Showing papers in "IEEE Transactions on Vehicular Technology in 2011"

Cognitive radio networking and communications: an overview

Abstract: Cognitive radio (CR) is the enabling technology for supporting dynamic spectrum access: the policy that addresses the spectrum scarcity problem that is encountered in many countries. Thus, CR is widely regarded as one of the most promising technologies for future wireless communications. To make radios and wireless networks truly cognitive, however, is by no means a simple task, and it requires collaborative effort from various research communities, including communications theory, networking engineering, signal processing, game theory, software-hardware joint design, and reconfigurable antenna and radio-frequency design. In this paper, we provide a systematic overview on CR networking and communications by looking at the key functions of the physical (PHY), medium access control (MAC), and network layers involved in a CR design and how these layers are crossly related. In particular, for the PHY layer, we will address signal processing techniques for spectrum sensing, cooperative spectrum sensing, and transceiver design for cognitive spectrum access. For the MAC layer, we review sensing scheduling schemes, sensing-access tradeoff design, spectrum-aware access MAC, and CR MAC protocols. In the network layer, cognitive radio network (CRN) tomography, spectrum-aware routing, and quality-of-service (QoS) control will be addressed. Emerging CRNs that are actively developed by various standardization committees and spectrum-sharing economics will also be reviewed. Finally, we point out several open questions and challenges that are related to the CRN design.

Simulating LTE Cellular Systems: An Open-Source Framework

Abstract: Long-term evolution (LTE) represents an emerging and promising technology for providing broadband ubiquitous Internet access. For this reason, several research groups are trying to optimize its performance. Unfortunately, at present, to the best of our knowledge, no open-source simulation platforms, which the scientific community can use to evaluate the performance of the entire LTE system, are freely available. The lack of a common reference simulator does not help the work of researchers and poses limitations on the comparison of results claimed by different research groups. To bridge this gap, herein, the open-source framework LTE-Sim is presented to provide a complete performance verification of LTE networks. LTE-Sim has been conceived to simulate uplink and downlink scheduling strategies in multicell/multiuser environments, taking into account user mobility, radio resource optimization, frequency reuse techniques, the adaptive modulation and coding module, and other aspects that are very relevant to the industrial and scientific communities. The effectiveness of the proposed simulator has been tested and verified considering 1) the software scalability test, which analyzes both memory and simulation time requirements; and 2) the performance evaluation of a realistic LTE network providing a comparison among well-known scheduling strategies.

State-of-Charge Estimation of the Lithium-Ion Battery Using an Adaptive Extended Kalman Filter Based on an Improved Thevenin Model

Abstract: An adaptive Kalman filter algorithm is adopted to estimate the state of charge (SOC) of a lithium-ion battery for application in electric vehicles (EVs). Generally, the Kalman filter algorithm is selected to dynamically estimate the SOC. However, it easily causes divergence due to the uncertainty of the battery model and system noise. To obtain a better convergent and robust result, an adaptive Kalman filter algorithm that can greatly improve the dependence of the traditional filter algorithm on the battery model is employed. In this paper, the typical characteristics of the lithium-ion battery are analyzed by experiment, such as hysteresis, polarization, Coulomb efficiency, etc. In addition, an improved Thevenin battery model is achieved by adding an extra RC branch to the Thevenin model, and model parameters are identified by using the extended Kalman filter (EKF) algorithm. Further, an adaptive EKF (AEKF) algorithm is adopted to the SOC estimation of the lithium-ion battery. Finally, the proposed method is evaluated by experiments with federal urban driving schedules. The proposed SOC estimation using AEKF is more accurate and reliable than that using EKF. The comparison shows that the maximum SOC estimation error decreases from 14.96% to 2.54% and that the mean SOC estimation error reduces from 3.19% to 1.06%.

