A Comparative Study of Deep Reinforcement Learning-based Transferable Energy Management Strategies for Hybrid Electric Vehicles

The deep reinforcement learning-based energy management strategies (EMS) have become a promising solution for hybrid electric vehicles (HEVs). When driving cycles are changed, the neural network will be retrained, which is a time-consuming and laborious task. A more efficient way of choosing EMS is to combine deep reinforcement learning (DRL)...

Finite Element Analysis of Power Module Packages with One-step Molding for Power Inductors

With the development of 5G communication technology and the rise of power semiconductors, the switching frequency of the circuit keeps increasing, which pushes for miniaturization of power modules and related components. Therefore, in this paper, a one-step molding technology was proposed for a DC/DC buck converter power module. We proposed a...

Updated Delft mass transport model DMT-2: Computation and validation

Progress in multiscale computational electromagnetics in time domain

Many system-level electromagnetic design problems are multiscale and very challenging to solve. They remain a significant barrier to system design optimization for a foreseeable future. Such multiscale problems often contain three electrical scales, i.e., the fine scale (geometrical feature size much smaller than a wavelength), the coarse scale ...

Experimental investigation of the hydrodynamic characteristics of heave plates using forced oscillation