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.

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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.

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Controlled AC Electrical Drives

Force ripple is the main disadvantage of conventional linear switched reluctance actuators/motors (LSRAs/LSRMs). Based on finite element analysis (FEA), a new method to minimize force ripple is proposed for multimodular LSRAs/LSRMs in this paper. First, the force distribution of an LSRA/LSRM module is computed by using FEA. Then, the scheme of the spatial distribution of modules is developed. Finally, the modular spatial displacement is optimized to minimize force ripple. The computed results based on the FEA demonstrate the proposed method. The proposed method does not require any change in both module design and motor control. Thus, it is simple, cost-low, feasible, and effective.

A Novel Method to Minimize Force Ripple of Multimodular Linear Switched Reluctance Actuators/Motors

Renewable energy sources require power electronics for the power processing in order to enhance the operation and performance. In this study, a method of harnessing wind power on-board of an electric vehicle using switched reluctance generator (SRG) coupled to a wind turbine, which is mounted on the vehicle is discussed. The wind turbine integrated with SRG poses a number of challenges for vehicle application as the location and the design are special. The present investigation aims at acquiring the first hand experience in the practical implementation of such a system for on-board power generation. Various configurations of wind turbines are studied. The experimental test from a prototype is presented to validate the theoretical predictions.

Experimental examination on a new switched reluctance wind power generator system for electric vehicles

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.

Maximum-Force-per-Ampere Strategy of Current Distribution for Efficiency Improvement in Planar Switched Reluctance Motors

Linear switched reluctance actuator (LSRA) is of great potential using in kind of high-force linear applications such as automotive suspension system. In this study, an electrical controlled active suspension system is built. Bi-directional power amplifier is used to supply power to and absorb generated energy from linear actuator based on the movement requirement. The linear motions are accomplished by retracting and extending the LSRA. With regard to the established electromagnetic suspension system, a real-time control algorithm is developed. Sliding model technique with adaptive mechanism is studied to compensate the system non-linearities and external road profile. Experiments are conducted at the laboratory to present the high performance of proposed active suspension system.

Adaptive sliding mode technique-based electromagnetic suspension system with linear switched reluctance actuator

This paper presents a novel two-dimensional (2-D) planar switched reluctance motor (PSRM) for position control applications. The proposed 2-D planar motor has the advantages of simple mechanical construction, high reliability, and the ability to withstand hostile operating conditions. Due to the unique structure of the planar motor's magnetic circuit, there is very little coupling between the X- and Z-axis, and no decoupling compensation is needed. It is expected that this innovative SR planar motion system will be an ideal replacement for traditional X-Y tables in industrial automation applications

Norbert C. Cheung

Papers

A Novel Method to Minimize Force Ripple of Multimodular Linear Switched Reluctance Actuators/Motors

Experimental examination on a new switched reluctance wind power generator system for electric vehicles

Maximum-Force-per-Ampere Strategy of Current Distribution for Efficiency Improvement in Planar Switched Reluctance Motors

Adaptive sliding mode technique-based electromagnetic suspension system with linear switched reluctance actuator

A Novel Planar Switched Reluctance Motor for Industrial Applications