Low switching frequency is always used in an electric rail traction induction motor control system, in order to reduce switching losses and increase system reliability. But under low switching frequency, the conventional single pulse width modulation (PWM) technique for the whole speed region will produce a large number of harmonic components, which in turn cause motor heating, torque ripple, and other adverse effects. In this paper, a hybrid PWM technique formed by merging carrier-based asynchronous and synchronous modulation and optimal synchronous modulation is proposed to achieve low losses and total harmonics based on very low switching frequency. A simple low-cost and low-power digital signal processor (DSP) and field programmable gate array (FPGA) hybrid hardware structure is then adopted for implementing the technique, which fully utilizes advantages and resources of each processor. Total harmonic distortion of the system can hence be reduced by operating with the high-precision hybrid PWM, while not compromising the multirate and multitask processing requirements of traction control. Detailed implementations in both DSP and FPGA with high accuracy, low usage of resources, and computational burden are then described, focusing particularly at the smooth transitions among different PWM schemes. Simulations and experiments are eventually performed with results captured for validating the presented hybrid PWM technique.

This paper proposes a tightly coupled inductive power transfer (IPT) system for the low-voltage and high-current charging of automatic guided vehicles (AGVs). There are two challenges in the system design. First, the widely varying range of the airgap introduces difficulties to design the compensation circuit. Second, the low-voltage and high-current working condition introduces difficulties to maintain the system efficiency. This paper reveals that there are a large amount of high-order harmonic currents in a tightly coupled IPT system, and we have provided an effective design method to reduce the harmonics. The integrated LCC compensation circuit is selected as a solution, showing four merits: good robustness to the airgap variation, easy controllability, convenience to optimize the efficiency, and low high-order harmonics. A prototype is implemented, and the magnetic coupler size is 220 × 200 × 10 mm. Experimental results show that it achieves 1.78 kW power transfer from a 300 V dc source to a 24 V battery with 86.1% efficiency and a 73.8 A charging current across an airgap of 15 mm. When the airgap varies between 5 and 25 mm, the system power variation is within ±36.7% and the efficiency is not significantly affected.

Induction motor parameters are essential for high-performance control. However, motor parameters vary because of winding temperature rise, skin effect, and flux saturation. Mismatched parameters will consequently lead to motor performance degradation. To provide accurate motor parameters, in this paper, a comprehensive review of offline and online identification methods is presented. In the implementation of offline identification, either a DC voltage or single-phase AC voltage signal is injected to keep the induction motor standstill, and the corresponding identification algorithms are discussed in the paper. Moreover, the online parameter identification methods are illustrated, including the recursive least square, model reference adaptive system, DC and high-frequency AC voltage injection, and observer-based techniques, etc. Simulations on selected identification techniques applied to an example induction motor are presented to demonstrate their performance and exemplify the parameter identification methods.

Model predictive control, especially model predictive current control, has received a great deal of attention in the motor drive field in recent years, due to its ability to render fast dynamic response and to handle multiple variables, nonlinearities, and system constraints in an intuitive way. However, the conventional single-vector-based model predictive hysteresis current control (SV-MPHCC) brings about some problems, such as high sampling frequency and poor steady-state control performance. In this paper' a novel double-vector-based model predictive hysteresis current control (DV-MPHCC), which utilizes an arbitrary vector and a zero vector to form a voltage vector combination, is proposed. To verify the improved performance over a short predictive horizon, a series of comparisons are conducted between the two control algorithms by simulation and experiment in the paper. Both simulation and experiment results validate that the DV-MPHCC proposed has advanced steady-state control performance, and a lower sampling frequency.

Railway vehicles have been based on a wheel-rail system since the system's origination. Therefore, the adhesion-coupling behavior between wheel and rail is the fundamental element of railway traction [1]. However, low vehicle wheel-rail adhesion caused by high humidity, rain, snow, oil, or decomposing leaves is a common problem that can cause damage to some elements of the traction system and decrease traction performance [2]. It may even give rise to safety problems and reduce comfort, not to mention delays and their corresponding economic impact. Good traction control to ensure the system is working at high adhesion point is therefore critical and mandatory for the traction control units (TCUs) [2]-[6].

With increasingly prominent role of rail transit in the entire urban transport system, an auxiliary inverter is used increasingly. The complicated and fluctuating load condition of the auxiliary inverter implies special designs about structure and control strategy are necessary. For this purpose, a comprehensive control strategy is proposed. First of all, this paper proposes a structure that is capable of suppressing unbalanced voltage. Second, the control strategy based on the resonant controller is proposed, which can balance split capacitors voltage, is capable of suppressing the effect of unbalanced load and nonlinear load. This paper introduces the design method of the control system in detail. Then, this paper simulates the proposed comprehensive control strategy in MATLAB. Finally, experimental results are presented, which fully demonstrate the excellent performance of the comprehensive control strategy.