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The proposed solutions in the literature for integrating Device-to-Device (D2D) communication in cellular networks require added functionalities and consume valuable network resources, mainly in the discovery process. Unlike existing solutions, this paper mitigates the requirement of additional resources in the LTE-A network. This is achieved by proposing to offload a portion of the discovery traffic and processing of D2D communications that involve vehicular users (drivers and passengers) into Vehicular Ad-hoc Networks (VANETs) by using the inherent knowledge of the Road Side Units (RSUs) about users in their coverage areas. In addition, the paper develops an analytical model to analyze the duration of peer discovery in highway scenarios. The results are validated through simulation experiments using both the Network Simulator NS3 and Matlab. The analytical and numerical results demonstrate the effectiveness of the proposed scheme, and show that a low discovery latency is obtained.

Radio tomographic imaging systems use received signal strength measurements between static wireless sensors to image the changes in the radio propagation environment in the area of the sensors, which can be used to localize a person causing the change. To date, spatial models used for such systems are set a priori and do not change. Imaging and tracking performance suffers because of the mismatch between the model and the measurements. Collecting labeled training data requires intensive effort, and the data degrade quickly as the environment changes. This paper provides a means for a radio tomographic imaging system to bootstrap to improve its spatial models using unlabeled data, iteratively improving itself over time. A collection of tracking filters are presented to improve the accuracy of image and coordinate estimates. This paper presents an online method to use these estimates to instantaneously update spatial model parameters. Further, a smoothing method is presented to fine-tune the model with a given finite latency. The development efforts are evaluated using simulations and validated with real-world experiments conducted in three different environments. With respect to another state-of-the-art radio tomographic imaging system, the results suggest that the presented system increases the median tracking accuracy by twofold in the most challenging environment and by threefold when the model parameters are trained using the smoothing method.

This paper reconsiders the design of blind interference alignment (BIA) for $K$ -user MISO interference channel in which each receiver is equipped with a reconfigurable antenna of preset $M_k\geq 3$ modes. Beyond the degree of freedom (DoF)-oriented BIA (D-BIA) design proposed by Lu et al. , we further take into account the frequency of mode switching within one supersymbol frame. Even though every receiving antenna is reconfigurable with preset multiple modes, from an engineering perspective, it is of practical importance for each receiving antenna to make less number of mode switching in order to gain the benefits such as less switching power consumption and less signal distortion. To this end, we propose in this paper switching-oriented BIA (S-BIA) scheme, which preserves the same degree of freedom (DoF) gain as D-BIA while offering reduced mode switching frequency. Theoretical analysis and simulation results demonstrate that, compared to D-BIA, S-BIA can gain $100/(M-1)$ percent of switching saving when $M_k = M$ is odd for all transmitters. Remarkably, S-BIA offers 50% switching saving for multiuser $3\times 1$ interference channels.

With the ever-growing number of mobile users and the rapid growth of wireless data service requirement, quality of experience (QoE) has emerged as an essential indicator for users, service providers, and operators. Meanwhile, to improve coverage and serve users, a lot of small cell base stations (SBSs) must be installed, and a great amount of energy is consumed. However, as far as is known, there are few works that have studied the combinatorial problem of QoE and energy aware SBS management, which jointly implements power selection, load management (SU allocation), and channel allocation. This paper investigates the problem of QoE and energy aware SBS management, which consists of power selection, load management, and channel allocation. In this paper, we resort to cloud technologies to solve such a complicated combinatorial problem and employ an iterative approach in which two subproblems are alternatively assigned and optimized at each iteration, i.e., 1) transmission power and load joint management and 2) channel allocation. We propose a two-dimensional-action extended weakly acyclic game theoretical scheme to optimize the two subproblems distributedly and iteratively. We define a novel two-dimensional-action pure strategy Nash equilibrium (2D-NE) and prove that at least one 2D-NE exists in the proposed game. With the help of cloud, we propose two kinds of better response algorithms to achieve 2D-NE of the proposed game $G_w$ . Moreover, simulation results show that the proposed approach could achieve a good QoE-energy utility performance and a high QoE energy efficiency.

In cognitive radio (CR) networks, cooperative spectrum sensing is utilized to improve the sensing performance to avoid potential interference to primary users (PUs) and increase spectrum access opportunities for secondary users (SUs). A cooperative spectrum sensing process is divided into three phases: individual sensing/detection, reporting/fusion, and data transmission. In the reporting phase, one or more reporting channels are needed to transmit individual sensing results to a fusion center (FC), and global spectrum sensing results are determined at the FC. The number of required reporting channels depends on the number of spectrum sensors or SUs, which relates to reporting channel efficiency and channel scheduling complexity. That is to say, the reporting channel design can be a challenge, especially when fixed assignment scheduling is used. Therefore, in this paper, we design a reporting channel scheme based on random access protocols, including slotted Aloha and reservation-Aloha. Performance evaluations in terms of PU detection probabilities and false alarm probabilities considering the proposed reporting channels are presented. In addition, the impact of soft/unquantized spectrum sensors or detectors (SUs) and malicious SUs is considered in this paper. Analytical and simulation results illustrate the effectiveness of the proposed reporting channel scheduling methods in improving the cooperative spectrum sensing performance.

With the never-ending increase in the number of mobile connected devices and the need for higher data rates anywhere, anytime, higher frequency bands are being considered for communications. As millimeter-wave technology moves from research to commercial deployments, and motivated by the still limited bandwidth, the terahertz (THz) band is envisioned as the next frontier for communications. When it comes to vehicular networks, communication at much higher frequencies and, consequently, with much higher data rates brings many exciting opportunities as well as challenges. In this paper, an overview of the opportunities and challenges in THz communications for vehicular networks is provided. In addition, the papers in this Special Section which provide first-time solutions to some of these challenges, are introduced.

In this paper, we consider a heterogenous network in which low-power indoor femtocells are deployed in the coverage area of the existing macrobase station (MBS). This paper proposes a novel coordinated random beamforming and user-scheduling strategy to improve the throughput of users served by the femtocell access point (FAP) while satisfying the quality-of-service (QoS) requirements of users served by both MBS and FAP. The strategy, termed as QoS-aware coordinated scheduling (QACS), requires limited coordination between the MBS and FAP, i.e., only the indexes of the qualified beams are shared. Exact statistical analysis for the ergodic achievable rate of both FAP and MBS with the proposed strategy are presented. Scheduling fairness is also addressed for the proposed QACS.

