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This work presents an ACC-like longitudinal controller for an autonomous electric vehicle, named Ego-Vehicle, based on a Deep Deterministic Reinforcement Learning algorithm. More specifically, the designed algorithm exploits the use of the Deep Deterministic Policy Gradient (DDPG) agent and the reward function explicitly takes into account both the speed and position error of the Ego-Vehicle w.r.t. the preceding one. After properly training the DDPG agent, the control ACC-like strategy is validated considering a realistic driving cycle for the preceding vehicle. Numerical results confirm the effectiveness of the designed strategy.

The problem of the motor cooling in electric aircraft propulsion is analyzed. In particular, the possibility of using forced convection cooling with external air flow is investigated. By approximating the heat exchange of an electric motor with the heat exchange of a semi-infinite thin plate immersed in an airstream, the effects of altitude on temperature and pressure are introduced into the thermal model. By solving the model in a specific range of altitude and aircraft speed variations, the change in the heat transfer coefficient on the motor surface is determined. These values are used for calculating the maximum temperature in a test motor by means of finite element analysis.

A Triple-Port Active Bridge (TAB) dc-dc converter, designed for performing the decoupled control of two batteries, is presented in the paper. The proposed configuration has been developed to counteract the power intermittency occurring in Concentrator Photovoltaic (CPV) power plants, managing the power balance into a microgrid simultaneously. Specifically, the implementation of real-time CPV smoothing control algorithms allows the evaluation of power battery set-points for balancing both the CPV power intermittency and microgrid power flow. In the present paper, the feasibility of the proposed configuration, referring to an installed CPV power plant, has been investigated. The decoupled management of two batteries, resorting to TAB implementation, was first verified by simulation analysis. Subsequently, the designed hardware TAB configuration is presented. Finally, the preliminary experimental results of the proposed energy storage system are reported.

The full electric aircraft concept requires accurate design and suitable choice and integration of all the used components. Obviously, the electric propulsion drive is one of the most important on-board equipment. Both power converters and electric motors must have low weight, suitable overload capacity and high reliability. In this paper, two possible solutions of electric propulsion motor for unmanned aerial vehicle are investigated. Sizes, weight and some features of a three-phase PMSM motor are compared to those of a six-phase motor obtained by an appropriate rewinding of the armature, with fixed stator and rotor magnetic circuits. The losses obtained from the numerical analyzes are compared to evaluate the convenience of one solution over the other.

The aim of the paper is to develop a method for short-term deterministic and probabilistic photovoltaic (PV) power forecasting, and to present the results for an actual applicative case study. The proposed method is based on the exponential smoothing models, and two variants of this approach are analyzed within both the deterministic and the probabilistic frameworks. In particular, the probabilistic forecasting method is developed through an ensemble-based procedure that includes point forecasts obtained through several smoothing exponents. The case study discussed in this paper is based on experimental data obtained from an existing plant, and the corresponding results are compared with a benchmark based on the persistence model. It is found that the proposed exponential smoothing method significantly improves the result of the short-term PV power forecasting, both in the deterministic and probabilistic frameworks.

The aim of the paper is the development of an optimal design for the sizing of a three windings transformer. The sizing was carried out through the solution of an optimization problem so that the leakage reactances are available within a fixed range to reduce the couplings between the two secondary windings. The optimization problem was solved with a software that uses finite element method to improve settlement procedure based on a differential evolution algorithm. Starting from an initial population of transformers, through the differential evolution we obtained the optimal solution which fits perfectly the required specifications.

This paper focuses on the interdisciplinary research on the design of a smart gateway for managing the dynamic error code testing collected and generated by the Electronic Control Unit (ECU) from the automotive industry. The techniques used to exchange information between the ECU code errors and knowledge bases, based on data fusion methods, allowed us to consolidate and ensure data reliability, and then to optimize processed data in our distributed electronic systems, as the basic state for Industry 4.0 standards. At the same time, they offered optimized data packets when the gateway was tested as a service integrator for ECU maintenance. The embedded programming solutions offered us safe, reliable, and flexible data packet management results on both communication systems (Transmission Control Protocol/Internet Provider (TCP/IP) and Controller Area Network (CAN) Bus) on the Electronic Control Unit (ECU) tested for diesel, high-pressure common rail engines. The main goal of this paper is to provide a solution for a smart, hardware–software, Industry-4.0-ready gateway applicable in the automotive industry.

