Kartik V. Sastry

Unrestricted charging of electric vehicles (EVs) can result in violations of the grid’s operating limits, and/or equipment damage or failure. To address this, we propose a two-stage smart charging (SC) algorithm for EVs in single-family residences. In the first stage, we pose an SC optimization problem considering only the EV owner’s interests. In the second stage, we leverage the existence of multiple optimal (or near-optimal) solutions to this optimization problem to reduce the grid impact of EV charging at no (or negligible) cost to the EV owner. We then assess the grid impact of our SC strategy in a residential area, where all EVs are controlled in a decentralized manner (i.e., independently of one another). For comparison, we also assess the grid impact of rapid charging and other known SC strategies. Our assessment utilizes Monte-Carlo simulation techniques and a physics-based distribution feeder model. Focusing only on the price-minimization SC problem, we show that (i) if existing SC strategies are employed, then SC can have the same undesirable effects as unrestricted, rapid charging, and (ii) if our proposed SC strategies are employed, then SC can significantly lower the grid impact of EV adoption at no additional cost to the EV owner.

Flexural ultrasonic transducers experience sustained residual vibrations after their excitation has ended. This behavior limits both the minimum range and the range resolution of single-transducer distance sensors operating in pulse-echo mode. Two methods are presented to address residual vibration issues without reducing the intensity of the transmitted pressure waves. The first method is a transmitter enhancement; a number of out-of-phase damping cycles is appended to the desired number of excitation cycles, thereby hastening the decay of the pulse-imposed transducer voltage. The second method is a receiver enhancement; the echo-induced transducer voltage is isolated from the pulse-imposed transducer voltage by subtracting a stored masking signal from the acquired receiver signal. The proposed methods rely on a simple learning procedure that does not require a mathematical model of the system. Because this procedure is executed on an embedded microcontroller, the proposed methods are insensitive to variations in components or parameters. Experiments demonstrate improvements in both minimum range and range resolution.