The ever-increasing demand for mobile Internet and high-data-rate applications poses unique challenging requirements for 5G mobile networks, including spectrum limitations and massive connectivity. Cognitive radio and carrier aggregation (CA) have recently been proposed as promising technologies to overcome these challenges. In this paper, we investigate joint relay selection and optimal power allocation in an underlay cooperative cognitive radio with CA, taking into account the availability of multiple carrier components in two frequency bands, subject to outage probability requirements for primary users (PUs). The secondary user network employs relay selection, where the relay that maximizes the end-to-end sum rate is selected, assuming both decode-and-forward and amplify-and-forward relaying. The resulting optimization problems are optimally solved using convex optimization tools, i.e., dual decomposition and an efficient iterative method, allowing their application in practical implementations. Simulation results illustrate that the proposed configuration exploits the available degrees of freedom efficiently to maximize the SU rate, while meeting the PU average outage probability constraints. 1 1967-2012 IEEE. Manuscript received May 27, 2016; revised October 2, 2016; accepted November 7, 2016. Date of publication December 2, 2016; date of current version July 14, 2017. The work of P. D. Diamantoulakis, G. K. Karagiannidis, and T. Khattab was supported by the NPRP under Grant NPRP 6-1326-2-532 from the Qatar National Research Fund (a member of Qatar Foundation). This work was presented in part at the IEEE Wireless Communications and Networking Conference (WCNC), Doha, Qatar, Apr. 2016. The review of this paper was coordinated by Prof. D. B. da Costa. Scopus

This paper studies wireless charging of lithium-ion batteries for electric vehicles. The charging profile mandates a constant-current (CC) charging for a discharged battery until the battery voltage reaches the cutoff voltage at rated power. The charging continues at the cutoff voltage with a constant-voltage (CV) charging at a power level down to 3% of the rated power in order to fully charge the battery. An inductive-power-transfer (IPT) converter should be designed with minimal number of stages to achieve high efficiency. However, high efficiency for such a wide load range is difficult to achieve. Moreover, the efficiency-to-load relationship is distinctly different for CC and CV charging operations, posing difficulties for the single-stage design. This paper describes the design of a single-stage IPT converter that complies with the battery charging profile and, at the same time, achieves optimal efficiency. Design optimization includes soft switching for the entire battery load range, efficiency optimization for CC and CV modes of operation, and system efficiency optimization for the whole battery charging profile. Measured results of two experimental IPT battery chargers are presented for illustration and verification.

With the proliferation of sensors, such as accelerometers, in mobile devices, activity and motion tracking has become a viable technology to understand and create an engaging user experience. This paper proposes a fast adaptation and learning scheme of activity tracking policies when user statistics are unknown a priori, varying with time, and inconsistent for different users. In our stochastic optimization, user activities are required to be synchronized with a backend under a cellular data limit to avoid overcharges from cellular operators. The mobile device is charged intermittently using wireless or wired charging for receiving the required energy for transmission and sensing operations. Firstly, we propose an activity tracking policy by formulating a stochastic optimization as a constrained Markov decision process (CMDP). Secondly, we prove that the optimal policy of the CMDP has a threshold structure using a Lagrangian relaxation approach and the submodularity concept. We accordingly present a fast Q-learning algorithm by considering the policy structure to improve the convergence speed over that of conventional Q-learning. Finally, simulation examples are presented to support the theoretical findings of this paper., 14 pages, 10 figure

Fourth/Fifth Generation heterogeneous wireless networks (4G/5G HetNets) use or will use small cells (SCs) to extend network coverage and increase spectrum efficiency. However, the standard and technical specifications do not specify how to plan the locations of the SCs within the network. Several papers introduced strategies for planning the locations of SCs in the 4G HetNet architecture. However, SCs placement strategies to support the self-healing functionality of the 4G/5G self organizing networks framework has not been studied in the literature. The placement of SCs in 4G HetNets such that an SC failure will not interrupt service, hence making the network fault tolerant, is an important design and planning problem that is addressed in this paper. We present an integer linear program formulation for planning operators of managed SC locations with fault tolerance. We allow one SC to fail and by using self-healing, a fault-tolerance service is provided at designated fail-over levels (defined in terms of users throughput). We consider the problem of SC location planning by using offloading in both out-band and in-band modes, and an interference model is presented to consider the in-band mode and to address the effect of interference on SCs placement planning. A novel approach to provide a linear interference model by using an expanded state space to get rid of nonlinearity is introduced. We present numerical results that show how our model can be used to plan the positions of SCs. We also incorporate the existence of obstacles in the planning, such as large structures or natural formations, that might happen in real life. To the best of our knowledge, this is the first work that addresses the planning of SC locations in 4G/5G HetNets in a fault-tolerant manner.

In this paper, we present a novel Wi-Fi-based pedestrian collision avoidance (PCA) system: WiSafe. Compared to vision-based and radar-based PCA systems, WiSafe has a key advantage of Non-Line-of-Sight (NLOS). WiSafe can assist drivers in discovering pedestrians in NLOS and blind spots, where the views of drivers are blocked by buildings, vehicles, or other obstacles. In particular, it is very useful when driving in poor visibility conditions such as at night, in heavy rain, or thick fog. WiSafe can save split seconds, which can potentially save lives. Instead of using wireless access in vehicular environments/dedicated short-range communications to protect pedestrians, WiSafe provides a simple, effective, and low-cost solution. Without changing Wi-Fi standards, WiSafe is compatible with 802.11a/b/g/n and can be implemented by apps on smartphones or wearable devices. The complete analysis, implementation, and experiments are presented in this paper. The results show that WiSafe can achieve and even exceed the PCA requirements.

In this paper, a new cooperative two-way cognitive relaying scheme is proposed. In this model, a primary user (PU) network consisting of two PU sources communicate with each other via a single amplify-and-forward (AF) relay. In addition, a secondary user (SU) source transmits its data to an SU destination via the same PU relay node. To mitigate the SU interference caused to the PU network, the PU network considers the SU network pairs as two additional relay nodes helping the original PU relay node in improving the PU network performance. As a reward for its cooperation, the PU network allows the SU network to communicate simultaneously via the PU relay node by using the decode-and-forward protocol. The proposed system allows the transmission of four PU symbols and one SU symbol in four/three time slots resulting in a bandwidth efficiency of $1.25/1.67$ based on the cooperative scheme, respectively. Two power allocation optimization problems are formulated: the first problem minimizes the weighted sum of the average symbol error probability of both PU and SU systems, whereas the second problem maximizes the total achievable sum rate of the PU and SU networks. Lagrangian multiplier method is used to find the optimal solutions for both problems under the constraint of maximum allowable power budget. In addition, the paper investigates how the proposed model improves the PU physical layer security performance against a single passive eavesdropper. The results show that the error performance of the proposed relay selection model outperforms the conventional two-way relaying networks with AF protocol. Moreover, findings illustrate that the total achievable sum rate of the proposed relay elimination model is higher than the total achievable rate of the conventional two-way relaying model. From secrecy point of view, the proposed model is shown to achieve a nonzero secrecy rate that improves the PU system security against eavesdropping attacks.