Classification and Review of Control Strategies for Plug-In Hybrid Electric Vehicles

Abstract: To reduce fuel consumption and emissions in plug-in hybrid electric vehicles (PHEVs), it is equally important to select an appropriate drive train topology as it is to develop a suitable power flow control strategy While there are many control strategies that have been developed and presented, most are expansions of hybrid electric vehicle (HEV) control strategies and do not maximize the true potential the PHEV offers as a result of its ability to operate in electric-only mode over a significant distance In this paper, state-of-the-art control strategies are reviewed and classified in detail PHEV controllers mostly operate on either a rule-based or an optimization-based algorithm, each having its own advantages and disadvantages An overview of the controllers is given, and an analysis on which strategy is more suitable to maximize PHEV performance in different drive cycle conditions is provided Finally, a new classification for PHEV control strategies based on the operation of the vehicle is presented and verified through simulation results

Battery-Management System (BMS) and SOC Development for Electrical Vehicles

Abstract: Battery monitoring is vital for most electric vehicles (EVs), because the safety, operation, and even the life of the passenger depends on the battery system. This attribute is exactly the major function of the battery-management system (BMS)-to check and control the status of battery within their specified safe operating conditions. In this paper, a typical BMS block diagram has been proposed using various functional blocks. The state of charge (SOC) estimation has been implemented using Coulomb counting and open-circuit voltage methods, thereby eliminating the limitation of the stand-alone Coulomb counting method. By modeling the battery with SOC as one of the state variables, SOC can be estimated, which is further corrected by the Kalman filtering method. The battery parameters from experimental results are integrated in the model, and simulation results are validated by experiment.

Energy Management of a Fuel Cell/Supercapacitor/Battery Power Source for Electric Vehicular Applications

Abstract: This paper presents an energy management method in an electrical hybrid power source (EHPS) for electric vehicular applications. The method is based on the flatness control technique (FCT) and fuzzy logic control (FLC). This EHPS is composed of a fuel cell system as the main source and two energy storage sources (ESSs)-a bank of supercapacitors (SCs) and a bank of batteries (BATs)-as the auxiliary source. With this hybridization, the volume and mass of the EHPS can be reduced, because the high energy density of BAT and high power density of SC are utilized. In the proposed novel control strategy, the FCT is used to manage the energy between the main and the auxiliary sources, and the FLC is employed to share the power flow in the ESS between the SC and the BAT. The power sharing depends on the load power and the state of charge of the SC and the BAT. EHPS is controlled by the regulation of the stored electrostatic energy in the dc buses. The main property of this strategy is that the energy management in the power source is carried out with a single general control algorithm in different operating modes, consequently avoiding any algorithm commutation. An EHPS test bench has been assembled and equipped with a real-time system controller based on a dSPACE. The experimental results validate the efficiency of the proposed control strategy.

Cooperative Algorithms for MIMO Interference Channels

Abstract: Interference alignment (IA) is a transmission technique for exploiting all available degrees of freedom in the frequency- or time-selective interference channel with an arbitrary number of users. Most prior work on IA, however, neglects interference from other nodes in the network that are not participating in the alignment operation. This paper proposes three generalizations of IA for the multiple-antenna interference channel with multiple users that account for colored noise, which models uncoordinated interference. First, a minimum interference-plus-noise leakage (INL) algorithm is presented and shown to be equivalent to previous subspace methods when noise is spatially white or negligible. This algorithm results in orthonormal precoders that are desirable for practical implementation with limited feedback. A joint minimum mean square error design that jointly optimizes the transmit precoders and receive spatial filters is then proposed, whereas previous designs neglect the receive spatial filter. Finally, a maximum signal-to-interference-plus-noise ratio (SINR) algorithm is developed and proven to converge, unlike previous maximum SINR algorithms. The sum throughput of these algorithms is simulated in the context of a network with uncoordinated cochannel interferers that are not participating in the alignment protocol. It is found that a network with cochannel interference can benefit from employing precoders that are designed to consider that interference, but in extreme cases, such as when only one receiver has a large amount of interference, ignoring that the cochannel interference is advantageous.