Lithium-ion batteries are often operated to reach excellence in technical and economical performance, but they rapidly degrade as a consequence of charge/discharge profiles. Maintaining the knowledge of the actual capacity of the battery is mandatory to pursue the objectives without incurring into unexpected constraints. This paper addresses battery prognostic from the viewpoint of probabilistic prediction of the State of Health (SoH) and of the Remaining Useful Life (RUL) of the batteries. Two probabilistic models based on time series and quantile regression, each developed in a different framework, are developed and compared for this purpose. They are specifically suited up to exploit data coming from Accelerated Degradation Tests (ADTs). Moreover, a dedicated procedure to extract a single, point value from the probabilistic predictions is presented to let the models work also in deterministic scenarios. Numerical experiments conducted on actual public data confirm the validity of the proposal, within a rigorous comparison with relevant benchmarks taken from the literature on the topic.

The universal power demand is increasing every day because of population growth, industrial revolution and high standards of living. The renewable energy technologies (RETs) are environmental and cost-effective solutions to satisfy dynamic load profile based on the application of multiple components of a standalone microgrid system that encompasses photovoltaic (PV), diesel generator (DG), electric storage system and wind turbine generator (WTG). This study reveals more insight into various research questions that have not been completely addressed in past investigations. The contributions of the study are expressed: (i) analyse the effects of RETs on the total cost, (ii) test the total benefits, (iii) estimate the market benefit share of the unit that reflects the benefit of one generation unit in proportion to the whole power system, (iv) maximise and minimise the yearly average power generated by (PV and WTG) and DG. This research work presents the application of fmincon optimising tool to accomplish the objectives of the study owing to some significant characteristics. The outcomes of the work show the validity of the model and can assist the utilities to minimise the costs that are identified with the optimal operation of their power systems.

This paper presents a modified modulation scheme for quasi-Z-Source converters, based on the Maximum Constant Boost Control (MCBC) concept and Switching Frequency Optimal (SFO) as reference signal. The effectiveness of the proposed technique is validated by comparing the obtained results (in terms of AC harmonic content and voltage stress) with those carried out from traditional modulation schemes. For this reason, a test bench has been assembled and the benefits of the SFO MCBC modulation scheme have been valuated.

The role of wiring system in an electric vehicle is very important for the correct performance of electrical drives. The transmission of power and the functionality of the onboard systems depend by the correct choice of the cables used, which permits to reduce the overvoltage during the transient and the rapid ageing of the insulations. An important aspect in cable sizing is the determination and verification of ampacity, which is influenced by many factors as the temperature, the installation, and the type of voltage supply. In the paper are analyzed the thermal effects of current ripples introduced by the DC-DC converter during the discharge phase of the battery storage system. A numerical approach based on magnetic and thermal finite element analysis is used with the aim to analyze the cable performance.

The aim of the paper is the study of an optimal integration of a supercapacitor-based storage system and inductive power transfer system for the free-catenary operation of a tramway. Starting from the definition of the topology of inductive power transfer system, we propose and analyze a design procedure for the pads of the inductive power system. In the second part of the paper, an optimal integration strategy for the correct size of on-board supercapacitors and the power of the inductive energy transfer are proposed. The results obtained by means of numerical simulations are discussed. © 2018 IEEE.

