A Multi-Source Electric Vehicle Charging Station (MS-EVCS) is a local entity that combines the grid energy with Distributed Energy Resources (DERs) with the aim of reducing the grid impact due to electric vehicles (EVs) charging events. The integration of stationary and in-vehicle Energy Storage Systems (ESSs) in MS-EVCSs has gained increasing interest thanks to the possibility of storing energy at off-peak hours to be made available at peak-hours. However, the ESS technology and the vehicle-to-grid (V2G) concept show several issues due to cost, battery life cycle, reliability, and management. The design of the MS-EVCS energy management system is of primary importance to guarantee the optimal usage of the available resources and to enhance the system benefits. This study presents a novel energy management strategy for Real-Time (RT) control of MS-EVCS considering DERs, stationary ESS, and V2G. The proposed energy management control allows defining the MS-EVCS control policy solving several cascaded-problems with the aim of achieving the minimum operating cost when the battery degradation and the stochastic nature of the sources are considered. The key feature of the proposed methodology is the lower computational effort with respect to traditional optimal control methodologies while achieving the same optimal solution.

Cyber security is one of the most crucial aspects of the Internet of Things (IoT). Among the possible threats, great interest is today paid toward the possible capturing of information caused by external attacks on both client and server sides. Whatever the IoT application, the involved nodes are exposed to cyberattacks mainly through the vulnerability of either the sensor nodes themselves (if they have the capabilities for networking operativity) or the IoT gateways, which are the devices able to create the link between the local nodes of the IoT network, and the wide area networks. Due to the low-cost constraints typical of many IoT applications, the IoT sensor nodes and IoT gateways are often developed on low-performance processing units, in many cases customized for the specific application, and thus not easy to update against new cyber threats that are continuously identified. In the framework of cyberattacks aimed at capturing sensitive information, one of the most known was the heartbleed, which, has allowed attackers to remotely read protected memory from an estimated 24–55 percent of popular HTTPS sites. To overcome such a problem, which was due to a bug of the OpenSSL, a suitable patch was quickly released, thus allowing to avoid the problem in most of the cases. However, IoT devices may require more advanced mitigation techniques, because they are sometimes unable to be patched for several practical reasons. In this scenario, the paper proposes a novel measurement method for inline detecting intrusions due to heartbleed and heartbleed-like attacks. The proposed solution is based on an effective rule which does not require decoding the payload and that can be implemented on a low-performance general-purpose processing unit. Therefore, it can be straightforwardly implemented and included in either IoT sensor nodes or IoT gateways. The realized system has been tested and validated on a number of experiments carried out on a real network, showing performance comparable (in some cases better) with the heavier machine learning-based methods.

Nowadays, the series-parallel (SP) and the parallel-series (PS) configurations represent the main architectures considered for designing a battery pack. In both architectures, cell-to-cell parameters’ variations due to manufacturing tolerances, thermal gradients, and cell degradation can strongly impact the overall performance of battery packs. However, the effect of the parameter variation on the pack performance changes depending on the architecture and the number of cells. This manuscript aims at providing a method for the assessment of the impact of cell-to-cell parameters’ variations due to potential different aging and thermal conditions for the cells in a generic SP and PS pack architecture. For this purpose, a generalized reduced order equivalent circuit model for the battery pack is defined, leading to a set of steady-state equations for easily and systematically calculating the current and voltage imbalances due to capacity and internal resistance variations independently from the pack architecture and the number of cells. A parametric analysis is reported for quantitatively evaluating the severity of the imbalances due to the cell-to-cell parameters’ variations for both battery pack architectures. The results of the comparative analysis demonstrate that PS architecture is more impacted by parameters’ variations with respect to the SP one, since a higher current imbalance is always obtained. The difference in the severity of the current imbalance in the pack architectures strongly increases as the number of series-connected cells rises. Moreover, among the cell parameters’ variations, a major impact of the capacity imbalance on the reduction of the overall performance of the battery pack is observed.

The paper presents a control strategy for induction motor which optimizes both efficiency and torque response in both transient and steady state. In the context of vectorial control of induction motor, the optimum problem is defined according to the calculus of variations for a given step change of the reference torque. This allows finding the closed-form analytical solution of the current reference trajectories which minimize the amplitude of the stator current. Simulation and experimental results confirm the validity of the proposed approach that allows getting significant improvements in the drive efficiency. As a consequence, if the induction motor is used in the powertrain of an electric vehicle, the proposed control strategy can determine an increase of the range per charge, as demonstrated by the analysis of a case study.

A new field-oriented control strategy for induction motor is proposed in the paper. It is called Maximum Torque Per Watt (MTPW) and allows obtaining the minimum value of the sum of the stator and rotor losses due to joule effect, and of the iron losses, for a given value of the reference torque and of the motor speed. Iron losses have been modeled according to Steinmetz equation, separating hysteresis and eddy currents and taking into account the dependence both on the frequency and on the peak value of the flux density. Numerical and experimental results are presented to confirm the validity of the proposed approach, which allows achieving significant improvements in the efficiency of induction motor drive.

A general approach to direct torque and flux control of induction motor fed by VSI is presented in the paper. The inverter switching patterns are generated as a function of the reference values both of the electromagnetic torque and of the controlled flux. In particular, the proposed control algorithm is independent on which kind of flux is controlled, rotor or stator one. The results obtained by means of a real time simulation show that the proposed control strategy allows to obtain a very fast and accurate response of the drive