IET Electrical Systems in Transportation最新文献

Electric road systems (ERSs) are anticipated to be major energy consumers. The energy efficiency of an ERS can be significantly improved by implementing the practice of driving electric vehicles (EVs) in closely spaced platoons. This driving configuration effectively reduces the drag coefficient of all vehicles within the platoon, resulting in a substantial decrease in the power demanded from the grid. Moreover, it enables the collective recuperation of regenerative energy from braking EVs rather than feeding the individual braking energy into each vehicle battery. Recuperating energy is well understood from trains. To safeguard the network from overvoltage, braking resistors are commonly utilised in conjunction with a nearby energy storage system (ESS) or feeding power upstream into the AC grid via bidirectional substations. This paper utilises Simulink to model an ERS featuring two EV platoons (EVPs), simulating power flow within the system and assessing various technologies for regenerative energy recuperation. A control technique for efficient management of regenerative energy is introduced and validated through experiments by using dedicated software designed for emulating regenerative braking energy in DC railway applications.

Decarbonizing rail transport in response to global warming is fundamental to achieving a net zero transportation system. Along with increased passenger mobility and network electrification initiatives, significant connectivity between the train and infrastructure is needed to underpin operational communications and safety, information exchange, and customer comfort. Track-to-train data connectivity solutions that are being proposed require a source of electrical power available at regular locations. This source of electricity is not always readily accessible along the railway track, even when the traction systems are powered by electricity. For low-power and low-voltage (LV) applications, deriving electric power from the overhead catenary system is costly, potentially bulky, complicated, or not even technically feasible with present conventional or innovative power derivation methods. This paper investigates the technical feasibility and applicability of the capacitive divider technology in electrified AC traction systems and proposes a power supply solution that could utilize the in situ 25 kV AC overhead line to supply low-power LV applications. A prototype has been developed, and the principles of deriving active power up to 47 W at 108 V have been demonstrated through laboratory experiments and simulations. The prototype has a relatively low complexity, does not require any auxiliary power supply circuitry, has relatively a lower cost compared to other solutions, and can be constructed rapidly due to the availability of off-the-shelf components. The proposed power supply solution has the potential to support data connectivity applications thus becoming an enabler of the information exchanged between train and infrastructure.

The concept of more electric aircraft (MEA) is a major trend in the aircraft industry. Compared to the conventional aircraft electrical power system (AEPS), the MEA–EPS has become more integrated and complex. The MEA–EPS demonstrates typical characteristics of a cyber–physical system (CPS) as a result of the implementation of intelligent management and information sensing techniques, thereby transforming into an aircraft cyber–physical power system (ACPPS). However, the improved architecture provides reliability while also introducing vulnerability. The methodologies used to evaluate the reliability of conventional aircraft EPS are not easily transferable to ACPPS. Therefore, it is essential to assess the vulnerability of MEA–EPS for stable operation and optimal system design. To identify the critical components and branches of MEA–EPS, this paper proposes an ACPPS framework and a modeling approach. Additionally, by applying complex network theory, the system is abstracted into an undirected network. The statistical properties of the network are examined from both structural and functional perspectives, revealing that the system exhibits a robust scale-free characteristic. Finally, four attack strategies are used to simulate random failures and malicious attacks. Simulation results indicate that the cyber-side is more fragile than the physical-side and several countermeasures are recommended to defend against attacks.

Wireless power transfer (WPT) has been developed as a transformative alternative to traditional plug-in charging for electric vehicles (EVs), offering significant developments in mobile charging. EVs are charged while moving on the roads. This review provides a comprehensive overview of various WPT technologies, including inductive power transfer (IPT), resonant inductive transfer, capacitive power transfer (CPT), microwave power transfer (MWPT) and laser power transfer (LPT), for both near-field and far-field applications. Different WPT topologies, such as series–series (SS), series–parallel (SP), parallel–parallel (PP), parallel–series (PS), LC-S, LC-P, S-SP and LC-LC, are analysed for their specific advantages in EV applications. Additionally, key standards for WPT, including SAE J2954, IEC 61980, ISO 19363, IEEE C95.1-2345 and TA-15, are providing a regulatory framework for safe and efficient implementation. The paper also explores the integration of artificial intelligence (AI) techniques like deep Q-network (DQN) and large language model (LLM) in the WPT system. Further, smart road technologies and cybersecurity measures in WPT systems, with a particular focus on issues such as data protection for cyberattacks, are discussed. The role of the Internet of Things (IoT) and edge computing in monitoring and controlling EVs for optimal charging is discussed. Furthermore, the application of blockchain technology in WPT is discussed. The advancements in coil design are also discussed. Finally, the challenges and limitations of WPT, such as energy transfer efficiency, misalignment of coils, electromagnetic interference (EMI), safety and security, are discussed.

Electric vehicles (EVs) are increasingly gaining popularity due to zero greenhouse gas emissions and some other privileges. However, limited battery capacity and drive range are known as the main obstacles to the widespread usage of EVs. Signalized intersections are among the bottleneck situations, in which the transportation systems are away from their optimal operation point. Eco-driving is an effective solution for dealing with idle stop-and-go issue before the signalized intersections, which is attainable thanks to the merits of advanced connected vehicle (ACV) technology. In this study, an eco-cooperative driving strategy is presented in proximity to the signalized intersections, considering driver comfort. First, Virginia Tech’s microscopic (VT-Micro) model is developed, taking into account road slope and regenerative braking energy. Then, using the model, all optimal acceleration and deceleration levels for uphill, flat, and downhill scenarios with consideration of driver comfort are determined. Finally, the effectiveness of the eco-cooperative driving strategy is examined.

