In this paper, a high-power high-efficiency wireless-power-transfer system using the class-E operation for transmitter via inductive coupling has been designed and fabricated using the proposed design approach. The system requires no complex external control system but relies on its natural impedance response to achieve the desired power-delivery profile across a wide range of load resistances while maintaining high efficiency to prevent any heating issues. The proposed system consists of multichannels with independent gate drive to control power delivery. The fabricated system is compact and capable of 295 W of power delivery at 75.7% efficiency with forced air cooling and of 69 W of power delivery at 74.2% efficiency with convection cooling. This is the highest power and efficiency of a loosely coupled planar wireless-power-transfer system reported to date.

Design and Test of a High-Power High-Efficiency Loosely Coupled Planar Wireless Power Transfer System

This paper presents a critical review of the drivelines in all-electric vehicles (EVs). The motor topologies that are the best candidates to be used in EVs are presented. The advantages and disadvantages of each electric motor type are discussed from a system perspective. A survey of the electric motors used in commercial EVs is presented. The survey shows that car manufacturers are very conservative when it comes to introducing new technologies. Most of the EVs on the market mount a single induction or permanent-magnet (PM) motor with a traditional mechanic driveline with a differential. This paper illustrates that comparisons between the different motors are difficult by the large number of parameters and the lack of a recommended test scheme. The authors propose that a standardized drive cycle be used to test and compare motors.

/pdf/electrical-motor-drivelines-in-commercial-all-electric-1ho8rutglq.pdf

Electrical Motor Drivelines in Commercial All-Electric Vehicles: A Review

In this paper, a dynamic surface control (DSC) scheme is proposed for a class of uncertain strict-feedback nonlinear systems in the presence of input saturation and unknown external disturbance. The radial basis function neural network (RBFNN) is employed to approximate the unknown system function. To efficiently tackle the unknown external disturbance, a nonlinear disturbance observer (NDO) is developed. The developed NDO can relax the known boundary requirement of the unknown disturbance and can guarantee the disturbance estimation error converge to a bounded compact set. Using NDO and RBFNN, the DSC scheme is developed for uncertain nonlinear systems based on a backstepping method. Using a DSC technique, the problem of explosion of complexity inherent in the conventional backstepping method is avoided, which is specially important for designs using neural network approximations. Under the proposed DSC scheme, the ultimately bounded convergence of all closed-loop signals is guaranteed via Lyapunov analysis. Simulation results are given to show the effectiveness of the proposed DSC design using NDO and RBFNN.

Dynamic Surface Control Using Neural Networks for a Class of Uncertain Nonlinear Systems With Input Saturation

In this paper, the direct adaptive neural control is proposed for a class of uncertain nonaffine nonlinear systems with unknown nonsymmetric input saturation. Based on the implicit function theorem and mean value theorem, both state feedback and output feedback direct adaptive controls are developed using neural networks (NNs) and a disturbance observer. A compounded disturbance is defined to take into account of the effect of the unknown external disturbance, the unknown nonsymmetric input saturation, and the approximation error of NN. Then, a disturbance observer is developed to estimate the unknown compounded disturbance, and it is established that the estimate error converges to a compact set if appropriate observer design parameters are chosen. Both state feedback and output feedback direct adaptive controls can guarantee semiglobal uniform boundedness of the closed-loop system signals as rigorously proved by Lyapunov analysis. Numerical simulation results are presented to illustrate the effectiveness of the proposed direct adaptive neural control techniques.

Direct Adaptive Neural Control for a Class of Uncertain Nonaffine Nonlinear Systems Based on Disturbance Observer

The use of AC electrical machines in controlled electrical drive applications is reviewed. The major types of electrical machines are briefly summarized to set the context and establish the physical basis for the control techniques used. Machine properties, which are the key to successful control, can be obscured by the necessary mathematics required for machine analysis and control scheme derivations. The main focus of this paper is on control techniques which are being applied to make AC drives a rapidly growing area. Development of the control is discussed, with concentration on recent trends suitable for practical applications in the industry with good dynamic behavior. A particular feature is the increasing importance of speed or position sensorless techniques.