Energy and Battery Management of a Plug-In Series Hybrid Electric Vehicle Using Fuzzy Logic

Abstract: Fuzzy logic is used to define a new quantity called the battery working state (BWS), which is based on both battery terminal voltage and state of charge (SOC), to overcome the problem of battery over-discharge and associated damage resulting from inaccurate estimates of the SOC. The BWS is used by a fuzzy logic energy-management system of a plug-in series hybrid electric vehicle (HEV) to make a decision on the power split between the battery and the engine, based on the BWS and vehicle power demand, while controlling the engine to work in its fuel economic region. The fuzzy logic management system was tested in real time using an HEV simulation test bench with a real battery in the loop. Simulation results are presented to demonstrate the performance of the proposed fuzzy logic energy-management system under different driving conditions and battery SOCs. The results indicate that the fuzzy logic energy-management system using the BWS was effective in ensuring that the engine operates in the vicinity of its maximum fuel efficiency region while preventing the battery from over-discharging.

Path Loss Modeling for Vehicle-to-Vehicle Communications

Abstract: Vehicle-to-vehicle (V2V) communications have received increasing attention lately, but there is a lack of reported results regarding important quantities such as path loss. This paper presents parameterized path loss models for V2V communications based on extensive sets of measurement data collected mainly under line-of-sight conditions in four different propagation environments: highway, rural, urban, and suburban. The results show that the path loss exponent is low for V2V communications, i.e., path loss slowly increases with increasing distance. We compare our results to those previously reported and find that, while they confirm some of the earlier work, there are also differences that motivate the need for further studies.

Improved Performance of Serially Connected Li-Ion Batteries With Active Cell Balancing in Electric Vehicles

Abstract: This paper presents an active cell balancing method for lithium-ion battery stacks using a flyback dc/dc converter topology. The method is described in detail, and a simulation is performed to estimate the energy gain for ten serially connected cells during one discharging cycle. The simulation is validated with measurements on a balancing prototype with ten cells. It is then shown how the active balancing method with respect to the cell voltages can be improved using the capacity and the state of charge rather than the voltage as the balancing criterion. For both charging and discharging, an improvement in performance is gained when having the state of charge and the capacity of the cells as information. A battery stack with three single cells is modeled, and a realistic driving cycle is applied to compare the difference between both methods in terms of usable energy. Simulations are also validated with measurements.

A Review of Charging Algorithms for Nickel and Lithium Battery Chargers

Abstract: Battery-charging algorithms can be used for either single- or multiple-battery chemistries. In general, single-chemistry chargers have the advantages of simplicity and reliability. On the other hand, multichemistry chargers, or “universal battery chargers,” provide a practical option for multichemistry battery systems, particularly for portable appliances, but they have some limitations. This paper presents a review of some charging algorithms for major batteries, i.e., nickel-cadmium, nickel-metal-hydride, and lithium-ion batteries for single- and multiple-chemistry chargers. A comparison between these algorithms in terms of their charging schemes and charge termination techniques is included. In addition, some trends of recent chargers development are presented.

State-of-Charge Estimation and State-of-Health Prediction of a Li-Ion Degraded Battery Based on an EKF Combined With a Per-Unit System

Abstract: This paper describes the application of an extended Kalman filter (EKF) combined with a per-unit (p.u.) system to the identification of suitable battery model parameters for the high-accuracy state-of-charge (SOC) estimation and state-of-health (SOH) prediction of a Li-Ion degraded battery. Variances in electrochemical characteristics among Li-Ion batteries caused by aging differences result in erroneous SOC estimation and SOH prediction when using the existing EKF algorithm. To apply the battery model parameters varied by the aging effect, based on the p.u. system, the absolute values of the parameters in the equivalent circuit model in addition to the discharging/charging voltage and current are converted into dimensionless values relative to a set of base value. The converted values are applied to dynamic and measurement models in the EKF algorithm. In particular, based on two methods such as direct current internal resistance measurement and the statistical analysis of voltage pattern, each diffusion resistance (RDiff) can be measured and used for offline and online SOC estimations, respectively. All SOC estimates are within ±5% of the values estimated by ampere-hour counting. Moreover, it is shown that RDiff is more sensitive than other model parameters under identical experimental conditions and, hence, implementable for SOH prediction.

