Showing papers by "James S. Freudenberg published in 2010"
TL;DR: In this article, the power flow characterization of a bidirectional galvanically isolated high-power dual active bridge DC/DC converter was studied, and the authors developed a power flow model based on a detailed analysis over a short time scale, that incorporates additional parameters, including the power semiconductor voltage loss and dead time.
Abstract: This paper studies the power flow characterization of a bidirectional galvanically isolated high-power dual active bridge DC/DC converter. In experimental tests at the University of Michigan, we have observed three phenomena, which we term as internal power transfer, phase drift, and low system efficiency, that are present under certain operating conditions. These phenomena cannot be explained by conventional power transfer analysis. The authors develop a new model, based on a detailed analysis over a short time scale, that incorporates additional parameters, including the power semiconductor voltage loss and dead time. The new power flow model may be used to explain the observed phenomena and to characterize the power flow of the converter. The model may also be used to perform accurate power flow computations over a wide operating range, thereby supporting optimal hardware design, operating range selection, and power management strategy development. Experimental results are presented to illustrate the validity of the new model.
211 citations
TL;DR: This work considers the problem of stabilizing an unstable system driven by a Gaussian disturbance using a feedback signal transmitted over a memoryless Gaussian communication channel, and shows that for scalar systems the lower bound on the mean square norm of the state is tight, and achievable using linear time invariant communication and control.
Abstract: We consider the problem of stabilizing an unstable system driven by a Gaussian disturbance using a feedback signal transmitted over a memoryless Gaussian communication channel. By applying the concept of entropy power, we show that the mean square norm of the state vector must satisfy a lower bound that holds for any causal, measurable communication and control strategies that result in signals having well defined differential entropy. In addition, we show that use of nonlinear, time varying strategies does not allow stabilization over a channel with a lower signal-to-noise ratio than that achievable with linear time invariant state feedback. Finally, we show that for scalar systems the lower bound on the mean square norm of the state is tight, and achievable using linear time invariant communication and control.
99 citations
29 Jul 2010
TL;DR: Considering the algorithm complexity, the closed loop performance and the necessary computational time, the nonlinear MPC scheme is more desirable than the linear MPC for this application.
Abstract: This paper compares the computational time and closed loop system performances for linear and nonlinear Model Predictive Control (MPC) of the full bridge DC/DC converter under starting, overload and load step change conditions. The control objective is to regulate the output voltage without violating the peak current constraint. The experimental results reveal that both linear and nonlinear MPC algorithms can successfully achieve voltage regulation and peak current protection. Considering the algorithm complexity, the closed loop performance and the necessary computational time, the nonlinear MPC scheme is more desirable than the linear MPC for this application.
4 citations