/pdf/controlled-ac-electrical-drives-1ttwuo7kop.pdf

Controlled AC Electrical Drives

The method of the optimization design with multi-objectives for switched reluctance motors (SRMs) in electric vehicles (EVs) is proposed in this paper. It is desired that electric motors for EVs have high torque, high efficiency, and high torque density. Thus, the developed optimization function is selected as the correct compromise between the maximum average torque, maximum average torque per copper loss, and maximum average torque per motor lamination volume, by using three weight factors and three base values. The stator and rotor pole arc angles are selected as the optimized variables. Furthermore, the authors also discuss the design requirements and some constraints on the optimization design. The results of the optimization design show that the proposed method meets the requirements of EVs on electric motors well. A prototype of the optimally designed in-wheel SRM for EVs has been manufactured. This paper provides a valuable method to implement the optimal design of SRMs for EVs.

Multi-Objective Optimization Design of In-Wheel Switched Reluctance Motors in Electric Vehicles

In this study, six kinds of the drivetrain systems of electric motor drives for EVs are discussed. Furthermore, the requirements of EVs on electric motor drives are presented. The comparative investigation on the efficiency, weight, cost, cooling, maximum speed, and fault-tolerance, safety, and reliability is carried out for switched reluctance motor, induction motor, permanent magnet blushless DC motor, and brushed DC motor drives, in order to find most appropriate electric motor drives for electric vehicle applications. The study shows that switched reluctance motor drives are the prior choice for electric vehicles.

Selection of eLECTRIC mOTOR dRIVES for electric vehicles

This paper presents three criteria for evaluating the motoring operations of switched reluctance motor (SRM) drives for electric vehicles (EVs). They imply motoring torque, copper loss, and torque ripple, respectively. The effects of the turn-off and turn-on angles on these criteria are investigated under hysteresis current control. To fulfill the best motoring operation, consequently, the multiobjective optimization function is developed by using three weight factors and three groups of base values: the correct balance between the maximum average torque, the maximum average torque per root mean square current, and the maximum torque smoothness factor. The study in this paper shows that the turn-off and the turn-on angles can be optimized to maximize the developed multiobjective function. In addition, the control method for the best motoring operation of SRM drives in EVs is proposed. In this method, two angular controllers are proposed to automatically tune the turn-off and turn-on angles to obtain high motoring torque, low copper loss, and low torque ripple. Simulations and experimental results have demonstrated the proposed optimal control method. Therefore, this paper offers a valuable and feasible approach for implementing the best motoring operation of SRM drives for EVs.

Optimal Control Method of Motoring Operation for SRM Drives in Electric Vehicles

An integral sliding-mode direct torque control (ISM-DTC) scheme with space-vector modulation for wind-energy conversion systems based on doubly-fed induction generators (DFIGs) under unbalanced grid voltage is proposed. The torque and power pulsations at twice the grid frequency caused by unbalanced grid voltage can be minimized by the proposed ISM-DTC scheme. Compared with existing control schemes of DFIGs under unbalanced grid voltage, the parametric uncertainties are included into the design procedure of sliding-mode controller, which guarantees the robustness of the controller. Because the torque and reactive power are directly controlled by the rotor voltage, the measurement, coordinate transformation, and symmetrical component extraction of rotor current are eliminated, which simplifies the structure of the controller. Simulation and hardware implementation results validate the effect and parametric robustness of the proposed ISM-DTC scheme.

Integral Sliding-Mode Direct Torque Control of Doubly-Fed Induction Generators Under Unbalanced Grid Voltage

This paper describes a novel method of estimating the position of a plunger inside a solenoid. The solenoid is a single-phase variable reluctance actuator, with a highly nonlinear magnetic circuit. For the proposed method, position is estimated indirectly through the solenoid's incremental inductance in the high current region. It exploits the advantage that motional electromotive force (EMF) is negligible under normal operating condition. The incremental inductance is obtained from the rate of current rise of the pulse-width modulated (PWM) waveform, which in turn, is measured by a dedicated current rise measurement circuit. Position is estimated from a two-dimensional look-up table of incremental inductance and current. The method is simulated and then implemented on a typical industrial solenoid valve. Factors which affect the accuracy of the estimation and methods of overcoming them are also described in the paper.

Norbert C. Cheung

Papers

Multi-Objective Optimization Design of In-Wheel Switched Reluctance Motors in Electric Vehicles

Selection of eLECTRIC mOTOR dRIVES for electric vehicles

Optimal Control Method of Motoring Operation for SRM Drives in Electric Vehicles

Integral Sliding-Mode Direct Torque Control of Doubly-Fed Induction Generators Under Unbalanced Grid Voltage

Position estimation in solenoid actuators