Lithium-ion (Li-ion) batteries are core equipment of Electric Vehicles (EVs) and they are expected to spread out through smart power systems (e.g., Smart Grids (SGs)). Batteries are subject to degradation over time, which gradually reduces the supplied voltage and capacity until they fail to meet minimum requirements. Battery prognostic is mandatory in order to keep track of the degradation over time and in order to schedule maintenance and replacement before failures, which can cause severe damages and harmful effects on EVs and SGs. However, the estimation of the State of Health (SoH) and of the Remaining Useful Life (RUL) of batteries is not trivial, since they cannot be directly measured. Predictive models should be therefore applied to accomplish this task, by linking SoH and/or RUL to variables measured during previous charge/discharge cycles (e.g., capacity, voltage, current, temperature). In this paper, a Multiple Linear Regression (MLR) model is developed to predict the SoH of batteries on the basis of historical data. The model exploits data collected for the battery under investigation and collected data of batteries characterized by Accelerated Degradation Tests (ADTs). Predictions of the RUL, given in terms of number of remaining charge/discharge cycles, can be further extracted from predictions of the SOH obtained through the proposal. Numerical experiments based on actual data are presented to validate the performance of the proposal.

Recently, multiphase machines have gained worldwide attention from the research community and industry for their applications in the electric ship propulsion, electric transports, more-electric aircrafts and for those particular loads that require continuous operation of the machine after one or more phases become open-circuited. A fault can be due to the loss of one of the leg transistors in the voltage source inverter, or be internal to the machine, affecting one of the phase windings. Multiphase machines can continue to operate even in the case where more than one phase is open-circuited, while for a three-phase machine, post-fault operation is possible only if one phase is opened and the star point of the machine is connected to the dc mid-point of the inverter.In this papers the modeling and control of a five-phase induction machine with the field oriented control technique are presented; then, an algorithm for the post fault operation when one stator phase is open-circuited has been proposed and the results of the simulations, carried out with different load torques and reference speeds, have been reported and discussed.

The e-Mobility is one of the most important field of interest in the frame of green energy utilization, new technologies are now available for employment in the system Vehicle – User – Infrastructure. The equilibrium and stabilization of the electric system is a critical aspect but the grid balancing support can be obtained through Electric Vehicles mobile storage: the local energy system can rely on the bulk of the electric vehicle in operation and take advantage by the appropriate energy exchange through the bi-directional power exchange Grid to Vehicle (G2V) and Vehicle to Grid (V2G) with their on board energy storage. The energy supply can be operated by the electric power transfer and/or by hydrogen filling, to be used in hybrid system battery - fuel cell. For the user convenience, the energy charging could be hand free operated by wireless power transfer system and the approach to the charging spot can be supported by the driving assistance system. In the paper a possible scenario for E-Mobility system is proposed, with the interaction of the various factors impacting the expected target objectives for the social benefits.

The battery storage system is one of the most important components in an electric drive used for electric traction and propulsion. During its performance, the battery can be exposed to critical environment conditions or can work in overload, with a decrease of battery lifetime. The safeguard of the storage system needs an accurate thermal model, able to simulate all the battery conditions and the temperature variation during the transient. In the paper it is proposed a methodology which merges experimental test and heuristic optimization, able to characterize the thermal battery behavior during the transient

In the view of the general use electric vehicle, totally pollution free during operation, the range extension over the autonomy allowed by the recommended and most effective overnight charge of the battery, should be considered according to the time required to get on board the appropriate energy for the accomplishment of the mission. Two streamlines are possible for vectoring energy to the vehicle in a totally clean mode, feed the traction system: the electricity and the hydrogen. The electricity is generally recognized as a vector showing the highest efficiency and the lowest CO2 production, with reference to the generation based on the mix of the European energy sources, including the renewable ones. A combination of these supply lines for a hybrid battery-fuel cell system is considered and the various aspects of the infrastructures is discussed with an analysis of the parameters impacting the energy transfer, the production of the hydrogen, the type of interfaces for the two lines of supply with respect to the above mentioned features. In particular, the infrastructural solution at the station consisting of electricity supply by magnetic field wireless power transfer and hydrogen produced by electrolysis or by natural gas reforming is considered. In the paper a trade-off scenario is discussed about the use of a Fuel Cell Hydrogen Electric Hybrid externally chargeable system with respect to the energy consumption and CO2 production, considering the double energy supply electricity and hydrogen.