In this paper, we propose a novel distributed cooperative sensing algorithm for connected vehicles. The adaptive energy detection threshold, which is used to decide whether the channel is busy, is optimized in this paper by using a computationally efficient numerical approach. The proposed optimization approach minimizes the probability of an incorrect detection as a function of both the probability of false alarm and the probability of missed detection. By considering both probabilities when computing the probability of incorrect detection, to the best of the authors' knowledge, the proposed approach is novel. During the energy detection process, large-scale fading, multipath fading, Doppler effect, and transmission errors affecting the control messaging process are accounted for in order to provide a practical solution for connected vehicles. Once the available channels have been detected, the vehicles share this information using broadcast control messages. Each vehicle evaluates the available channels by voting on the information received from one-hop neighbors, where the credibility of each neighbor is weighted during the voting process. An interdisciplinary approach referred to as entropy-based weighting is used to define the neighbor, as well as the vehicle's own credibility. The voting mechanism is switched between the proposed voting mechanism and the traditional voting approach obtained from the current state of the art in order to maintain a balance between the computational cost/latency and robust spectrum sensing. Experimental results show that by using the proposed distributed cooperative spectrum sensing mechanism, spectrum detection error converges to zero.

Contrary to the traditional theoretical analysis with perfect self-interference cancellation, this paper studies the outage performance of a full-duplex (FD) decode-and-forward two-way relay system with the consideration of the residual self-interference incurred by the FD mode. The exact closed-form outage probability expressions are derived in this paper. In addition, the asymptotic outage performance is investigated when the transmit powers increase to infinity, and the result demonstrates that the outage probabilities monotonically increase and finally converge to 1 as the transmit power exceeds a certain threshold. Furthermore, optimal power allocation schemes and optimal relay node placement strategies are then proposed to improve the outage performance. Finally, simulation results are conducted to verify the accuracy of the theoretical analysis.

This paper considers both nondistributed and distributed multilevel amplify-and-forward (AF) wireless relay networks. For a fair comparison, the nondistributed multilevel AF relay network consists of a one-source–one-destination pair and a relay at each level with multiple antennas, whereas the distributed network consists of a one-source–one-destination pair and multiple distributed relays at each level with a single antenna at each relay. In this paper, relay beamforming matrices are determined for both networks based on the minimum mean square error (MMSE) criterion. During data transmission, power is independently and individually constrained at the relays at each level. Finally, an iterative algorithm is proposed to solve the desired optimization problem.

Cellular heterogeneous networks (HetNets), which are realized through shared carrier deployments of macrocells and small cells, are widely seen as a potential solution to serve growing data capacity demands. While these networks pose significant challenges in interference management, much of the focus in earlier efforts has been limited only to small-cell range expansion in the downlink. In this paper, we provide a comprehensive analysis of interference management techniques applicable to the uplink of cellular HetNets, with the goal of characterizing and improving edge user (e.g., 5th percentile) performance. In particular, we propose and study virtual soft-handoff (VSHO), which offers a low-complexity and low-overhead solution that exploits the link asymmetry observed in the uplink geometry of HetNets. VSHO exploits the fact that, in the uplink, an edge macro user who suffers from very low throughput may be closer to a nearby small cell than its own macrocell. The intuition is that such macro users should have better decoding opportunity when their signals are processed at the nearby small cell with better channel conditions. We also study how interference cancelation (IC) and interference avoidance through resource blanking can be incorporated into our VSHO proposal for further throughput gains. In addition to the VSHO techniques outlined in this paper, we also analyze other candidate techniques available in the Third Generation Partnership Project Long-Term Evolution (3GPP-LTE), such as cell-range expansion (CRE) and joint processing, to present a unified view of interference management options available in HetNets.

A compact and efficient design for the electromagnetic interference (EMI) filter stage has become one of the most critical challenges in designing a high-density power converter, particularly for avionic applications. To maintain the regulatory standard requirements, EMI filter design needs to be precisely implemented. However, the attenuation characteristics of common-mode (CM) and differential-mode (DM) EMI filters may vary in practice from their respective theoretical calculations due to difficulty and inaccuracy in the noise modeling. This is particularly true for a three-phase active boost rectifier, which inherently has a CM high-frequency component in the rectifier output. This paper puts forward a detailed mathematical modeling of CM noise, originated from different sources, and discusses a concept to significantly reduce the CM noise effects. Furthermore, minimizing the weight and size of DM filter stage has been a design concern as the DM stage consumes a significant part of the weight of the whole system. This paper proposes a compact EMI filter topology with enhanced power density, which aims at satisfying the conducted EMI requirements according to DO-160F in avionics applications. The experimental verifications of the designed EMI filter are performed from the conducted emission results, obtained from a 6-kW laboratory prototype of an integrated stage of EMI and three-phase boost PFC converter.

In this paper, a spectrum-band selection scheme is developed for secondary users (SUs) in underlay spectrum-sharing networks to balance the performance between SUs and primary users (PUs) while guaranteeing PUs' priority. With the developed scheme, among multiple candidate spectrum bands, a given secondary transmitter (ST) is scheduled to access the spectrum band with minimum ratio of the ST–PU channel power gain to the SU link channel power gain. To evaluate this scheme, the SU's performance is investigated concerning its service delay. Under the constraint on average interference from the ST to PUs, the ST's optimal power allocation is obtained in a closed form to achieve the maximum effective capacity (EC) over SU links. Illustrative numerical results and asymptotic discussions substantiate the validity of our derivations and, moreover, demonstrate that, for the case of stringent delay requirements but loose average interference constraint, the band-selection scheme developed in this paper achieves better performance than both the selection of the band with maximum SU link channel power gain and that with minimum ST–PU channel power gain.

