Abstract

Abstract

Abstract

Abstract
This paper targets the development of hybrid energy storage systems (ESS), based on the batteries-supercapacitors blending. In particular, we will develop two methodologies for the combined sizing/energy management of hybrid ESS. The first method assumes that the division of power between the sources is performed through lowlhigh pass filters, which allow us to evaluate, in a simple and rapid way, the trade-offs and economic gains due to the hybridization. The second approach relies on a nonlinear optimization problem, and seeks the minimization of the installation and electrical charging costs of the sources. Simulation results reveal the existence of a threshold in the EV range, from which the introduction of the supercapacitors is less beneficial in economic terms.

Abstract
The energy storage system (ESS), as well as its efficient management, represents a key factor for the success of electric vehicles. Due to well-known technological constraints in ESSs, there has been a growing interest in combining various types of energy sources with complementary features. Among the many possible combinations, our interest here lies in the hybridization of batteries and supercapacitors (SCs) with an active parallel arrangement, i.e., the sources are connected to the direct current (dc) bus through two bidirectional dc-dc converters (step-up). Based on this ESS topology, a robust dc-link controller is employed to regulate the dc-bus voltage and track the SCs current in spite of uncertainties in the system. For this purpose, we start by showing that the converters' uncertainty, e. g., the powertrain load, can be modeled as a convex polytope. The dc-link controller is then posed as a robust linear-quadratic regulator problem and, by exploring the convex polytope, converted in a linear matrix inequalities framework, which can efficiently be solved by numerical means. Finally, the operation envelope of the controller is extended by scheduling the gains according to the energy sources' voltages, which is an important feature to cope with the voltage variations in the SCs. To analyze the performance of the control architecture, a reduced-scale prototype was built. The experimental results show that, compared with the nonrobust and non-gain-scheduled controllers, the proposed dc-link controller offers better transient response and robustness to disturbances. Furthermore, the global performance of the controller is evaluated during certain driving cycles.

Abstract
In spite of several technical advances made in recent years by the automotive industry, the driver's behaviour still influences significantly the overall fuel consumption. With the rise of smartphones adoption, there are also new opportunities to increase the awareness to this issue. The main aim of this paper is to present a new smartphone application that will help drivers reduce the fuel consumption of their vehicles. This is accomplished by using the smartphone's sensors and the vehicle state to detect the driving pattern and suggest new behaviours in real time that will lead to a more efficient driving experience. The preliminary results show the potential for significant energy savings and their relevance for changing the drivers' behaviour.