The sudden increase in power demand has put the utilization of renewable energy technologies (RETs) in a crucial position to reduce the number of people that have no access to the electrical power supply on the global note. The sustainable energy system is the cost effective technology to meet the load demand based on different applications and combinations of several components of RETs. In view of this, the optimization of an off-grid power system that comprises of the diesel generator, PV, WTG and ESS is investigated. This research work permits the load sharing among the components of a microgrid system as a criterion to harness the economic benefits of RETs. This paper presents the application of the GA to minimize the total cost of the proposed microgrid system. This optimization method is implemented in MATLAB environment and the simulation results indicate that minimum total cost is obtained from the technique. The GA is much simpler to implement and uses less computational time to solve the problem of the power system. The proposed algorithm can assist the distribution network operators to reduce the total cost that is related to the operation of a microgrid system.

Due to the large and rapid fluctuation of requested power, the coupling between renewable energy and tramway system can be affected by serious control problems. Therefore, the use of an energy storage system is required in order to store and optimally dispatch the energy. Supercapacitors (SC) are the well suitable technology for traction applications but are limited by the energy density. The use of “hybrid” SC and battery storage systems permits to supply the peak power and recovery energy by braking with SC; instead the integration with renewable energy can be optimized with the batteries. The paper proposes an optimal design for the reduction of cost of battery storage systems integrated with photovoltaic power plants.

Three-winding transformer model is widely utilized in High Voltage Direct Current (HVDC) system or railway power supply system. Coupled with a diode rectifier, the application of three winding transformers for power distribution is now increasing because of increased demand for reliable and available electrical supply. This paper analyzes the application of a three-winding transformer as a primary power distribution system instead of a standard two-winding transformer. Moreover, we present a fast calculation of short circuit current.

The possibility of realizing full electric or hybrid electric propulsion for aircraft has been considered due to the constant growth in the use of electric technologies in aircraft and the availability of high-power-density electrical machines and converters. In this paper, an optimized design approach is proposed with reference to the optimal trade-off between energy storage system sizing and the fuel mass of a series of hybrid aircraft. The problem is approached using an integer optimization algorithm based on differential evolution and by mixing both the flight mechanics and the electrical issues inherent to hybrid flights. This method has been validated by means of implementing numerical simulations and the results are reported and discussed in the paper.

Despite the yearly rise in the market quota of full electric vehicles, the main limitations on the deployment of electric vehicles are the real performances of the battery storage during operation. In this study, the authors focus on hybrid electrical storage systems composed of lead acid batteries and supercapacitors. Two different coupling methods are investigated: (i) the direct parallel coupling of the two storage devices and (ii) coupling by means of a step-up converter between the supercapacitor bank and direct current (DC) link of the entire power-train, where lead acid batteries are also connected. A specific control strategy is proposed and implemented in the step-up converter to guarantee the correct power management of the power train and in particular: (i) to save the power request to the lead acid battery pack, (ii) maintain an adequate state of charge of the supercapacitor bank, and (iii) guarantee an adequate voltage level on the DC link. A prototype of the hybrid battery, integrating the proposed control technique, was realised and tested on a real forklift. The performances of the entire power-train were experimentally measured in a warehouse test cycle emulating a typical daily working cycle.

The efficiency of the system is a very important parameter for high power electrical drives applications,. Moreover, in the system the efficiency of the power converter play a fundamental role and for this reason, the soft switching modulation techniques represent the best choice. This paper presents a novel computational method for harmonic mitigation on the output voltage of a five-level, three-phase Cascaded H-Bridge Inverter without solving non-linear equations. Through this simple approach the Working Areas have been identified in which the harmonics reference have minimum amplitude possible. Moreover, polynomial equations to evaluate the control angels have been found. In this way, through the polynomial equations can be possible to approximate the trend of the control angles versus fundamental amplitude and without solving nonlinear equations the control angles can be evaluated. The obtained polynomial equations can be easily implemented in a digital system to real-time operation. The paper also presents the circuit simulation analysis in MatLab/PLECS environment.

