Time filter

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Holland, MI, United States

Zhang Z.,Nexteer Automotive | Wei C.,University of Nebraska - Lincoln | Qiao W.,University of Nebraska - Lincoln | Qu L.,University of Nebraska - Lincoln
IEEE Transactions on Power Electronics | Year: 2016

This paper proposes a novel direct torque control (DTC) scheme for permanent-magnet synchronous motor (PMSM) drives using a relatively low sampling frequency. Unlike the conventional DTC in which a single voltage vector is selected according to the outputs of the hysteresis controllers, the proposed DTC uses nonlinear adaptive-midpoint saturation controllers to regulate the torque and flux tracking errors and determine the durations of multiple voltage vectors which are selected from a new switching table. The proposed DTC naturally inherits most intrinsic merits of the conventional DTC, e.g., fast dynamics, robust to disturbances, no coordinate transformation, etc. Meanwhile, the steady-state torque and flux ripples which afflict the conventional DTC are significantly reduced. Moreover, by adjusting the midpoints of the saturation controllers adaptively, the steady-state torque tracking error, which is a common issue in the DTC schemes particularly when the sampling frequency is relatively low, is fully eliminated. The effectiveness of the proposed adaptive saturation controller-based DTC is verified by experimental results on a 180-W PMSM drive system. © 1986-2012 IEEE.

Wei C.,University of Nebraska - Lincoln | Zhang Z.,Nexteer Automotive | Qiao W.,University of Nebraska - Lincoln | Qu L.,University of Nebraska - Lincoln
IEEE Transactions on Power Electronics | Year: 2016

This paper proposes an artificial neural network (ANN)-based reinforcement learning (RL) maximum power point tracking (MPPT) algorithm for permanent-magnet synchronous generator (PMSG)-based variable-speed wind energy conversion systems (WECSs). The proposed MPPT algorithm first learns the optimal relationship between the rotor speed and electrical power of the PMSG through a combination of the ANNs and the Q-learning method. The MPPT algorithm is switched from the online RL to the optimal relation-based online MPPT when the maximum power point is learned. The proposed online learning algorithm enables the WECS to behave like an intelligent agent with memory to learn from its own experience, thus improving the learning efficiency. The online RL process can be reactivated any time when the actual optimal relationship deviates from the learned one due to the aging of the system or a change in the environment. Simulation and experimental results are provided to validate the proposed ANN-based RL MPPT control algorithm for a 5-MW PMSG-based WECS and a small emulated PMSG-based WECS, respectively. © 2015 IEEE.

Islam R.,Nexteer Automotive | Husain I.,University of Akron
IEEE Transactions on Industry Applications | Year: 2010

This paper analyzes the noise and vibration in permanent-magnet synchronous motors (PMSMs). Electromagnetic forces have been identified as the main cause of noise and vibration in these machines, rather than the torque ripple and cogging torque. A procedure for calculating the magnetic forces on the stator teeth based on the 2-D finite-element (FE) method is presented first. An analytical model is then developed to predict the radial displacement along the stator teeth. The displacement calculations from the analytical model are validated with structural finite-element analysis (FEA) and experimental data. Finally, the radial displacement is converted into sound power level. Four different PMSM topologies, suitable for the electric power steering application, are compared for their performances with regard to noise and vibration. © 2006 IEEE.

Lelong V.,ECM United States Inc. | Welch A.,Nexteer Automotive
ASM International - 28th Heat Treating Society Conference, HEAT TREATING 2015 | Year: 2015

For more than 20 years now Low Pressure Vacuum Carburizing (LPC) has taken over several industries as the main carburizing choice. These industries take advantage of LPC's clean environment, versatility, "just in time" processing, along with possible distortion control that comes with gas quenching capabilities to process millions of parts each month. However, there are still hundreds of types of parts that can be converted to LPC with minimal effort. The authors will show the recent history and products currently being processed in LPC and how they were transitioned to LPC. Metallurgical results will be shown along with production loading scenarios. In addition, the process of a particular part showing timing and cost of each treatment process will be reviewed. These facts will show the audience the benefits and how they can take advantage of low pressure vacuum carburizing. © 2015 ASM International®.

Yang T.,Nexteer Automotive
IEEE Transactions on Control Systems Technology | Year: 2015

This brief presents a new control framework of electric power steering (EPS) systems for ground vehicles based on admittance control. An impedance filter is used to define the desired admittance of the system under the torsion bar (T-bar), and a position tracking control loop is used to enforce its apparent admittance. A road feedback path implemented with a road feedback filter provides the driver with awareness of road conditions with selected frequency components and magnitudes. In this new control framework, the base admittance of the system under the T-bar, which determines the base steering feel, can be configured independently from the closed position control loop; such separation of the closed-loop control design and steering feel configuration can potentially reduce the overall system tuning and calibration time. Common EPS characteristics are related to the design parameters of the new control framework. Numerical cosimulations, including an EPS system model and a vehicle model under different road conditions and maneuvers, show that the base steering feel matches the designed steering feel, and the system has good road disturbance rejection. With the road feedback filter, the base steering feel is augmented and the road condition awareness is improved. © 1993-2012 IEEE.

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