This study discusses a brushless permanent magnet (PM) generator. A high-efficiency interior PM (IPM) generator has been designed. It is suggested to use a three-phase, 12-/10-pole generator for the auxiliary power unit application. In this regard, to compute the components of the flux density distribution in the air gap of an IPM generator, a hybrid analytical model is employed. The unique aspects of this work include the development of a 2-dimensional (2-D) analytical method to determine the air gap magnetic flux density in the IPM generator, as well as the first-ever replacement of the stator slot with surface currents without the need for a repetitive loop. The rotor body bore receives 1-dimensional (1-D) analytical IPMs first transferred using the magnetic equivalent circuit (MEC) model. After that, the 2-D analysis is modified to take the stator slot’s impacts into account by adding virtual surface currents (VSCs). Using boundary conditions and the Laplace/Poisson equations, the radial and tangential flux components of the flux density distribution in the air gap IPM generator were computed. The suggested method and the acquired findings have been validated by the finite element method (FEM), analytical model, and experimental results, indicating that the IPM generator is a promising option for electric vehicle (EV) auxiliary power unit applications.

The introduction of electrical vertical take-off and landing (eVTOL) aircraft enables a greener, quieter, and faster method of aerial transportation method than helicopters. Key electrical power technologies are also being developed to enable the realization of these new aircraft types. The Pyrofuse protection device is a nonresettable protection device (NRPD) that offers desirable features for use within small electric aircraft applications. The components used in the Pyrofuse are also currently available at the intended power levels and at low cost. However, the nonresettable aspect of the device represents a challenge in the certification process for its use in eVTOL electrical system protection, although there is a current shortage of published literature on this aspect. Accordingly, this paper provides the first document-based review of certification compliance assessment for the use of NRPDs in an eVTOL environment. This assessment shows that devices such as Pyrofuses can achieve airworthiness in a range of roles as the primary protection for eVTOL electrical power system (EPS). However, this airworthiness is highly dependent on the physical design of the aircraft design, the proposed location of NRPDs, and the immunity to common mode and common cause failures.

For hybrid buses equipped with hybrid energy storage systems, it is crucial to thoroughly evaluate and analyze the potential of different hybrid configurations in order to select an appropriate powertrain configuration for subsequent development. Currently, due to the low efficiency of energy management systems’ multiobjective weighting algorithm and the comparison of different configuration performance under specific component parameters, it is difficult to fully demonstrate the performance potential of configurations. To solve the above problems, multiple allowable component parameter schemes need to be considered. This article introduces a multiobjective evaluation method for hybrid powertrain configurations based on the nondominated sorting dynamic programming algorithm and employs parameter selection and collaborative energy management strategy optimization to overcome the challenge of large computational volume. Through the multiobjective Pareto front of fuel economy and battery SoH (state of health) changes, an effective comparison and analysis of the performance of two hybrid powertrain configurations were conducted. The results reveal that, for an 18-ton urban bus, under equivalent variations in battery SoH, the power-split configuration demonstrates an average fuel consumption reduction of 10.7% compared to the series-parallel configuration. The comparison results of various parameter configuration combinations indicate that the power-split configuration outperforms the series-parallel configuration in urban driving conditions. The aforementioned conclusions also provide reference for the selection of configuration schemes for similar types of commercial vehicles.

Reversible substations (RSs) permitting bidirectional power flows can recover the regenerative braking energy of trains in DC traction power supply systems (TPSSs), increasing the energy efficiency of railway systems. To predict their effects on system dynamics and energy savings, the paper develops multiresolution models (MRMs) to simulate the RS roles with different fidelities. A high-resolution model for the transient simulation replicates a particular topology where a three-level voltage source inverter is connected to the secondary winding of an existing 12-pulse rectifier transformer and regulated to keep a constant DC voltage in the inverting mode. Furthermore, it can model the transient effects of pantograph-to-line arcing by inserting arc voltage profiles at the train’s input stage. To increase the computation speed in the long-term energy flow simulation, a low-resolution model simplifies the rectifiers into a series connection of a diode and a controlled voltage source depicting their nonlinear output characteristics and then places a DC voltage source in parallel to form a reverse path for braking power recovery. In addition, nonlinear conversion efficiencies are introduced to calculate energy flows across substations. The MRMs are tested based on a 1.5 kV DC TPSS and discussed alongside system dynamics under normal operation or pantograph arcing and the consistencies between different models. The RS using bidirectional voltage source converters only is additionally modelled to compare the technical performance of the two topologies in terms of system dynamics and energy efficiencies.

Rail breaks, which are crucial maintenance issues for the railways, require immediate inspection and maintenance as it can cause severe railway accidents. Though, it is still difficult to promptly detect rail breaks that occur during train operation even with the advances in maintenance and inspection technologies. In this research, as a preliminary study on rail break detection system, a deep learning-based discontinuous rail position classification method, which is using vibration data obtained from distributed acoustic sensing (DAS) system during train operation, is proposed. To analyze the vibration data, a preprocessing algorithm for determining train occupancy is applied first. After that, the data in the space–time domain occupied by the train is converted to the spectrogram which is in the frequency domain by using short-time Fourier transformation (STFT). In the third step, the spectrogram images are applied to the proposed 2D convolutional neural network (2D CNN) model and the network detects discontinuous rail positions along the track, which are geometrically distinct from continuous welded rails, such as rail breaks. In order to evaluate the superiority of the proposed network model, performance comparison tests with other existing models were conducted with data collected from an actual railway line. From the results, the proposed model could achieve 99.17%, 93.33%, 87.5%, 90.32% for accuracy, precision, recall, and F1 score, respectively, and the results show overwhelming detection performance compared to other models.