ABAKA: An Anonymous Batch Authenticated and Key Agreement Scheme for Value-Added Services in Vehicular Ad Hoc Networks

Abstract: In this paper, we introduce an anonymous batch authenticated and key agreement (ABAKA) scheme to authenticate multiple requests sent from different vehicles and establish different session keys for different vehicles at the same time. In vehicular ad hoc networks (VANETs), the speed of a vehicle is changed from 10 to 40 m/s (36-144 km/h); therefore, the need for efficient authentication is inevitable. Compared with the current key agreement scheme, ABAKA can efficiently authenticate multiple requests by one verification operation and negotiate a session key with each vehicle by one broadcast message. Elliptic curve cryptography is adopted to reduce the verification delay and transmission overhead. The security of ABAKA is based on the elliptic curve discrete logarithm problem, which is an unsolved NP-complete problem. To deal with the invalid request problem, which may cause the batch verification fail, a detection algorithm has been proposed. Moreover, we demonstrate the efficiency merits of ABAKA through performance evaluations in terms of verification delay, transmission overhead, and cost for rebatch verifications, respectively. Simulation results show that both the message delay and message loss rate of ABAKA are less than that of the existing elliptic curve digital signature algorithm (ECDSA)-based scheme.

Energy-Optimal Control of Plug-in Hybrid Electric Vehicles for Real-World Driving Cycles

Abstract: Plug-in hybrid electric vehicles (PHEVs) are currently recognized as a promising solution for reducing fuel consumption and emissions due to the ability of storing energy through direct connection to the electric grid. Such benefits can be achieved only with a supervisory energy management strategy that optimizes the energy utilization of the vehicle. This control problem is particularly challenging for PHEVs due to the possibility of depleting the battery during usage and the vehicle-to-grid interaction during recharge. This paper proposes a model-based control approach for PHEV energy management that is based on minimizing the overall CO2 emissions produced-directly and indirectly-from vehicle utilization. A supervisory energy manager is formulated as a global optimal control problem and then cast into a local problem by applying the Pontryagin's minimum principle. The proposed controller is implemented in an energy-based simulator of a prototype PHEV and validated on experimental data. A simulation study is conducted to calibrate the control parameters and to investigate the influence of vehicle usage conditions, environmental factors, and geographic scenarios on the PHEV performance using a large database of regulatory and “real-world” driving profiles.

Analysis of Information Dissemination in Vehicular Ad-Hoc Networks With Application to Cooperative Vehicle Safety Systems

Abstract: Cooperative vehicle safety systems (CVSSs) rely on vehicular ad-hoc networks (VANETs) for the delivery of critical vehicle tracking information. The wireless channel in such systems is shared by vehicles within the transmission range of each other. Due to the near-linear spatial distribution of vehicles in a highway scenario, the vehicular broadcast network is heavily affected by the hidden node interference phenomenon, which considerably limits its capacity. The performance of vehicle tracking application that is the basis for CVSS is therefore significantly affected by the performance of the underlying network. The two main parameters that affect the network condition and performance are the range and rate (frequency) of transmission of safety and tracking messages. In this paper, we analyze the effect of different choices of rate and range and present models that quantify network performance in terms of its ability to disseminate tracking information. Following a thorough analysis of the hidden node affected VANET, we show that channel occupancy or busy ratio can be used as a feedback measure that quantifies the success of information dissemination and, consequently, the CVSS, under different network conditions. These findings are used to design feedback control schemes for transmission range adaptation, which are robust to variations of road and network traffic.

Performance Analysis of the IEEE 802.11 MAC Protocol for DSRC Safety Applications

Abstract: In this paper, we evaluate and improve the performance of the medium-access control (MAC) protocol for safety applications in a dedicated short-range communication (DSRC) environment. We first develop an analytical model to study the IEEE 802.11 distributed coordination function (DCF) MAC protocol that has been adopted by the IEEE 802.11p standard for DSRC. Explicit expressions are derived for the mean and standard deviation of the packet delay, as well as for the packet delivery ratio (PDR) at the MAC layer in an unsaturated network formed by moving vehicles on a highway. The proposed model is validated using extensive simulations, and its superior accuracy is compared with that of other existing models is demonstrated. Insights gained from our model reveal that the principal reason for the low PDR of the DCF protocol is packet collision due to transmissions from hidden terminals. We then present a novel protocol based on the DCF that uses an out-of-band busy tone as a negative acknowledgment to provide an efficient solution to the aforementioned problem. We extend our analytical model to the enhanced protocol and show that it preserves predictive accuracy. Most importantly, our numerical experiments confirm that the enhanced protocol improves the PDR by up to 10% and increases the supported vehicle density by up to two times for a range of packet arrival rates while maintaining the delay below the required threshold level.