This paper investigates the distributed adaptive control problems for nonlinear vehicle-following systems subject to nonlinear acceleration uncertainties involving vehicle acceleration disturbances, wind gusts, and parameter uncertainties. It is worth mentioning that the acceleration of the leader in most existing studies is always assumed to be zero or constant; the evolution of the leader in this paper may be subject to some unknown bounded input. Distributed adaptive control strategies based on an integral sliding mode control (ISMC) technique are proposed to maintain a rigid formation for a string of vehicle platoon in one dimension. First, distributed adaptive control based on traditional constant time headway (TCTH) policy under the assumption that the initial spacing and velocity errors are zero is developed to guarantee that all spacing errors are uniformly ultimately bounded and that the string stability of the whole vehicle platoon is also satisfied. Then, a modified constant time headway (MCTH) policy is proposed to remove the assumption of zero initial spacing and velocity errors and simultaneously effectively decrease the intervehicle spacing (i.e., increase the traffic density), making them nearly equal to those by using the constant spacing (CS) policy. Adaptive compensation terms without requiring a prior knowledge of upper bounds of the uncertainties are constructed to compensate for the time-variant effects caused by nonlinear acceleration uncertainties. Finally, numerical simulation results show the validity and advantages of the proposed policy up to a significant higher traffic density.

With the increasing demand of spectrum and emergence of mobile devices, a cloud radio access network (C-RAN) is a promising technology to improve network capacity and coverage. The key concept of the C-RAN is to separate the radio function unit in remote radio heads (RRHs) from the digital function unit in baseband units (BBUs). This separation facilitates efficient spectrum and infrastructure sharing in the C-RAN. This paper considers the cooperative interference management among RRHs in the C-RAN. The RRHs can form coalitions to mitigate intra-interference and jointly serve their subscribers. To characterize RRH performance under the coalition, this paper develops two signal-to-interference-plus-noise-ratio (SINR)-based downlink throughput models of RRH, where one adopts tools from stochastic geometry to capture the interference from vehicular users (VUs) belonging to noncooperative RRHs, and another ignores the VU interference. In this paper, a coalition formation game is formulated to model the situation in which RRHs of C-RAN can make an individual decision to cooperatively serve their VUs if the throughput of the RRH can be improved. To obtain the solution of the proposed game, we develop a distributed coalition formation algorithm and analyze the stability of the coalition structure using a Markov chain model. Simulation results show that, as compared with the noncoalition and grand coalition, our distributed coalition formation can improve the C-RAN throughput by at least 20% and 80%, respectively. Furthermore, according to extensive simulation, we can define the conditions needed for RRHs to form a coalition and obtain higher throughput.

In cognitive radio networks, secondary users (SUs) can use a frequency band when the primary user (PU) of the band is not transmitting. Spectrum sensing is one of the methods that SUs employ to know if the PU has stopped transmitting. Accurate spectrum sensing boosts the likelihood that an SU detects a spectrum opportunity. However, it will be challenging for affordable receivers to support accurate spectrum sensing due to receiver impairments, including IQ imbalance and aliasing. Several other papers have developed methods that can address the effects of IQ imbalance in spectrum sensing. This paper presents a technique that can address not only IQ imbalance but the effects of aliasing on multiband spectrum sensing as well. We use channelized spectrum-domain modeling of receivers to develop the technique. This paper presents the theoretical development of the receiver modeling technique and the proposed spectrum sensing mechanism. The performance of the proposed mechanism is evaluated using simulations and hardware-based measurements. The results demonstrate that the proposed mechanism significantly enhances the opportunity detection probability of affordable cognitive radios with high IQ imbalance and poor antialiasing filter selectivity performances.

This work considers the problem of reliability and secrecy enhancement for wireless content sharing between a content source node and a content requester. By exploiting the social characteristics of multiple nodes in the presence of multiple independent eavesdroppers, this paper first investigates the impact of mobility for source node selection for transmission reliability, within a cooperative wireless network. Furthermore, trustworthiness and social-tie-based jammer node selections are explored for cooperative jamming to provide secrecy, while allocating power appropriately to the source node and the cooperative jammer node to maximize the worst-case ergodic secrecy rate. Specifically, the source transmitter is selected by first narrowing the potential link set to provide the desired transmission success rate while considering the physical channel and social characteristics jointly. Moreover, the effect of jammer dependability based on its social interactive behavior is also investigated. Instead of focusing on full channel state information (CSI), this paper also investigates the more practical case in which only statistical CSI knowledge is known. Our optimization is based on the upper and lower bounds to the secrecy rate to simplify the power optimization problem without noticeable performance loss. Additional performance analysis for the impact of social characteristics is given. Finally, a one-dimensional search is proposed to further reduce the computational complexity of the power optimization.

The Internet Protocol (IP) Multimedia Subsystem (IMS) is a framework for delivering all-IP-based services. Voice via IMS has been defined as a possible solution from Third-Generation Partnership Project (3GPP) Release 5, prior to long-term evolution (LTE). However, the cost and immediate need for IMS services prevented operators from migration to IMS-based services, particularly with the wide presence of circuit-switched (CS) services offered in Global System for Mobile Communications (GSM) and Universal Mobile Telecommunications System (UMTS) networks. CS fallback (CSFB), which was introduced in 3GPP Release 8, enables the support of voice service without IMS. This is the common deployed scenario for many exiting LTE networks. Voice over LTE (VoLTE) is compulsory to offer rich communication services (RCS) via IMS, in addition to improving the performance of the already deployed CSFB voice solution. However, CSFB and VoLTE are still deployed concurrently, where operators can gradually roll out an LTE/IMS system, while still supporting 2G/3G fallback mechanism. It is, therefore, important to benchmark the performance of both solutions, highlight the deployment challenges, and study the impacts on the end-user experience. This paper provides performance analysis, deployment challenges, and comparisons between these voice solutions. This paper presents practical performance analysis, including end-to-end assessment of call setup delay under different radio conditions, main challenges impacting the in-call performance, as well as performance aspects of Single Radio Voice Call Continuity (SRVCC) and its evolution releases.

Functional safety is of great importance for electric and hybrid electric vehicles (EV/HEVs). One way to improve functional safety of EV/HEVs is to develop reliable and robust onboard diagnostics (OBD) so that, once a component fault is detected, effective remedial actions are taken to avoid system failures. In this paper, we develop a systematic model-based diagnostic approach based on structural analysis for electric drive systems that can form the basis of OBD design for EVs. The structural analysis approach for fault detection and isolation (FDI) evaluates a system's structural model, using the mathematical model of the system in matrix form, from which it is possible to determine the analytic redundancy and to design the structured residuals. In this paper, we demonstrate the application of this methodology by carrying out the design of a diagnostic approach for permanent-magnet synchronous machine (PMSM) drive systems of EVs, with specific focus on sensor fault diagnosis. The diagnostic approach is first verified through a simulation study on the EcoCAR2 vehicle, which is a plug-in HEV developed by the Center for Automotive Research at The Ohio State University, and is then further validated through an experimental study on a test bench consisting of a three-phase inverter enabled by the TMS320F28035 digital signal processor and a PMSM.

