Researchers from Iowa State University, including Ashutossh Gupta, Vassilis Kekatos, Dionysios Aliprantis, and Steve Pekarek, have published a study that delves into the dynamic modeling of load demand in electrified highways. Their work, published in the IEEE Transactions on Power Systems, offers valuable insights for grid operators and designers of electrified roadways (ERs).
Electrified roadways equipped with dynamic wireless power transfer (DWPT) technology promise to extend the driving range of electric vehicles (EVs) and reduce the need for large on-board batteries. However, the spatial arrangement of transmitter coils embedded in the roadway pavement results in an oscillatory power draw from the EV’s receiver coil. Understanding this dynamic behavior is crucial for power system studies.
The researchers modeled the load of individual EVs in both the time and frequency domains, assuming constant EV speed. They found that a nonlinear control scheme implemented in existing DWPT-enabled EVs exhibits milder frequency harmonics compared to a linear alternative. Moreover, the harmonics of an EV load decrease in amplitude with the length of the receiver coil.
The study also proposed and analyzed stochastic models for the total DWPT load served by an ER segment. These models illustrate how the composition of EVs on the ER affects its frequency spectrum. Interestingly, the researchers discovered that serving more EVs with longer receiver coils, such as trucks, does not necessarily result in milder harmonics.
The researchers validated their analytical findings using realistic traffic flows from a traffic simulator. This work provides practical applications for the energy sector, particularly for grid operators and ER designers, by offering insights into the dynamic behavior of load demand in electrified highways. Understanding these dynamics can help in designing more efficient and reliable power systems to support the growing adoption of EVs.
Source: IEEE Transactions on Power Systems, “Dynamic Modeling of Load Demand in Electrified Highways Based on the EV Composition”
This article is based on research available at arXiv.