Fault-Tolerant Control With Active Fault Diagnosis for Four-Wheel Independently Driven Electric Ground Vehicles

Abstract: This paper presents a fault-tolerant control approach for four-wheel independently driven (4WID) electric vehicles. An adaptive control-based passive fault-tolerant controller is designed to ensure vehicle system stability and to track the desired vehicle motion when an in-wheel motor/motor driver fault happens. Due to the system actuation redundancy, it is challenging to isolate the faulty wheel and to accurately estimate the control gain of the faulty in-wheel motor/motor driver for 4WID electric vehicles. An active fault diagnosis (FD) approach is thus proposed to explicitly isolate and evaluate the fault. Based on the estimated control gain of the faulty wheel, the control efforts of all the wheels are redistributed to relieve the torque demand on the faulty wheel. Simulations using a high-fidelity CarSim full-vehicle model show the effectiveness of the proposed in-wheel motor/motor driver active fault diagnosis and fault-tolerant control approaches in various driving scenarios.

Intersection-Based Geographical Routing Protocol for VANETs: A Proposal and Analysis

Abstract: This paper presents a class of routing protocols for vehicular ad hoc networks (VANETs) called the Intersection-based Geographical Routing Protocol (IGRP), which outperforms existing routing schemes in city environments. IGRP is based on an effective selection of road intersections through which a packet must pass to reach the gateway to the Internet. The selection is made in a way that guarantees, with high probability, network connectivity among the road intersections while satisfying quality-of-service (QoS) constraints on tolerable delay, bandwidth usage, and error rate. Geographical forwarding is used to transfer packets between any two intersections on the path, reducing the path's sensitivity to individual node movements. To achieve this, we mathematically formulate the QoS routing problem as a constrained optimization problem. Specifically, analytical expressions for the connectivity probability, end-to-end delay, hop count, and bit error rate (BER) of a route in a two-way road scenario are derived. Then, we propose a genetic algorithm to solve the optimization problem. Numerical and simulation results show that the proposed approach gives optimal or near-optimal solutions and significantly improves VANET performance when compared with several prominent routing protocols, such as greedy perimeter stateless routing (GPSR), greedy perimeter coordinator routing (GPCR), and optimized link-state routing (OLSR).

Relay Selection for Two-Way Relaying With Amplify-and-Forward Protocols

Abstract: In this paper, we propose a relay selection amplify-and-forward (RS-AF) protocol in general bidirectional relay networks with two sources and N relays. In the proposed scheme, the two sources first simultaneously transmit to all the relays, and then, a single relay with a minimum sum symbol error rate (SER) will be selected to broadcast the received signals back to both sources. To facilitate the selection process, we propose a simple suboptimal min-max criterion for relay selection, where a single relay that minimizes the maximum SER of two source nodes will be selected. Simulation results show that the proposed min-max selection has almost the same performance as the optimal selection with lower complexity. We also present a simple asymptotic SER expression and make a comparison with the conventional all-participate AF relaying scheme. The analytical results are verified through simulations. To improve the system performance, optimal power allocation (OPA) between the sources and the relay is determined based on the asymptotic SER. Simulation results indicate that the proposed RS-AF scheme with OPA yields considerable performance improvement over an equal-power-allocation scheme, particularly with a large number of relay nodes.

