. However, the notable acoustic and electromagnetic noises induced by the conventional fixed-frequency signal injection are very harsh and shrill to hear, which limits the practical application. Aiming at reducing unnecessary acoustic noise, a novel random voltage injection method based on the Markov chain (MC) is proposed in this article. Two high-frequency square-wave voltages with different types of frequencies and amplitudes are randomly injected into the estimated d-axis by MC rules, and this way has spread spectrum characteristics, which can effectively reduce the unnecessary noise. In addition, a new signal demodulation compensation method considering the digital delay effect in high-frequency signals is proposed, which effectively reduces the position and velocity estimation errors. Then, the power spectra density of the induced high-frequency currents under the fixed frequency injection method and the proposed MC method are compared and analyzed. The high performance of the proposed MC method has been validated by the experiment drive platform and compared with the traditional fixed frequency under different control conditions.

Novel Random Square-Wave Voltage Injection Method Based on Markov Chain for IPMSM Sensorless Control

In the low-speed operating range of sensorless interior permanent magnet synchronous motor (IPMSM), this article proposed an ultrahigh frequency (UHF) sinusoidal voltage injection method supplied by the control power supply, and the corresponding signal injection and detection system topology are designed. The proposed method replaces the traditional high-frequency injection method to continuously detect the rotor position by injecting UHF sinusoidal detection voltage into the three-phase motor windings during the main power supply (MPS) down, thereby avoiding the loss of rotor polarity information. When the MPS is restored, there is no need to wait for the convergence process of the position observer and the rotor polarity determination process. The sensorless IPMSM can immediately resume normal operation at low speed. For applications with low load inertia, the proposed method improves the rapidness of rotating restart, realizes zero-wait operation after MPS is restored, and reduces the speed drop during the power down. For electric vehicle (EV) applications, the proposed method meets the requirements of EVs event data recorder to continuously record the motor speed when the MPS is off. The experimental results verify the correctness of the theoretical analysis and the feasibility of the proposed method.

Low-Speed Rotating Restart and Speed Recording for Free-Running Sensorless IPMSM Based on Ultrahigh Frequency Sinusoidal Wave Injection

In the low-speed operating range of sensorless interior permanent magnet synchronous motor (IPMSM), this article proposed an ultrahigh frequency (UHF) sinusoidal voltage injection method supplied by the control power supply, and the corresponding signal injection and detection system topology are designed. The proposed method replaces the traditional high-frequency injection method to continuously detect the rotor position by injecting UHF sinusoidal detection voltage into the three-phase motor windings during the main power supply (MPS) down, thereby avoiding the loss of rotor polarity information. When the MPS is restored, there is no need to wait for the convergence process of the position observer and the rotor polarity determination process. The sensorless IPMSM can immediately resume normal operation at low speed. For applications with low load inertia, the proposed method improves the rapidness of rotating restart, realizes zero-wait operation after MPS is restored, and reduces the speed drop during the power down. For electric vehicle (EV) applications, the proposed method meets the requirements of EVs event data recorder to continuously record the motor speed when the MPS is <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> . The experimental results verify the correctness of the theoretical analysis and the feasibility of the proposed method. 

This article presents a new scheme to extract the rotor position angle of interior permanent magnet synchronous motors using a high-frequency signal injection method with an iterative strategy. An iterative strategy based on the binary principle is proposed to reduce the computational burden using discrete rotor position angles. These discrete rotor position angles are obtained from the angle space, which is divided into several separate sectors and employed to calculate the defined cost function that generates the optimal rotor position angle. With the number of iterations increasing, the accuracy of the iterative search strategy will increase geometrically. Finally, a series of experimental tests have been carried out to compare the performances of the proposed and the conventional low-speed sensorless methods. Experimental results have verified the effectiveness of the proposed low-speed sensorless scheme.

