<span>Amidst the ever-increasing advancements in the technological realm-the electrical vehicle industry too has seen several leaps. This particularly owes to three primary factors one, the fact that we are running out of conventional resources like petrol and diesel; two, higher efficiency of electric vehicles; and finally, less pollution caused by them. This has led to a burgeoning in the use of BLDC motors with electronic commutation not only in EVs but also in industrial and commercial applications. This requires an enhanced driving and control mechanism to tap the efficiency that such motors provide to increase performance and to get better controllability and reliability. This paper presents a controller for this EV motor driver with increased efficiency by combining various strategies.</span>

The availability of large-scale datasets collected via mobile phones has opened up opportunities to study human mobility at an individual level. The granular nature of these datasets calls for the design of summary statistics that can be used to describe succinctly mobility patterns. In this work, we show that the radius of gyration, a popular summary statistic to quantify the extent of an individual's whereabouts, suffers from a sensitivity to outliers, and is incapable of capturing mobility organised around multiple centres. We propose a natural generalisation of the radius of gyration to a polycentric setting, as well as a novel metric to assess the quality of its description. With these notions, we propose a method to identify the centres in an individual's mobility and apply it to two large mobility datasets with socio-demographic features, showing that a polycentric description can capture features that a monocentric model is incapable of.