Influence of High-Frequency Charge–Discharge Cycling Induced by Cell Voltage Equalizers on the Life Performance of Lithium-Ion Cells

Abstract: Various types of cell voltage equalizers that exchange charges among cells have been proposed for series-connected lithium-ion cells. During equalization, cells are possibly cycled not only over a conventional period that ranges from seconds to hours but at a high frequency that is equal to the operating frequency of the equalizers as well. This paper investigates how the high-frequency cycling occurs and the factor that affects the life performance of the cells during high-frequency cycling. Experiments on charge-discharge cycling at frequencies of 1-100 kHz were performed for lithium-ion cells. The capacity of cells cycled at frequencies below 10 Hz significantly deteriorated, whereas the capacity decay of cells cycled at higher frequencies were identical to the corresponding calendar degradation. Simulation analyses revealed that the cycling current at high frequencies served only to charge and discharge the double-layer capacitance Cdl, whereas the current that flows through the charge-transfer resistance Rct, indicating the charge-transfer process, dominated at low frequencies. A correlation between the degradation trend and current distribution to Cdl and Rct was observed, implying that the calendar degradation and the degradation due to the charge-transfer process were the major causes of capacity decay in the frequency range below 10 Hz.

Outage Analysis of Decode-and-Forward Cognitive Dual-Hop Systems With the Interference Constraint in Nakagami- $m$ Fading Channels

Abstract: This paper studies the outage probability performance of decode-and-forward (DF) cognitive dual-hop systems for Nakagami-m fading channels, with consideration of an interference temperature limit. An exact outage probability expression is derived, and the impact of various key system parameters, such as interference temperature and fading severity, is investigated. Our results show that the interference temperature constraint causes the outage saturation phenomenon, but the outage performance gets better when the channel quality of the secondary transmission links improves. However, how the channel quality of the interfering links affects the outage performance depends on the channel quality of the secondary transmission links, as well as the interference temperature constraint and maximum transmit power.

Adaptive Reduced-Rank Equalization Algorithms Based on Alternating Optimization Design Techniques for MIMO Systems

Abstract: This paper presents a novel adaptive reduced-rank multiple-input-multiple-output (MIMO) equalization scheme and algorithms based on alternating optimization design techniques for MIMO spatial multiplexing systems. The proposed reduced-rank equalization structure consists of a joint iterative optimization of the following two equalization stages: 1) a transformation matrix that performs dimensionality reduction and 2) a reduced-rank estimator that retrieves the desired transmitted symbol. The proposed reduced-rank architecture is incorporated into an equalization structure that allows both decision feedback and linear schemes to mitigate the interantenna (IAI) and intersymbol interference (ISI). We develop alternating least squares (LS) expressions for the design of the transformation matrix and the reduced-rank estimator along with computationally efficient alternating recursive least squares (RLS) adaptive estimation algorithms. We then present an algorithm that automatically adjusts the model order of the proposed scheme. An analysis of the LS algorithms is carried out along with sufficient conditions for convergence and a proof of convergence of the proposed algorithms to the reduced-rank Wiener filter. Simulations show that the proposed equalization algorithms outperform the existing reduced- and full- algorithms while requiring a comparable computational cost.

Second Use of Transportation Batteries: Maximizing the Value of Batteries for Transportation and Grid Services

Abstract: Plug-in hybrid electric vehicles (PHEVs) and electric vehicles (EVs) are expected to gain significant market share in the next few decades. The economic viability for such vehicles is contingent upon the availability of cost-effective batteries with high power and energy density. For initial commercial success, government subsidies will be instrumental in allowing PHEVs and EVs to gain a foothold. However, in the long term, for electric vehicles to be commercially viable, the economics have to be self-sustaining. Toward the end of the battery life in the vehicle, the energy capacity left in the battery is not sufficient to provide the designed range for the vehicle. Typically, the automotive manufacturers recommend battery replacement when the remaining energy capacity reaches 70%-80%. There is still sufficient power (kilowatts) and energy capacity (kilowatthour) left in the battery to support various grid ancillary services such as balancing, spinning reserve, and load following. As renewable energy penetration increases, the need for such balancing services is expected to increase. This work explores optimality for the replacement of transportation batteries to be subsequently used for grid services. This analysis maximizes the value of an electric vehicle battery to be used as a transportation battery (in its first life) and, then, as a resource for providing grid services (in its second life). The results are presented across a range of key parameters, such as depth of discharge (DOD), number of batteries used over the life of the vehicle, battery life in the vehicle, battery state of health (SOH) at the end of life in the vehicle, and ancillary services rate. The results provide valuable insights for the automotive industry into maximizing the utility and the value of the vehicle batteries in an effort to either reduce the selling price of EVs and PHEVs or maximize the profitability of the emerging electrification of transportation.