The twin goals of maximizing fuel economy (FE) and improving consumer acceptance by reducing the cost of the energy storage system (ESS) in a series hybrid electric vehicle (SHEV) powertrain is addressed here by using energy storage as a means for filtering drive-cycle power demands on the engine, rather than an energy source for supplying an all-electric drive mode. The concept is intended to minimize, if not eliminate, the battery in the SHEV without resorting to full-range proportional control of the engine and generator. An initial optimization study reported for a mid-size SHEV showed that a 4.5-kWh lithium-ion battery pack was still required. In this paper, a sports-car-class SHEV was studied, where the challenge is to reduce the size of the ESS even more because the available space allocation is only one fourth that of the mid-size vehicle. In this paper, a controller is developed, which allows a hybridized SHEV to be realized with a light ESS. The controller includes a duty-cycling feature that manages the engine performance in multiple efficient regions and a bandwidth-limited (BWL) proportional controller feature that limits low-bandwidth battery current. The performance of the controller has been validated for a SHEV powertrain model with an 80- $\text{V}_{\mathrm{dc}}$ 1.125-kWh battery, plus an 80- $\text{V}_{\mathrm{dc}}$ 46.4-F ultracapacitor module using a customized Autonomie vehicle model. The results show that the combined FE of the new design is increased by 13%, compared with the corresponding FE in the equivalent conventional vehicle. Additional FE improvement is possible by reducing the engine size further to reflect the average power demand imposed by real drive cycles.

The use of unmanned aerial systems (UASs), which are also known as unmanned aerial vehicles, and by the term “drones” in the popular press, is growing rapidly. To ensure safety, UAS control and nonpayload communication (CNPC) links must operate very reliably in a variety of conditions. This requires an accurate quantitative characterization of the air–ground (AG) channel, and this channel characterization is the focus of this paper. After providing motivation and background, we describe our methods and modeling approach, followed by a description of our simultaneous dual-band (L-band ∼970 MHz, C-band ∼5 GHz) measurement campaign and the over-water (OW) measurement sites. Example results for path loss and root-mean-square delay spread are provided, as well as the results for channel stationarity distance (SD), used in calculating small-scale Rician $K$ - factor and correlations between the two receiver antennas that we employed in each frequency band. Two distinct SD measures—the power delay profile (PDP) correlation coefficient and the spatial autocorrelation matrix collinearity—were used and found to be of the same order. Path-loss exponents are near that of free space, but significant two-ray cancelation effects for these OW settings warrant more accurate models, which we provide. Delay spreads in the OW channels are also dominated by the two-ray components and are hence typically very small (∼10 ns) but can exceed 350 ns. A third intermittent multipath component (MPC) is also present a nonnegligible fraction of time; hence, we provide statistical wideband AG channel models to represent this. Future papers in this series will report results for the AG channel with ground sites in other types of environments.

This paper investigates the secrecy outage performance of transmit antenna selection (TAS)/maximal ratio combining (MRC) in multiple-input-multiple-output (MIMO) cognitive radio networks (CRNs) over Rayleigh fading channels. In the considered system, a secondary user (SU-TX) equipped with N A (N A ≥ 1) antennas uses TAS to transmit confidential messages to another secondary user (SU-RX), which is equipped with N B (N B ≥ 1) antennas and adopts the MRC scheme to process multiple received signals. Meanwhile, an eavesdropper equipped with N E (N E ≥ 1) antennas also adopts the MRC scheme to overhear the transmitted information between SU-TX and SU-RX. SU-TX adopts the underlay strategy to guarantee the quality of service (QoS) of the primary user (PU) without spectrum sensing. In this paper, we derive the exact and asymptotic closed-form expressions for the secrecy outage probability (SOP). Simulations are conducted to validate the accuracy of the analysis.

This paper investigates collaborative spectrum sharing (CSS) for which a cognitive secondary transmitter acts as a decode-and-forward (DF) relay for two primary users (PUs) occupying an interfering multiple-access channel. PUs are assumed to send their signals simultaneously; hence, interference between the primary signals exists due to the multiple-access nature. The secondary user (SU) selects and forwards one of the PU's signals to a desired destination, and at the same time, the SU also transmits its own signal only if it is not harmful to PUs. The selection of a primary signal to relay is investigated, depending on SU's knowledge of two primary source–destination channels, for which closed-form outage probabilities for PUs and SU are provided accordingly. With the help of the closed-form PU's outage probability, an optimal selection strategy between the primary signals and an optimal power allocation between the primary and secondary signals are also obtained in closed form, which minimizes SU's outage probability while keeping the PU's outage performance at an SU-free level. Numerical investigation is used to verify and illustrate the analysis given in this paper. Numerical results also show that the SU's performance can vary significantly according to the amount of channel knowledge that the SU can have.

Source localization based on time-difference-of-arrival (TDOA) measurements from spatially separated sensors is an important problem in sensor networks. In this paper, we study the optimal geometries of a team of networked sensors for the TDOA-based localization problem, taking into account the a priori uncertainty of the source location. Two types of TDOA sensor pairing methods, namely, centralized and decentralized , are considered. Analytic solutions to the optimal sensor geometries in the ideal case are derived in both static and movable source cases. In the movable source case, sensor geometry design is investigated under an extended Kalman filter (EKF) framework. Furthermore, under sensor motion and communication constraints, we extend this paper to an optimal sensor path planning problem. Simulations demonstrate its enhancement to the source localization and tracking performance.

In this paper, we address the problem of securing information transmission in very adverse environments, i.e., no eavesdropper channel state information (CSI) and imperfect legitimate channel CSI, by introducing a massive multiple-input–multiple-output (M-MIMO) relay. The relay is powered through wireless power transfer from the source, such that it can flexibly adjust its position according to the secrecy requirement. The benefits of a M-MIMO relay are fully exploited to enhance both power transfer efficiency and information transmission security. In particular, the challenging issues incurred by short interception distance and long transfer distance are well addressed simultaneously. The focus of this paper is on investigating the secrecy performance of two classical relaying protocols, namely amplify-and-forward (AF) and decode-and-forward (DF), and obtaining explicit expressions of secrecy outage capacity in terms of transmit power, channel condition, and antenna number. Furthermore, we propose two effective performance optimization schemes, i.e., power control at the source, and relaying protocol switch at the relay. Finally, our theoretical claims are validated by simulation results.

This paper proposes a blended rule-based energy management system (EMS) for a plug-in hybrid electric vehicle (PHEV). The proposed EMS is formulated over driving information and vehicle trip energy and not over vehicle speed profiles, as usually seen. The proposed EMS design structure and strategy is described followed by its evaluation. This is the first time a platform for a rule-based acausal EMS has been designed. Performance metrics such as the fuel economy and the number of engine stop–starts are compared with conventional rule-based EMS over real-world destinations with uncertain trip demand. Its performance metrics compared with a conventional EMS for a full parallel PHEV was found to be superior in this paper.

