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.

Abstract
This paper presents FIEEV - Fault Injection Environment for Electric Vehicles, a Matlab/Simulink-based simulator environment for evaluating the fault impacts on vehicle stability in electrical vehicles. FIEEV makes it possible to simulate the temporal behavior of the faults and to study its effects on loss of vehicle's performance. Simulation results are presented to prove the validity of the presented framework. © 2012 IEEE.

Abstract
Among the many opportunities offered by electric vehicles (EVs), the design of power trains based on in-wheel electric motors represents, from the vehicle dynamics point of view, a very attractive prospect, mainly due to the torque-vectoring capabilities. However, this distributed propulsion also poses some practical challenges, owing to the constraints arising from motor installation in a confined space, to the increased unsprung mass weight and to the integration of the electric motor with the friction brakes. This last issue is the main theme of this work, which, in particular, focuses on the design of the anti-lock braking system (ABS). The proposed structure for the ABS is composed of a tyre slip controller, a wheel torque allocator and a braking supervisor. To address the slip regulation problem, an adaptive controller is devised, offering robustness to uncertainties in the tyre-road friction and featuring a gain-scheduling mechanism based on the vehicle velocity. Further, an optimisation framework is employed in the torque allocator to determine the optimal split between electric and friction brake torque based on energy performance metrics, actuator constraints and different actuators bandwidth. Finally, based on the EV working condition, the priorities of this allocation scheme are adapted by the braking supervisor unit. Simulation results obtained with the CarSim vehicle model, demonstrate the effectiveness of the overall approach.

Abstract
Spurred by the problem of identifying, in real-time, the adhesion levels between the tyre and the road, a practical, linear parameterisation (LP) model is proposed to represent the tyre friction. Towards that aim, results from the theory of function approximation, together with optimisation techniques, are explored to approximate the non-linear Burckhardt model with a new LP representation. It is shown that, compared with other approximations described in the literature, the proposed LP model is more efficient, that is, it requires a smaller number of parameters, and provides better approximation capabilities. Next, a modified version of the recursive least squares, subject to a set of equality constraints on parameters, is employed to identify the LP in real time. The inclusion of these constraints, arising from the parametric relationships present when the tyre is in free-rolling mode, reduces the variance of the parametric estimation and improves the convergence of the identification algorithm, particularly in situations with low tyre slips. The simulation results obtained with the full-vehicle CarSim model under different road adhesion conditions demonstrate the effectiveness of the proposed LP and the robustness of the friction peak estimation method. Furthermore, the experimental tests, performed with an electric vehicle under low-grip roads, provide further validation of the accuracy and potential of the estimation technique.