Distributed Media Services in P2P-Based Vehicular Networks

Abstract: A significant challenge in vehicular networks is to efficiently provide heterogeneous media services with the constraints of limited resources, high mobility, opportunistic contact, and service time requirements. In this paper, we study the heterogeneous media provision in peer-to-peer (P2P)-based vehicular networks and develop fully dynamic service schemes with the goals of maximizing the total user-satisfaction and achieving a certain amount of fairness. We first construct a general user-satisfaction model according to the network transmission mechanism, as well as different media delay-satisfaction characteristics. Then, we formulate the media service as an optimization problem and propose a joint content dissemination and cache update scheme. We also provide the exact steps to achieve the optimal solution at equilibrium, given the user-satisfaction function. Furthermore, we extend the proposed service scheme by addressing the fairness problem. Unlike prior works that target at bandwidth or demand fair, we propose a media-aware satisfaction-fairness strategy, which is aware of the characteristic of user-satisfaction and media content and ensures max-min satisfaction-fairness sharing among multiple vehicles. It is worth noting that both schemes are designed in a distributed manner, which is amenable to online implementation for vehicle networks. In addition, we provide extensive simulation results that demonstrate the effectiveness of our proposed schemes.

Detection of Utilizable Capacity Deterioration in Battery Systems

Abstract: Lithium ion (Li-ion) batteries exhibit high power and energy densities, as well as high-cycle-lifetime capabilities. Li-ion cells based on LiFePO4 cathodes are promising alternatives to predominant metal oxide technologies, particularly for applications with high power and cycle lifetime requirements. This paper includes investigations on high-power LiFePO4 cells' cycle lifetime. Therefore, 3000 full charge-discharge cycles are applied to the cells with high constant current rates. Through reference testing, increasing battery impedance and a fading capacity are identified as a consequence of battery aging. Capacity fade proceeds in a way that cells' open-circuit voltages (OCVs) change only in the range of high state-of-charge (SOC). A model-based method that can detect the decreasingly utilizable capacity is outlined. The proposed method considers the changing OCV characteristics and enables the determination of capacity loss without complete charge and discharge being necessary during battery operation. By the evaluation of capacity loss information, an accelerated battery aging or even possible battery damage caused by overcharge can be avoided during battery charging scenarios.

Provable Systemwide Safety in Intelligent Intersections

Abstract: The automation of driving tasks is of increasing interest for highway traffic management. The emerging technologies of global positioning and intervehicular wireless communications, combined with in-vehicle computation and sensing capabilities, can potentially provide remarkable improvements in safety and efficiency. We address the problem of designing intelligent in-tersections, where traffic lights and stop signs are removed, and cars negotiate the intersection through an interaction of centralized and distributed decision making. Intelligent intersections are representative of complex hybrid systems that are increasingly of interest, where the challenge is to design tractable distributed algorithms that guarantee safety and provide good performance. Systems of automatically driven vehicles will need an under lying collision avoidance system with provable safety properties to be acceptable. This condition raises several challenges. We need to ensure perpetual collision avoidance so that cars do not get into future problematic positions to avoid an immediate collision. The architecture needs to allow distributed freedom of action to cars yet should guard against worst-case behavior of other cars to guarantee collision avoidance. The algorithms should be tractable both computationally and in information requirements and robust to uncertainties in sensing and communication. To address these challenges, we propose a hybrid architecture with an appropriate interplay between centralized coordination and distributed freedom of action. The approach is built around a core where each car has an infinite horizon contingency plan, which is updated at each sampling instant and distributed by the cars, in a computationally tractable manner. We also define a dynamically changing partial-order relation between cars, which specifies, for each car, a set of cars whose worst-case behaviors it should guard against. The architecture is hybrid, involving a centralized component that coordinates intersection traversals. We prove the safety and liveness of the overall scheme. The mathematical challenge of accurately quantifying performance remains as a difficult challenge; therefore, we conduct a simulation study that shows the benefits over stop signs and traffic lights. It is hoped that our effort can provide methodologies for the design of tractable solutions for complex distributed systems that require safety and liveness guarantees.

