Fast ℓ₁-regularized space-Time adaptive processing using alternating direction method of multipliers

Motivated by the sparsity of filter coefficients in full-dimension space-Time adaptive processing (STAP) algorithms, this paper proposes a fast ℓ1-regularized STAP algorithm based on the alternating direction method of multipliers to accelerate the convergence and reduce the calculations. The proposed algorithm uses a splitting variable to...

Design, modelling and evaluation of a GaN based motor drive for a solar car

In recent years, electrical vehicle (EV) starts showing its unique advantages that the conventional combustion vehicles do not have. Together with the increasing interests on EV, the motor drive with higher efficiency and lighter weight also becomes more attractive. A promising solution is to apply the wide band gap (WBG) components including...

Comparison of Optimized Chargepads for Wireless EV Charging Application

Inductive power transfer (IPT) is becoming increasingly popular in stationary electric vehicle charging systems. In this paper, the influence of the different IPT coupler geometries on the performance factors efficiency, power density, misalignment tolerance, and stray field is studied. Five different cou-pler topologies namely the circular,...

Wind turbine drivetrains: State-of-the-art technologies and future development trends

This paper presents the state-of-the-art technologies and development trends of wind turbine drivetrains – the system that converts kinetic energy of the wind to electrical energy – in different stages of their life cycle: design, manufacturing, installation, operation, lifetime extension, decommissioning and recycling. Offshore development and...

Artificial intelligence combined with high-throughput calculations to improve the corrosion resistance of AlMgZn alloy

Efficiently designing lightweight alloys with combined high corrosion resistance and mechanical properties remains an enduring topic in materials engineering. Due to the inadequate accuracy of conventional stress-strain machine learning (ML) models caused by corrosion factors, a novel reinforcement self-learning ML algorithm combined with...