Traffic offloading among coexisting heterogeneous radio access technologies (RATs), i.e., inter-RAT offloading, is considered to be an effective strategy for enhancing the capacity of wireless networks and reducing the power consumption of both base stations (BSs) and mobile stations (MSs). To fully utilize inter-RAT offloading advantages, a mobility-aware evaluation is needed, which takes into account the combined effects of mobility and MS and BS spatial distributions on the performance gains. This paper proposes a novel analytical model that accurately describes MS mobility dynamics in heterogeneous wireless networks, while conveying detailed information on its location. In addition, this paper derives an analytical expression for calculating the packet loss probability for orthogonal-frequency-division-multiple-access (OFDMA)-based networks. Taking users' mobility and spatial distribution into account, this paper develops a Markovian-based framework for evaluating inter-RAT offloading performance. The accuracy of the proposed mobility model and the efficacy of the proposed performance evaluation framework are validated. Results show that MS mobility and vertical handover (VHO) cost significantly affect inter-RAT offloading performance, and ignoring their effects could lead to an inaccurate evaluation. When the effects of MS mobility and VHO cost on the performance are ignored, utilizing inter-RAT offloading decreases the packet loss probability by 9% and saves energy by 6%. However, accounting for these effects results in a 32% increase in the packet loss probability evaluation and a 64% increase in the energy consumption evaluation.

This paper studies the cooperative device-to-device (D2D) transmissions in cellular networks, where two D2D users communicate bidirectionally with each other and simultaneously serve as relays to assist the two-way transmissions between two cellular users. For this scenario, both cellular and D2D links share the same spectrum, thus creating mutual interference. In addition to that, a security problem also exists since the cellular users want to keep their messages secret from the D2D users and vice versa . To address these two issues, a security-embedded interference avoidance scheme is proposed in this paper. By exploiting the constellation rotation technique, the proposed scheme can create interference-free links for both D2D and cellular communications, thereby significantly improving the system error performance. Moreover, our scheme also provides an inherent secrecy protection at the physical layer, which makes the information exchange between cellular users and that between D2D users confidential from each other.

In this paper, secure communication aided by a multiantenna cooperative jammer is investigated. Under very practical but adverse assumptions, i.e., no instantaneous jammer–eavesdropper channel state information (CSI) and imperfect instantaneous jammer–receiver CSI, the residual interference from the jammer to the legitimate receiver appears, even with spatial beamforming. Then, this paper analyzes the impact of imperfect CSI on the function of cooperative jamming and derives closed-form expressions of multiple secrecy performance metrics, including ergodic secrecy rate, secrecy outage capacity, and interception probability. Interestingly, it is found that two antennas at the jammer is always optimal. Furthermore, some insights are obtained through asymptotic analysis, e.g., the secrecy performance is saturated as the source transmit power increases, the ergodic secrecy rate is a linear function of CSI feedback bits in the region of high transmit power at the source/jammer, and interception probability is independent of transmit power at the source and is a decreasing function of transmit power at the jammer. Finally, theoretical claims are validated by simulation results.

In this paper, we consider a cooperative simultaneous wireless information and power transfer (SWIPT) network with one source–destination pair and multiple energy harvesting relays. How to efficiently use these relays has been addressed in conventional cooperative networks, and this paper investigates the impact of SWIPT on the performance of such multirelay cooperative networks. In particular, the main contribution of this paper is that a closed-form expression of the outage probability achieved by the multirelay cooperative protocol is obtained, as well as its approximation at high SNR. In addition, the performance of the cooperative network with the SWIPT relays is compared with that in conventional systems with self-powered relays.

Wireless systems employing frequency-division duplexing (FDD) must use duplexing filters to isolate the sensitive receiver from its own strong transmission. The number of filters in the duplexer is equal to the total number of aggregated transmit and receive bands. These filters are nontunable; therefore, a separate duplexer is required for each combination of operating bands. This paper presents an adaptive duplexer architecture capable of handling more than one receiver channel and tunable over a wide frequency range. The structure uses a combination of a low-isolation device with multiple analog canceling loops controlled by a normalized least mean squares (N-LMS) algorithm to track changes in signal leakage. The control is a multiple-input–multiple-output (MIMO) problem. This paper shows that modeling the inverse plant can orthogonalize the problem and dramatically improve convergence times with reduced complexity over previous search algorithms. Low-power pseudonoise (PN) pilot signals are proposed to detect and cancel the transmitter noise. Simulations show that 50 dB of isolation is possible with 20-MHz Long-Term Evolution (LTE)-like channels. Convergence takes 80 iterations (10 ms) from cold or 15 iterations (1.5 ms) for changes in carrier frequency or antenna loading.

There is an ongoing debate in the research and industry communities as to whether IEEE 802.11p or Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) should be used for vehicular communications. In this paper, we argue that a hybrid vehicular network combining both technologies can increase the performance of the system. We first propose a mechanism to improve location-based routing in a hybrid vehicular network architecture by data and signaling traffic separation on independent wireless networks. We then develop analytical models to calculate the stochastic upper bound of the end-to-end delay (E2ED) for location-based routing in three different networking architecture alternatives based on a) short-range ad hoc only, b) cellular only, and c) the proposed hybrid ad hoc/cellular network. The analytical approach in this paper is based on the stochastic network calculus (SNC) theory, which provides a solid and uniform framework for analysis of the upper bound of the E2ED in communication networks. It is demonstrated that the proposed hybrid network provides a lower E2ED compared with the other two alternatives. Comparisons of realistic simulation results, carried out in NS-3, and analytical results show that the proposed delay bounds provide relatively tight approximations for the E2ED in the three alternative architectures for vehicular networks investigated in this paper.

Security and privacy have become increasingly critical demands in wireless networks, which, however, are particularly susceptible to eavesdropping attacks due to the broadcast nature of radio signals. This paper considers the problem of secure communication in the multiuser downlink with a passive eavesdropper (Eve), whose channel state information (CSI) is unavailable. The transmitter simultaneously transmits concurrent information signals to the users and artificial noise (AN) to Eve. We first assume that all users' CSI is perfectly known by the transmitter and derive a closed-form expression for the ergodic secrecy sum rate (SSR) in the large-system limit. We then use it as an objective function to optimize the power allocation between information signals and the AN. It shows that more power needs to be used for AN when Eve has more antennas and when the system serves fewer users. We also extend the analysis to the imperfect-CSI scenario, where the SSR saturates at high transmit power, and it is better to create more AN than to increase the signal strength when the channel estimation error is large. We derive a scale law of feedback bits (for frequency-division duplexing (FDD) systems) to maintain a constant rate offset compared with the perfect-CSI case and the optimal length of training sequence (for time-division duplexing (TDD) systems) to maximize the effective SSR. It shows that more feedback bits and longer training sequences are required to deal with the eavesdropping problem. Closed-form expressions derived in this paper can reduce the complexity of system analysis and design.