The interest in the hybrid electric aircraft propulsion is increasing. Different goals must be guaranteed for a correct performance of an electric propulsion system for aircraft: reliability, low weights, performance in critical conditions. The paper is focused on the thermal analysis of the medium/high frequency core transformers used for the coupling between the battery storage system and the electric motor in electric aircrafts. A multi-physics simulation is carried out to solve the transient thermal problem for the transformer during electrical assisted phase of the aircraft.

The accurate difference between the actual and predicted value of the future load demand defines the load forecasting. Load forecasting provides the most important information for power delivery and planning and plays an important role in energy management system. The aim of this paper is to model the electric baseline load profile, based on the predefined Key Performance Indicators (KPIs), in case of TUCN (Technical University of Cluj-Napoca) buildings and to demonstrate the economic and environmental benefits of controlling the consumption curve in Blocks of Buildings within several Demand Response programs.

The paper presents a design procedure for high frequency transformer windings adopted in the DC-DC converter used in electric vehicles. The output of the design procedure is the integration of a 3D printed plastic case in the transformer windings, with the aim to maximize the output power. The proposal design procedure is entirely based on a finite element analysis approach and on a differential evolution algorithm used for the solution of the optimization problem.

The actual trends in the design of AC drives are directed to the reduction of the total weight, volume and cost. Usually, this implies the necessity to adopt new motor topologies and converter architectures. An important role is played by the mono-inverter dual parallel motor (MIDP), which gives the possibility to reduce the total weight and costs of power converters. This paper proposes a novel model predictive control algorithm in order to improve the transient performances of a MIDP used for an overhead carrier. The effectiveness of the proposal control is verified through some numerical simulations.

The increase of electrical drives power density and reliability allows the possibility to develop an all-electric propulsion systems for the aircraft. A configuration based on a mono-inverter dual-parallel (MIDP) permanent magnet synchronous motors could be suitable in order to reduce the cost and the weight of the propulsion systems. This paper proposes a novel current references limitation strategy to improve the overall dynamic behaviour of the system during transient operations, without the worsening of oscillations damping. The effectiveness of the proposed solution is demonstrated through numerical simulations.

The transport system, a primary factor in the human activity, plays a major role in the context of the use of electricity, on environmental impact and on the social health. The Electric Mobility, in compliance with the EU Mandate, can bring a contribution to the transport system with user friendly means and solutions, reducing the negative effects in these areas. Considering that the use of electric energy has a beneficial effect in the transfer chain Well To Wheel, it appears worthy to consider means and ways to increase as much as possible the operation capability of the electric vehicles by getting involved a reduced electricity quantity. This objective requires the study of the system vehicle - power supply for identifying the ways and tools to transfer power grid to vehicle with simple and effective user friendly operation. The key points to be considered are the strategic positioning of the charging points, the appropriate coordination and govern of the mobility, the communication with the user and the technology for connection to the grid. An ultimate effect of structuring this system can be the possibility of rivisitation of the battery design, which could be reduced, with consequent benefits in weight, volume, cost, energy use and pollution during manufacturing and recycling. Various EU Projects deal with this matter, among which the Project FABRIC considers the feasibility for transferring power by magnetic field from electric infrastructure to the vehicle in motion, including the possible application, in interoperable way. with static, quasi dynamic and dynamic mode. The implementation and the effective operation of the system requires the Information and Communication Technology support for the interaction E-Mobility Center - User and the standardization at the international level of the requirements for the definition, production and application of the different elements and actors. The system Electric Vehicle - Grid infrastructure- Use definition and management is the object of a harmonized bulk of Standards, IEC, ISO, SAE, UL, to assure an effective utilization of the system for the benefit of the User and for the rational utilization of the energy.