Finite Position Control of Interior Permanent Magnet Synchronous Motors at Low Speed

The conventional direct torque control (DTC) has high torque and stator flux fluctuation that causes the stator current distortion. This paper presents an efficient control method based on the feedback-linearization direct torque control (FL-DTC) method for an interior permanent magnet synchronous motor (IPMSM) drive by using an improved firefly algorithm. The proposed approach can greatly restrain the poor performance of torque and stator flux. Thus, it is suitable for IPMSM drives in electric vehicles. First, a decoupled linear model is derived to implement the proposed efficient feedback linearization control for the IPMSM. Two phase voltages in d-q axes and two additional control inputs take shape into an isomorphism mapping with the concept of orthogonal transformation. The torque generation is related to the additional control. Second, the Hamiltonian efficient control theory combined with an improved firefly algorithm is applied to obtain an analytical solution. An efficient linearization controller is designed with a cost function considering the maximum voltage of the inverter. Finally, simulation and experiment are carried out to compare the performance of the proposed efficient FL-DTC with the improved firefly algorithm and the conventional direct torque control. The results show that the proposed control method can reduce the torque and flux ripples at a steady state and maintains a good dynamic response with the variations of speed and torque. 

Efficient feedback linearization control for an IPMSM of EVs based on improved firefly algorithm.

Electrically excited synchronous motor (EESM) has the characteristics of high order, nonlinear and strong coupling, so it is difficult to be controlled. However, it has the advantages of adjustable power factor, high efficiency, and high precision torque control, so it is widely used in high-power applications. The accuracy of a flux observer influences the speed control system of EESM. Based on state observer in modern control theory and electrical excitation synchronous machine state equation, a reduced-order flux observer is designed. Using the first-order difference method and forward bilinear transformation method, the reduced-order flux observer is discrete, and the stability of the motor system is analyzed. The analysis shows that the stability of the system using the bilinear transformation method is better than that using the first order forward difference method. In motor operation, motor parameters will be affected by the factors of temperature, magnetic saturation, and motor frequency. In this paper, the influence of parameter variation on the motor system is studied by using the variation of the pole distribution. Finally, the speed regulation system using the reduced-order observer is simulated, which verifies the accuracy of the reduced-order flux observer observation.

Air-Gap Flux Oriented Vector Control Based on Reduced-Order Flux Observer for EESM

Electrically excited synchronous motor (EESM) is widely used in many large equipment drives because of its strong overload capacity, high efficiency, and adjustable power factor. The research and development of a high-performance EESM control system can realize the high combination of energy-saving speed regulation and green environmental protection and has a high social effect and economic value. In this paper, the signal injection method is used to obtain the initial rotor position information of EESM. Sliding Fourier transform is used to improve the initial position angle detection method based on the rotor signal injection method, and the improved method is compared with the traditional voltage integration method. Rotor high-frequency signal injection method was used to detect the rotor position information of the motor during operation, and the influence of the damping winding on the rotor signal injection method was analyzed. On the premise that the damping winding had no influence on the method, a method of obtaining the rotor position information of EESM without a speed sensor was designed. Finally, the speed sensorless regulation system using the initial rotor position detection method is simulated, which verifies the accuracy of the proposed speed sensorless control scheme.

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Speed Sensorless Control Based on Initial Rotor Position Detection for EESM

Permanent magnet synchronous hub motors (PMSHMs) have been gradually introduced into the applications of electric vehicles. On this basis, the six-phase motor has the characteristics of high reliability, high power density and low torque ripple. And its fault tolerance is a large advantage compared with the three-phase motor. The multi-phase permanent magnet synchronous motor is redundant due to the number of phases. When the motor fails, it does not have to stop running, merely adjust its control mode and enter the fault-tolerant compensation control algorithm to resume the operation of the system. The FCS-MPC algorithm can replace the cascade structure in the traditional control and eliminate the modulation module. This makes it have good steady-state performance. The speed response is also improved. It can be combined with multiple control objectives with strong flexibility by simply changing the objective function. The prediction model is compensated. Finally, the experimental results show the effectiveness of this method.

Feng Cai

Papers

Finite Position Control of Interior Permanent Magnet Synchronous Motors at Low Speed

Efficient feedback linearization control for an IPMSM of EVs based on improved firefly algorithm.

Air-Gap Flux Oriented Vector Control Based on Reduced-Order Flux Observer for EESM

Speed Sensorless Control Based on Initial Rotor Position Detection for EESM

Fault-tolerant model predictive control of six-phase permanent magnet synchronous hub motors