Electric vehicles will become a popular mode of travel when petroleum prices increase and global warming intensifies. However, the short driving range of electric vehicles remains a challenge. To avoid battery depletion, navigation systems route electric vehicles to surrounding charging stations for battery exchange or recharge. Nonetheless, zero inventories and occupied sockets may result in variable charging time and longer travel time. Conventional navigation approaches have been unable to respond to variable charging time because these approaches do not consider the charging times and energy consumption of electric vehicles. Navigation systems can manage shared information, traffic, and battery life, and can improve the mileage per kilowatthour of electric vehicles. In this paper, an electric-vehicle navigation system (EVNS) based on an autonomic computing architecture and a hierarchical architecture over vehicular ad-hoc networks (VANETs) is proposed. In addition to moving energy, the proposed EVNS considers air conditioner energy to predict the state of charge (SOC) because air conditioning is the most demanding auxiliary load in electric vehicles. Moreover, this paper proposes a time-dependent routing algorithm that considers shared information. The results show that the proposed EVNS method results in 31.15% and 9.52% improvements in mileage compared with the shortest path first (SPF) method and the distributed method in Manhattan, New York City, NY, USA, respectively. Furthermore, the proposed EVNS method results in 32.39% and 20.67% improvements in mileage compared with the SPF method and the distributed method in Taipei, Taiwan, respectively.

In a cellular network, the network coverage is partitioned into nonoverlapping areas called registration areas to facilitate location management (LM) that keeps track of the location of a user equipment (UE) unit. In the second-generation Global System for Mobile Communications (GSM) and the third-generation Universal Mobile Telecommunications System (UMTS), a registration area is called a location area (LA) in the circuit-switched domain or a routing area (RA) in the packet-switched domain. In the fourth-generation Long-Term Evolution (LTE), a registration area is called a tracking area (TA). To tackle the drawbacks of the LA/RA-based LM scheme used in GSM and UMTS, which is intrinsically a static scheme, LTE adopts a dynamic LM scheme called a TA list (TAL)-based scheme. Under the TAL-based scheme, the network allocates to a UE unit a group of TAs referred to as a TAL instead of only a single TA. The UE can move freely within the allocated TAL without performing any location updates that are called TA updates (TAUs) in LTE. Only when moving into a TA that is not included in the allocated TAL does the UE need to perform a TAU, and afterward, the network will allocate, to the UE, a new TAL. The performance of the TAL-based scheme relies on the allocated TAL. If the allocated TAL is inappropriate with respect to the UE's mobility and traffic characteristics, the TAL-based scheme may produce adverse effects. To find an optimal TAL allocation method for global UE units that exhibit weak regularity in their mobility, this paper develops an embedded Markov chain approach to analyze the signaling cost of the TAL-based scheme. This paper distinguishes itself from existing studies in the following aspects. First, this paper follows LTE technical specifications, that is, the number of TAs in a TAL can vary and, furthermore, is upper bounded, whereas existing studies partially or completely ignore this stipulation. Second, this paper emphasizes the impact of a call handling model that dictates whether a TAU occurs after the completion of a call by considering two call handling models, i.e., a call plus location update and a call without location update. Third, as for the dependence among the cell residence time, the TA residence time, and the TAL residence time, this paper proposes the use of a fluid flow model to describe this dependence, which is simple but does not compromise accuracy. Analytical formulas for the total signaling cost of the TAL-based scheme due to TAU and paging operations, as well as formulas that are useful in designing an optimal paging scheme, are derived, and their accuracy is validated through Mont Carlo simulation. Then, numerical studies are carried out to investigate the impact of diverse parameters on the signaling cost, revealing that the network can allocate, to a UE unit, an optimal TAL that is consistent with the UE's mobility and traffic characteristics to minimize the signaling cost of the TAL-based scheme.

Resource allocation is an important strategy to optimize system performance in multiuser cooperative orthogonal frequency-division multiple-access (OFDMA) systems. In this paper, we jointly consider three different transmission modes in cooperative OFDMA systems, i.e., direct transmission (DT) mode, half-duplex (HD) relay cooperative transmission (HDRCT) mode, and full-duplex (FD) relay transmission (FDRT) mode. The joint optimization problem of transmission mode selection, subcarrier assignment, relay selection, subcarrier pairing, and power allocation (PA) is investigated. In this paper, we transform the binary assignment problem into a maximum-weighted bipartite matching problem, which can be solved by the classical Hungarian method. Based on the dual method, we solve the joint PA and binary assignment problem iteratively. Specifically, since the direct link is considered interference in the FD relay transmission mode, the PA problem in FD relay transmission mode is nontrivial. Thus, we provide a novel hierarchical dual method to solve the PA problem in FD relay transmission mode. In addition, in HDRCT mode, the joint transmission of both the source and relay is taken into account, and we provide a simple and insightful PA scheme. Simulation results show that the proposed algorithms can significantly enhance the overall system throughput, compared with previous works.

This paper examines the problem of optimizing hybrid electric vehicle (HEV) power management for fuel economy. This paper begins by presenting a pseudospectral algorithm to solve this optimization problem. Compared with traditional dynamic programming (DP)-based optimal power management approaches, this algorithm has two key advantages: It is numerically more efficient, and it furnishes both the optimal state and costate trajectories. Building on the second advantage, this paper proposes a two-level strategy for optimal power management in vehicles commuting along fixed routes. The upper level of the proposed strategy is a costate adaptation algorithm employing pseudospectral optimization, whereas the lower level is an instantaneous optimization controller employing Pontryagin's minimum principle (PMP). This paper shows its pseudospectral optimization algorithm and two-level strategy using numerical simulation for a series hybrid school bus. Parameters of the bus powertrain model are obtained from experimental component tests performed at the National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology. Simulation results show that the pseudospectral method reaches a solution close to DP with higher computational efficiency. Furthermore, the proposed two-level strategy is capable of adapting vehicle power management based on road-grade predictions, i.e., an attractive feature compared with more traditional online hybrid power management approaches such as the use of proportional integral derivative (PID) control for adaptive equivalent fuel consumption minimization [PID equivalent consumption minimization strategy (PID-ECMS)].

