励磁区間可変シングルパルス制御によるスイッチトリラクタンスモータの効率向上に関する検討

The problems of vibration noise and torque ripple limit the application of switched reluctance motors (SRMs). Previously various efforts for these two aspects are isolated. A novel fixed-frequency control method that can both decrease the vibration and the torque ripple simultaneously is presented in this paper, by introducing the two-step and three-step commutation methods into the improved direct instantaneous torque control (IDITC). The vibrations can be effectively suppressed under various operation modes, including chopping control and single pulse control, by adopting the novel control method. Furthermore, the novel control method minimizes the torque ripple under the torque chopping status. The design of time parameters of the three-step commutation method is also proposed in this paper. The experimental results verify the validity of this novel control method

A sensorless control strategy with one-phase lacking fault-tolerant capability is proposed in this paper for the switched reluctance motors (SRM). This strategy consists of a phase inductance slope zero-crossing detection scheme and a series of phase inductance partition logic algorithms, which is capable of capturing at least one-phase aligned position under both normal operation and one-phase lacking fault operation. With the recorded index position in each electric period, the rotor position can be estimated for sensorless driving accordingly. To ensure stable calculation of the phase inductance in this method, the SRM should be started and operated under single pulse control mode. Thus, for sensorless starting, an idle phase inductance double thresholds based sensorless synthetic starting scheme is also developed. The proposed strategy is easy for implementation and can ensure stable sensorless operation in full speed range. Moreover, it does not need any prior measuring process, complicated logic algorithm, or complex mathematical calculation. The theoretical analysis is conducted, and experimental results are provided to verify the feasibility of the proposed control strategy.

This paper presents efficiency optimization of switched reluctance motor based on genetic algorithm optimization technique. Switched reluctance motor (SRM) is considered for various applications due to its simple and robust construction. It is very essential to improve efficiency of switched reluctance motor. In this paper, optimization of 8/6 switched reluctance motor is achieved by using genetic algorithm with efficiency as its objective function. The objective of the paper is to identify the best switched reluctance motor design that provides better efficiency to satisfy the unique requirements of various applications. Using finite element analysis, a design validation of motor and characterization was made. It is analyzed that analytical results and simulation results are very close which establishes correctness of designs. The optimization result shows that the newly developed SRM design achieved better efficiency. The efficiency is increased from 82.75 % to 86.19 % with minor increase in weight. Improvement in efficiency can lead to lower energy usage, longer motor life span, and better performance.

In order to produce high-efficiency motors at relatively low production costs, a layered block is made from amorphous iron sheets. From the block, stator and rotor cores of a test switched reluctance motor (SRM) are fabricated. The experimental results of the test machine are compared to another test machine made from low iron loss silicon steel type 35A300 in JIS standard. This silicon steel is equivalent to M-22, 300, and V300-35A in ANSI, BS601, and DIN46400, respectively. The validity of the test results is compared and verified through use of an analytical simulation software package. Approximately 6% improvement in efficiency is observed for the prototype SRM with the layered amorphous core material. The SRM test motor has an efficiency of 95.1% at a speed of 8500 r/min with an output of 2.4 kW.

A current controlled switched reluctance motor (SRM) drive for variable speed applications with efficiency optimization is presented. A robust, modular and flexible prototyping SRM drives is proposed. It is composed of a power electronic block, a driver board, a measurement and interface board and a DSP controller board. Firing angles are computed online, the turn-on is calculated by means of the Boses rule, and the turn-off is calculated using the general theory of the optimal turn-off angle proposed by Gribble. In steady state operation, tie initial selection of firing angles is fine-tuned by means of an algorithm that minimizes the input power of the drive. A 6/4 switched reluctance motor drive prototype was tested and the experimental results show an improvement in online efficiency, a good steady-state performance and no deterioration in the dynamic response. An efficiency comparison with a commercial vector-controlled induction motor drive of the same size is also included.

