Search

Connected and automated vehicles have attracted more and more attention, given the benefits in safety and efficiency. This research proposes a novel model predictive control method in order to improve energy efficiency and ensure a safe spacing between vehicles. The proposed algorithm focuses on mixed traffic flow, which is more realistic than one that only includes autonomous vehicles. A high-fidelity energy loss model of an electric vehicle is adopted to improve the control's performance. A data-driven car-following model using machine learning is integrated in the framework of model predictive control to predict the behavior of human-driven vehicles. Its effectiveness in increasing energy efficiency is validated under two driving cycles. In the case of the scaled urban dynamometer driving schedule, the energy loss and the maximum spacing between the autonomous vehicle and the human-driven vehicle decreases by 6% and 18%, respectively, when compared with the baseline model predictive control without the consideration of interaction between the autonomous vehicle and the human-driven vehicle. In the scenario of the scaled city driving cycle, the energy loss of the autonomous vehicles also reduces by 3%, while the maximum and average spacing does not change significantly. The sensitivity of the optimization results to several parameters of the energy loss model is finally analyzed, and the robustness of the proposed algorithm is validated. [ABSTRACT FROM AUTHOR]

We present a model suitable for use in a vector control algorithm for synchronous reluctance machines with solid conducting rotors. The model takes the rotor flux dynamics into consideration. It is similar to an induction machine model, yet includes a magnetic saliency of the rotor. Here, we discuss techniques for parameter extraction and suggest a modification of the model to incorporate the nonlinear magnetic phenomena. We also investigate the influence of nonlinear magnetics on the model-based controller. Our model yields improved performance for a fast-changing torque command compared to the conventional model when utilized in a current regulator. Experimental results on a 120 kW, 55 000 rpm machine in a flywheel energy storage system validate the performance of the proposed model. Index Terms--Flux dynamics, nonlinear modeling, remanent magnetization, solid rotor, synchronous reluctance motor.

A hybrid controller, consisting of a model-based feedforward controller and a proportional--integral feedback compensator, for a solid-rotor synchronous reluctance motor/generator in a high-speed flywheel-based uninterruptible power supply application is proposed in this paper. The feedforward controller takes most of the control output of the current regulator based on the machine model, and the PI controllers compensate the possible inaccuracies of the model to improve the performance and robustness of the complete control system. The machine current tracking error caused by parameter inaccuracy in the model-based controller is mathematically analyzed and utilized to dynamically compensate the estimated flux linkage to eliminate the steady-state error in current regulation. Stability analysis is also presented, and it can be seen that the regulation performance and robustness of the system are improved by the proposed hybrid controller. Simulation and experimental results consisting of a flywheel energy storage system validates the performance of the controller. Index Terms--Flywheel, model-based control, synchronous reluctance motor, uninterruptible power supply (UPS).

Synchronous reluctance machines with solid rotor construction have advantages in certain high-speed applications such as flywheel energy storage systems. However, the solid rotor allows the flow of eddy currents, resulting in rotor loss and heat generation. The switching harmonics in the stator voltage supplied by a pulsewidth modulation (PWM) inverter are one of the sources of the rotor loss. This paper performs an analysis for the time harmonic loss in a solid-rotor synchronous reluctance machine, and investigates design and control issues associated with the inclusion of a three-phase LC filter for reduction of the rotor loss in solid rotor. A two-phase dynamic model of the machine which incorporates the LC filter dynamics is presented. This model is used to predict rotor losses due to switching harmonics generated by the three-phase PWM inverter. A model-based current regulator is utilized, which is modified to include the effects of the LC filter. Experimental results validate the proposed approach. Index Terms--filters, flywheels, harmonic analysis, losses, reluctance machines.

We present a magnetostatic continuum formulation for computing the magnetic fields and flux densities in permanent-magnet machine designs. This formulation offers certain advantages over traditional closed-form solutions and finite-element analysis. Our formulation is numerically robust. It models the tooth/winding region of the machine by using anisotropic permeability. Here, we derive spatial harmonics associated with the stator current density and rotor magnetization. We provide techniques to compute average flux density in the stator and rotor backirons and the stator teeth, and to calculate electromagnetic torque. The continuum formulation results compare well with those of finite-element analysis. Index Terms--Magnetic analysis, permanent-magnet machines.