A generalized integrated control strategy for vehicle dynamics using an optimal torque vectoring control approach is extended in this paper. The central objective of this approach is to generate optimal additional tire forces and yaw moment over the vehicle through the application of individual wheel torque to keep the vehicle on a target path. This is achieved by minimizing the error between the actual and target forces and moment at the center of gravity (CG). In this paper, this methodology is extended to a constrained optimal control approach that handles additional real-time constraints, which has several vehicle control applications. An online optimization strategy is used to solve the resulting constrained optimization problem that gives the necessary tire force adjustments at the tire level. Some typical applications are 1) differential braking on all wheels, which is applicable to both electric and conventional cars and 2) hybrid torque vectoring on the front wheels and differential braking on the rear wheels. Both simulations and experimental results show the usefulness of this approach of handling constraints with this optimal torque vectoring control.

In this paper, a nonlinear model predictive controller (NMPC) with a multiagent heuristic optimizer, which is called dynamic particle swarm optimization (DPSO), is proposed to reduce the cold-start hydrocarbon (HC) emission of an automotive spark-ignited engine. In general, the cold-start HC emission reduction has been proven to be a very challenging control problem that has attracted increasing attention from the automotive research community. The main contribution of this paper lies in the implementation of a model-based predictive control scheme that uses a discrete nonlinear control-oriented model for calculating the control commands. In the first part of the experiments, the developed control-oriented model is validated with some data obtained through experiments. Then, by applying the controller to different cold-starting conditions, the values of exhaust gas temperature $T_{\mathrm{exh}}$ and engine-out HC emissions are controlled to reduce the cumulative tailpipe emissions $\text{HC}_{\mathrm{cum}}$ . To ascertain the veracity of the proposed control scheme, the same problem is solved using Pontryagin's minimum principle. The conducted simulations indicate the applicability of DPSO as an effective solver at the heart of the NMPC. Moreover, the results of model-in-the-loop simulation and hardware-in-the-loop testing demonstrate the acceptable performance of the proposed control scheme for real-time applications, which is based on the NMPC method for the considered problem.

An improved controller for the energy management system of a power-split hybrid electric vehicle (HEV) is developed with the objectives of minimizing fuel consumption and improving drivability. Considering the specific application of vehicles plying on scheduled trips such as public transport, this paper assumes that the controller is privileged with a priori knowledge of the estimated total tractive energy requirement and the duration of the journey. In comparison to a recently introduced constant high-efficiency region (CHER)-based controller, this paper demonstrates that further reductions in fuel consumption can be achieved under certain driving cycles by limiting the internal-combustion-engine (ICE) operation to a dynamically varying high-efficiency region and adopting state-of-charge (SOC) swing control for battery energy storage. The frequency of engine on/off is therefore directly decided by the size of the energy storage, allowable swing of the SOC, and the tractive energy required. Performances of the CHER and dynamic high-efficiency region (DHER) controllers are compared through simulations against the existing controller of a commercial vehicle. The results reveal that the DHER controller outperforms the other two controllers in terms of fuel consumption in highway-style-driving scenarios. Therefore, to minimize fuel consumption while improving drivability under all driving scenarios, this paper proposes to combine the CHER controller with the DHER controller such that the best features of both controllers can be utilized.

International audience; This paper presents an online diagnosis method for the supercapacitors' aging problem. State-of-health (SoH) estimation is an important feature since aging introduces degradation in the supercapacitors' performance, which might eventually lead to their failure. SoH is usually measured by electrochemical impedance spectroscopy. However, this has to be performed offline and requires interruption of the system's operation. Unlike this method, this paper presents an online diagnosis technique for supercapacitors using an extended Kalman observer as a well-known tool for its particularities and performances to study nonlinear parameter estimation. The main objective of this paper is the online SoH diagnosis based on the supercapacitors' aging indicator estimation. Moreover, the proposed online estimation strategy requires only voltage and current measurements, which reduces the number of sensors with respect to other methods. The effectiveness of the proposed online observer is shown through experimental results, and robustness to noise is also studied.

Fuel cells have increasingly become an attractive option for providing clean electricity at relatively high efficiency. This paper discusses the key features of a proton exchange membrane fuel cell for a fuel cell-based auxiliary power unit (FC-APU) to supply a portion of electric loads in a vehicle. The FC-APU includes two converters: a unidirectional converter to control the fuel cell current and a bidirectional converter to control the dc-link voltage and battery current. This paper proposes 1) an energy management system (EMS) to manage the power transfer between the load and energy sources with emphasis on low stress on the fuel cell, 2) an iterative method to size the fuel cell and battery for a given load profile, based on the proposed EMS, and 3) a current estimator to reduce the effects of system transients on the dc-link voltage and increase system modularity. Simulation and experimental results validate the proposed EMS, sizing, and controller design.

This paper proposes a Flexible Infrastructure for Dynamic Power Control (FIDPC) of Electric Vehicle (EV) Battery Chargers. This infrastructure dynamically adjusts the EV battery charger current, according to the power demand of the home wherein the vehicle is plugged. An infrastructure was implemented to validate this proposal. Such infrastructure is composed by an EV battery charger and a communication system based on a Radio Frequency interface. The battery charger has nominal power of 3.6 kVA and operates with sinusoidal current and unitary total power factor, while the RF interface provides continuous data flow to the battery charger with information about the home total current consumption (rms value). Experimental tests were performed under realistic conditions to validate the concept behind the proposed FIDPC. These tests served to assess the behavior of the EV battery charger with dynamic power control on a single-phase, 230 V, 16 A, 50 Hz residential electrical installation. The experimental results confirm the quick time response of the FIDPC even when working under heavy home load variations., This work was supported by the Fundacao para a Ciencia e Tecnologia (FCT) through Project PEst-UID/CEC/00319/2013. The work of V. Monteiro was supported by the FCT agency through a doctoral scholarship under Grant SFRH/BD/80155/2011. The review of this paper was coordinated by Dr. D. Cao.

Wireless power transfer (WPT) is an emerging technology that can realize electric power transmission over certain distances without physical contact, offering significant benefits to modern automation systems, medical applications, consumer electronics, etc. This paper provides a comprehensive review of existing compensation topologies for the loosely coupled transformer. Compensation topologies are reviewed and evaluated based on their basic and advanced functions. Individual passive resonant networks used to achieve constant (load-independent) voltage or current output are analyzed and summarized. Popular WPT compensation topologies are given as application examples, which can be regarded as the combination of multiple blocks of resonant networks. Analyses of the input zero phase angle and soft switching are conducted as well. This paper also discusses the compensation requirements for achieving the maximum efficiency according to different WPT application areas.