This study deals with direct torque control (DTC) of induction motor drives when a multilevel inverter is involved. The proposed control technique is finalised to reduce the amplitude of torque oscillations and to improve the motor dynamic response regardless of operating speed conditions while assuring a satisfactory input current distortion. This is achieved by using a special look-up-table built with a novel approach. The control itself is based on the application in each sampling interval of one or two voltage vectors suitably selected, in order to ensure low electromagnetic torque ripple in steady-state operations and fast dynamic behaviour in transient operations. In the algorithm, the converter voltage vectors selection is carried out by using a novel look-up table whose entry points are computed by means of a specialised relation, starting from the outputs of multilevel hysteresis controllers. The suggested method, suitable for a generic multilevel inverter, is detailed for a neutral point clamped three-level inverter. The proposed algorithm is validated by several numerical results, and compared with a DTC algorithm based on a traditional three-speed range look-up tables. Finally, some experimental results, obtained with a scale laboratory setup, are shown, discussed and compared with the numerical ones.

The power extracted from PV arrays is usually maximized using maximum power point tracking algorithms. One of the most widely used techniques is the perturb &amp, observe algorithm, which periodically perturbs the operating point of the PV array, sometime with an adaptive perturbation step, and compares the PV power before and after the perturbation. This paper analyses the most suitable perturbation step to optimize maximum power point tracking performance and suggests a design criterion to select the parameters of the controller. Using this proposed adaptive step, the MPPT perturb &amp, observe algorithm achieves an excellent dynamic response by adapting the perturbation step to the actual operating conditions of the PV array. The proposed algorithm has been validated and tested in a laboratory using a dual input inductor push-pull converter. This particular converter topology is an efficient interface to boost the low voltage of PV arrays and effectively control the power flow when input or output voltages are variable. The experimental results have proved the superiority of the proposed algorithm in comparison of traditional perturb &amp, observe and incremental conductance techniques.

In this study, the design optimisation of a synchronous reluctance machine for light electric vehicles is proposed, to increase efficiency and reduce torque ripples. The existing machine was structurally optimised, using dedicated genetic algorithms, replacing only the rotor and keeping the stator and it's winding untouched. Starting from the original design of the rotor implemented in Flux2D, a finite element analysis software, and the genetic algorithm optimisation implemented in Matlab, a complex co-simulation was accomplished to obtain a rotor architecture that increases the machine's performances and decreases the torque ripples. By this, performing rotor skewing is not needed any more, hence the torque loss due to it was cancelled. The optimised rotor design increases the machine performances by higher mean torque, no skewing

The aim of this study is to present a new, accurate, and user-friendly software procedure for the analysis and rapid design of rotating induction machine windings, considering both the electric and the magnetic specifications of the machine itself. This procedure is a valid aid for quick first stage design without the necessity of using finite element method (FEM)-based design procedures. FEM can be used in a second design phase in order to refine the first stage results. The design procedure is hereafter outlined and some examples show its capability.

The spread of distributed generation systems has reinforced concerns and requirements on grid-tied power converters. The synchronization with the utility voltage vector is a major concern. In the literature, algorithms based on Phase Locked Loops are extensively presented. In spite of adequate performances under ideal and balanced grid conditions, under grid faults great inaccuracies arise. Shortcomings are overcome by advanced algorithms at the expenses of the complexity and computational cost. In this paper, grid synchronization algorithms are addressed. A solution is proposed by introducing a new post-filter stage in a Decoupled Double Synchronous Reference Frame not affecting, at the same time, the complexity of implementation, the detection time and damping of the conventional DDSRF solution. The post-filtering stage design criteria are described based on a mathematical derivation of the phase error in a conventional DDSRF algorithm under distorted grid utility. A comparison of system performances with the conventional DDSRF algorithm is carried out under distorted, balanced and unbalanced utility conditions, validating the benefits brought by the proposed solution.

In this paper, we address the problem of the probabilistic steady-state analysis of an electrical distribution system that includes wind and photovoltaic power plants. We propose a new method that takes into account the uncertainties due to the time variations of power load demands and the random nature of solar and wind energy. The new method extends a probabilistic approach proposed in the relevant literature for balanced electrical distribution systems to unbalanced electrical distribution systems, and it also takes into account the correlation among the random input variables. The method is based on Taguchi's orthogonal arrays. Numerical applications based on an IEEE test system provide evidence of the probabilistic performance of the proposed approach. The results obtained with the proposed method are compared with the results obtained using non-linear Monte Carlo simulation and the Point Estimate Method.