An Isolated High-Power Integrated Charger in Electrified-Vehicle Applications

Abstract: For electric and hybrid vehicles that use grid power to charge the battery, traction circuit components are not normally engaged during the charging time; hence, there is a possibility of using the traction circuit components in the charger circuit to have an onboard integrated charger. An isolated high-power integrated charger based on a special electrical machine with a double set of stator windings is described. Through the reconfiguration of the motor stator windings in the charging mode, a six-terminal machine is achieved. The so-called motor/generator acts as an isolated three-phase power source after synchronization with the utility grid in the charging mode. This rotary isolated power source constitutes a three-phase boost rectifier (battery charger) with full utilization of the inverter. The motor windings are reconfigured by a relay-based switching device for the charging and traction modes. This paper presents the mathematical model of the motor/generator and explains the system's functionality for the traction and charging modes. Furthermore, the charger grid synchronization and charge control are described. Finally, the simulation results are presented for a practically designed system with a traction power of 25 kW and a possible charge power of 12.5 kW.

Asymptotic Analysis of Cooperative Diversity Systems With Relay Selection in a Spectrum-Sharing Scenario

Abstract: Three low-complexity relay-selection strategies, namely, selective amplify and forward (S-AF), selective decode and forward (S-DF), and amplify and forward with partial relay selection (PRS-AF) in a spectrum-sharing scenario are studied. First, we consider a scenario where perfect channel state information (CSI) is available. For these scenarios, the respective asymptotic outage behaviors of the secondary systems are analyzed, from which the diversity and coding gains are derived and compared. Unlike the coding gain, which is shown to be very sensitive with the position of the primary receiver, the diversity gain of the secondary system is the same as the nonspectrum-sharing system. In addition, depending on the cooperative strategy employed, an increase in the number of relays may lead to severe loss of the coding gain. Afterwards, the impacts of imperfect CSI regarding the interference and transmit channels on the outage behavior of the secondary systems are analyzed. On one hand, the imperfect CSI concerning the interference channels only affects the outage performance of the primary system, whereas it has no effect on the diversity gain of the secondary system. On the other hand, the imperfect CSI concerning the transmit channels of the secondary systems may reduce the diversity gain of the three relay-selection strategies to unity, which is validated by both theoretical and numerical results.

Adaptive Vehicle Speed Control With Input Injections for Longitudinal Motion Independent Road Frictional Condition Estimation

Abstract: This paper presents a novel real-time tire-road friction coefficient estimation method that is independent of vehicle longitudinal motion for ground vehicles with separable control of the front and rear wheels. The tire-road friction coefficient information is of critical importance for vehicle dynamic control systems and intelligent autonomous vehicle applications. In this paper, the vehicle longitudinal-motion-independent tire-road friction coefficient estimation method consists of three main components: 1) an observer to estimate the internal state of a dynamic LuGre tire model; 2) an adaptive control law with a parameter projection mechanism to track the desired vehicle longitudinal motion in the presence of tire-road friction coefficient uncertainties and actively injected braking excitation signals; and 3) a recursive least square estimator that is independent of the control law, to estimate the tire-road friction coefficient in real time. Simulation results based on a high-fidelity CarSim full-vehicle model show that the system can reliably estimate the tire-road friction coefficient independent of vehicle longitudinal motion.

A Novel Hybrid-Excited Switched-Flux Brushless AC Machine for EV/HEV Applications

Abstract: A novel E-core hybrid-excited switched-flux permanent-magnet (SFPM) brushless machine is proposed based on an E-core SFPM machine, which has significantly less magnet and higher torque density than those of a conventional SFPM machine. The proposed machine has a simple structure. The main flux path of dc excitation does not affect the magnet excitation because it is not through magnets. The combination of stator and rotor pole numbers of the proposed machine is optimized, and the flux-enhancing and flux-weakening capabilities are investigated by 2-D finite-element analyses and experimentally validated.