A speed-estimation technique for induction machines, based on carrier signal injection and the standard two-axis smooth-air-gap induction machine model, is presented. The proposed speed-estimation technique can work over a wide range of operating points, including fundamental de excitation. The stability of the algorithm is analyzed using a two-time-scale approach. Based on the estimated rotor speed, a torque controller is designed. Experimental results are presented confirming the validity of this approach. A method to reduce torque ripple generated by the injected carrier signals is also introduced. Index Terms--Carrier signal injection, induction motor drives, speed sensorless, torque control.

The energy harvesting is investigated using 1-3 composites of PMN-PT single crystals in a soft epoxy matrix. It is shown that 1-3 composites enable the single crystals operating in the longitudinal mode to achieve high efficiency for energy harvesting, and the soft-polymer, matrix-supported single-crystal rods maintain high mechanical integrity under different external loads.

The mechanical and electrical boundary conditions for maximizing the energy harvesting density and mechanical-to-electrical coupling of electrostrictive materials are discussed. The comparison with a magnetic-based energy harvesting system shows that electrostrictive energy harvesting systems are preferable for small energy harvesting applications with low-frequency excitation.

This paper presents a position-sensorless vector torque controller designed to achieve maximum efficiency over a range of power and rotational speed for a synchronous reluctance machine. A model of the synchronous reluctance machine is presented which incorporates both winding and core losses. It is then shown that a stator-flux-oriented control scheme can achieve synchronous operation of the machine without a position sensor at medium and high electrical frequencies. For a given speed and torque, power losses in the machine are shown to be a function of only the stator flux magnitude. As the power losses are a convex function of the stator flux level, the optimal flux value can be found using a one-dimensional optimization algorithm, such as the Method of Sequential Quadratic Interpolations. Optimal flux values for a synchronous reluctance machine are determined using an experimental setup that accurately determines losses in the motor/drive system. Experimental results obtained from the test setup confirm the validity of the controller and the optimization algorithm. Index Terms--Field-oriented control (FOC), optimal control, synchronous reluctance machine.

This paper presents a two-dimensional steady-state finite-element solver, incorporating mechanical motion, that calculates eddy-current losses in the rotors of permanent-magnet machines. A shooting-Newton method is used to determine the periodic solution of the electromagneties. Computation of the shooting-Newton Jacobian is avoided by using a generalized minimum residual (GMRES) linear solver. This method is more computationally efficient than performing transient analysis until convergence. The solver can be used to compare the rotor losses of different design choices for a high-speed permanent-magnet machine. Results show that rotor losses can be reduced significantly by laminating the rotor backiron, segmenting the permanent-magnet poles, increasing the number of stator slots, and closing the stator slots. Index Terms--Electromechanical steady-state analysis, finite- element methods, generalized minimum residual (GMRES) method, permanent-magnet synchronous machines, rotor losses.

We present a numerically efficient steady-state finite-element solver for electromechanical devices incorporating magnetic saturation in which the magnetization of ferromagnetic materials is modeled as a field-dependent equivalent current density. We use a Lagrangian representation of continuum variables, thereby removing numerical instabilities due to the Peclet effect but precluding the use of standard harmonic balance methods. The shooting-Newton method is therefore used to calculate the steady-state behavior. A matrix-free Krylov-subspace linear solver, the generalized minimum residuals method (GMRES), dramatically reduces the computational burden by eliminating the need to calculate the shooting-Newton Jacobian. Simulation results from a synchronous reluctance motor model with 10 288 nodes and 4935 elements confirm that the proposed method requires much less computation time than running transient analysis until convergence. Index Terms--Electromechanical steady-state analysis, finite-element analysis, generalized minimum residuals method (GMRES), magnetic saturation.

An optimized method of harvesting vibrational energy with a piezoelectric element using a step-down dc-dc converter is presented. In this configuration, the converter regulates the power flow from the piezoelectric element to the desired electronic load. Analysis of the converter in discontinuous current conduction mode results in an expression for the duty cycle-power relationship. Using parameters of the mechanical system, the piezoelectric element, and the converter; the 'optimal' duty cycle can be determined where the harvested power is maximized for the level of mechanical excitation. It is shown that, as the magnitude of the mechanical excitation increases, the optimal duty cycle becomes essentially constant, greatly simplifying the control of the step-down converter. The expression is validated with experimental data showing that the optimal duty cycle can be accurately determined and maximum energy harvesting attained. A circuit is proposed which implements this relationship, and experimental results show that the converter increases the harvested power by approximately 325%. Index Terms--DC-DC, discontinuous conduction mode, energy harvesting, piezoelectric devices.