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

This paper describes the design of a linear switched reluctance motor (LSRM) for high-speed high-precision point-to-point motions. An S-shaped curve is first chosen as the trajectory motion profile and then a simple yet effective design procedure is introduced to design the motor's mechanical dimensions. Theoretical deduction and experimental results on the phase inductance and the static force generation are presented and compared with each other. The final design has a simple and robust structure. Measurements from the fabricated LSRM show that the motor has met all design specifications. The resultant LSRM is very useful in high-precision applications, especially in semiconductor fabrication machineries.

Design of a linear switched reluctance motor for high precision applications

An integrated rotary-linear machine based on switched reluctance principle is investigated. The characteristics of the motor are analyzed by finite-element methods, with particular emphasis on the coupled magnetic paths. Results from numerical calculation are verified by the hardware experiment. The simple yet effective decoupling algorithm for the independent position control of both rotary and linear axes is proposed. Implemented with the proportional-integral-differential algorithm, the motor is capable of high-precision rotary and linear position tracking with the steady error within 0.3 ° and 10 μm, respectively.

Performance Analysis and Decoupling Control of an Integrated Rotary–Linear Machine With Coupled Magnetic Paths

The coordinated tracking control for the group motion control system based on three direct-drive double-sided linear switched reluctance motors (LSRMs) is investigated in this paper. The system construction for the proposed coordinated tracking system is elaborated, including the unit system and group system design, communication configuration among unit systems, and stability and performance analysis of the group system. The coordinated control performance is concentrated on three identical LSRMs with different communication topologies. Experimental results demonstrate that necessary bidirectional interactions between the unit systems contribute to the coordination performance. The maximum dynamic tracking error within ±0.4 mm can be achieved under the sinusoidal reference of 30-mm amplitude and 0.2-Hz frequency.

Distributed Coordinated Motion Tracking of the Linear Switched Reluctance Machine-Based Group Control System

In this study, research and development of automotive active suspensions are reviewed. Structures and models of various automotive suspensions are described. Furthermore, typical commercial products of automotive suspensions are illustrated. Based on the reported studies and development, the authors discus the comparisons between various vehicular suspensions from the aspects of structure, weight, cost, ride comfort, handling performance, reliability, dynamic performance, energy recovery, and commercial maturity. Consequently, it is deduced that electromagnetic active suspensions are the future trend of automotive suspensions due to simple structure, high-bandwidth, accurate and flexible force control, high ride quality, good handling performance, and energy regeneration. At the same time, the issues of future research and development of electromagnetic active suspensions are proposed.

Study of art of automotive active suspensions

This paper proposes an efficient dynamic model for a solenoid. The magnetic characteristics in the model are based on piecewise approximation with the linear and saturation sections approximated by first order and second order functions respectively. A typical solenoid valve is used to validate the model. Preliminary results show that the model is both accurate and efficient. The model is used to design a proportional solenoid valve. >

Norbert C. Cheung

Papers

Design of a linear switched reluctance motor for high precision applications

Performance Analysis and Decoupling Control of an Integrated Rotary–Linear Machine With Coupled Magnetic Paths

Distributed Coordinated Motion Tracking of the Linear Switched Reluctance Machine-Based Group Control System

Study of art of automotive active suspensions

Modelling a linear and limited travel solenoid