A main source producing noise and vibration in a switched reluctance motor is time variation of radial force acting on stator tooth during excitation period. Based on this principle, two different control are examined and compared in this paper. One is two-stage commutation method well-known as active vibration cancellation technique and the other is flux profiling control. The flux profiling control proposed in this study considers an increased degree of freedom of flux profile with superposition of lower order harmonics. The parameters for flux profile are optimized by genetic algorithm to minimize vibration and acoustic noise while keeping target torque and minimizing power loss as well as torque ripple. Experimental studies on drive performance comparisons under different control using 50kW three-phase 18/12 test motor are carried out. As a result, the proposed control employing the optimized flux profile works better than the conventional two stage commutation method in terms of higher motor efficiency, reduced noise and vibration, and less torque pulsation.

In this paper, a selection of a few current references for acoustic noise reduction in the 36–24 and the 18–12 switched reluctance motors is presented. It is seen that the difference in radial force profile results in few optimal current references. It is found that the optimal current reference with extreme radial force sum flattening results in increased rms current and loss in a magnetically saturated region of the 18–12 SRM. Thus, proper selection of the current references is necessary. Analysis, simulation, and experimental results are presented with the conventional and optimal currents to verify the effectiveness of flattening radial force sum method in acoustic noise reduction. It is shown that effective acoustic noise reduction and efficiency improvement are confirmed with proposed current reference selection.

An enhanced direct instantaneous torque control of switched reluctance motor drives using ant colony optimization

Multi- objective optimization of switched reluctance motor drive in electric vehicles

Vibration power generation is an important issue in development of renewable energy. If a vibration system with a maximum possible amplitude is designed, it can be advantageous in improving the vibration power generation efficiency. In this study, we propose a Duffing-type bi-stable vibration energy harvesting system that utilizes the stochastic resonance phenomenon, which can significantly expand the vibration amplitude. We designed the motion rail shape of the bistable vibration model using the Duffing function, and created a Duffing-type wave-shaped motion rail using an acrylic plate. An electromagnetic motor was installed in place of the four rotating wheels below the mass block that moves on the wave-shaped motion rail. When the mass block moves on the rail, it can output a voltage directly from the electromagnetic motor. To verify the performance of the proposed bi-stable vibration energy-harvesting system, a vibration experiment was conducted by combining a random excitation signal that simulates an actual natural environment and intentional periodic excitation signal. Using the experimental results, the stochastic resonance phenomenon and vibration power generation performance of the bi-stable vibration energy-harvesting system were investigated. The stochastic resonance phenomenon can be reliably generated using the bi-stable vibration system proposed in this study, and a large amplitude expansion effect can be obtained in the response vibration of the mass block. In addition, using random signals simulating the natural environment and periodic signals as stimulus signals, vibration experiments were conducted separately for two measurement cases: single excitation and joint excitation. The measurement results showed that under the same input excitation energy, the simultaneous excitation of the two signals generated 82.99% more power than that generated by separate excitation of the two signals. The generation of the stochastic resonance phenomenon by exciting two signals simultaneously has a significant effect on the improvement of the power generation efficiency of the bi-stable vibration energy harvesting system.

This paper proposes a novel maximum-force-per-ampere strategy for the current distribution of planar switched reluctance motors (PSRMs) for efficiency improvement. This strategy is the first of its kind for planar motors, and it is used to generate the desired thrust force with the minimum sum of squares of the three-phase current. To formulate this strategy, a constrained optimization problem with time-varying parameters is first developed. Then, the problem is transformed into an unconstrained problem with a barrier function. Additionally, a self-designed adaptive genetic algorithm is introduced to solve the unconstrained optimization problem for locating the optimal currents. Comparative studies of the proposed and conventional strategies for a PSRM system are carried out via simulation and experiment, and planar trajectory tracking for the system with the proposed strategy is experimentally performed. The validity of the proposed strategy is also verified.