Etransportation最新文献

Energy consumption and driving safety of a vehicle are greatly influenced by the driving behaviors of the vehicle in front (also termed the preceding vehicle). Inappropriate responses to unanticipated changes in the preceding vehicle can lead to decreased energy efficiency and an increased risk of rear-end collisions. To address this issue, this study proposes an innovative Adaptive Eco-cruising Control Strategy (AECS) for connected electric vehicles (CEVs) considering the dynamic behavior prediction of the preceding vehicle. The AECS, which is designed with a two-stage receding horizon control framework, can adapt to scenarios where the preceding vehicle cuts in or moves out in a safer and energy-efficient manner compared to traditional eco-cruising strategies, which merely focus on a constant preceding vehicle. In the first stage, a prediction model for characterizing the dynamic behavior of preceding vehicles is developed using the Bayesian network. This model is trained using real-world vehicle driving data, allowing it to anticipate the driving trajectories of vehicles changing lanes in front. In the second stage, an energy-saving, safety, and driving comfort-oriented optimization problem is formulated as a quadratic programming form. The eco-cruising speed is then optimized to adapt to the dynamic traffic environment, especially when the preceding vehicle changes over time. Finally, several simulations are conducted to validate the AECS. The results demonstrate that the AECS can improve the energy efficiency of CEVs by up to 11.80% and 19.53% on average compared to the existing cruise control strategies and ensure vehicle driving safety and comfort, without compromising travel time. Additionally, the vehicle cut-in position, the cut-in vehicle speed, and the ego vehicle speed affect the energy efficiency improvement performance of the AECS.

The rapid expansion of electric vehicle market brings a huge stock of batteries, which can potentially serve as distributed energy storage systems to provide grid services through Vehicle-to-Grid (V2G) technology. Existing research on V2G's economic viability often simplifies intricate technical details and neglects the influence of key parameters on the results. To address these gaps, a technology-rich model was developed to evaluate the vehicle-side costs and profits of V2G. Given the current state of V2G-related technologies and costs, V2G's levelized cost of storage ranges from $0.085/kWh to $0.243/kWh, and its net present value ranges from $-1,317 to $3,013, depending on the operational strategies implemented. The variations in assessment results due to changes in key parameters were further evaluated to analyze the impacts of technological advancements and user behavior. With advancements in battery technologies, the net present value of V2G is expected to reach approximately $7,000. These findings underscore V2G's potential cost competitiveness against mainstream stationary energy storage technologies and suggest that, with appropriate technological development and usage scenarios, V2G could play a pivotal role in the new electricity system with renewable energy sources as the main component, offering substantial profitability.

All-solid-state lithium-sulfur batteries (ASSLSBs) based on sulfide solid electrolyte (SSE) hold great promise as the next-generation energy storage technology with great potential for high energy density and improved safety. However, the development of practical ASSLSBs is restricted by the scalable fabrication of sulfur cathode sheets with outstanding electrochemical performance, which remains a complex and challenging endeavor. Herein, we employ dry electrode technology to fabricate free-standing sulfur cathode sheets with both high sulfur content and loading. By utilizing polytetrafluoroethylene (PTFE) binders with unique fibrous morphologies in the dry electrodes, we achieved sulfur cathode sheets with high flexibility without compromising ionic and electronic conductivity. Remarkably, even with thickened dry cathode sheets featuring high sulfur loading of 4.5 mg cm^-2, the sulfur cathodes exhibit high initial discharge capacity of 1114.8 mAh g^-1 with good cycle stability and rate capability. Additionally, we successfully demonstrate the construction of sheet-type all-solid-state Li_3.75Si/SSE/S cells, showcasing favorable electrochemical performance with a high reversible capacity of 1067.4 mAh g^-1 after 30 cycles even at a high sulfur loading of 4.5 mg cm^-2 and high current density of 1 mA cm^-2 (0.2C). Our findings represent a demonstration of batteries coupled with high-capacity sulfur cathode and lithiated silicon anode exhibiting exceptional electrochemical performance. It also underscores the significant potential of dry-process technology in addressing the critical challenges associated with the practical production of ASSLSBs. This contribution propels ongoing endeavors in the development of next-generation energy storage systems.

Lithium-ion batteries (LIBs) play an important role for the global net-zero emission trend. They are suitable for the power interaction with the power grid with high penetration renewable energy. However, the detail evolution of the LIBs participating in frequency regulation (FR) service at low temperature is critical for the all-climate application, especially the capacity decay and the related economic loss. This study reveals that the primary degradation mechanisms for FR operation at low temperature include lithium plating of anode and lattice distortion of cathode. Surprisingly, FR with appropriate parameters for batteries at low temperature does not introduce additional capacity decay due to the great temperature rise brought about and the optimized interfacial mass transfer. This study then analyses the economy of electric vehicles (EVs) participating in FR service, which is called vehicle-to-grid (V2G). A better temperature control can improve the profit of 35.88 $/kW. An appropriate capability is also vital to improve the profit of FR service. Moreover, suitable FR conditions for LIBs can even bring a certain degree of capacity improvement at low temperature. This work guides the design criteria of non-destructive LIB interaction for future grid.

This paper compares the impact of two scaling methods of electric machines on the energy consumption of electric vehicles. The first one is the linear losses-to-power scaling method of efficiency maps, which is widely used in powertrain design studies. While the second is the geometric scaling method. Linear scaling assumes that the losses of a reference machine are linearly scaled according to the new desired power rating. This assumption is questionable and yet its impact on the energy consumption of electric vehicles remains unknown. Geometric scaling enables rapid and accurate recalculation of the parameters of the scaled machines based on scaling laws validated by finite element analysis. For this comparison, a reference machine design of 80 kW is downscaled with a power scaling factor of 0.58 and upscaled considering a power scaling of 1.96. For comparative purposes, optimal combinations of geometric scaling factors are determined. The scaled machines are derived to fit the driving requirements of two electric vehicles, namely a light-duty vehicle and a medium-duty truck. The comparison is performed for 9 standardized driving cycles. The results show that the maximal relative difference between linear and geometric scaling in terms of energy consumption is 3.5% for the case of the light-duty vehicle, compared with 1.2% for the case of the truck. The findings of this work provide evidence that linear scaling can continue to be used in system-level design studies with a relatively low impact on energy consumption. This is of high interest considering the simplicity of linear scaling and its potential for time-saving in the early development phases of electric vehicles.

As a nonlinear and dynamic system, the polymer electrolyte membrane fuel cell (PEMFC) system requires a comprehensive failure prediction and health management system to ensure its safety and reliability. In this study, a data-driven PEMFC health diagnosis framework is proposed, coupling the fault embedding model, sensor pre-selection method and deep learning diagnosis model. Firstly, a physical-based mechanism fault embedding model of PEMFC is developed to collect the data on various health states. This model can be utilized to determine the effects of different faults on cell performance and assist in the pre-selection of sensors. Then, considering the effect of fault pattern on decline, a sensor pre-selection method based on the analytical model is proposed to filter the insensitive variable from the sensor set. The diagnosis accuracy and computational time could be improved 3.7% and 40% with the help of pre-selection approach, respectively. Finally, the data collected by the optimal sensor set is utilized to develop the fault diagnosis model based on 1D-convolutional neural network (CNN). The results show that the proposed health diagnosis framework has better diagnosis performance compared with other popular diagnosis models and is conducive to online diagnosis, with 99.2% accuracy, higher computational efficiency, faster convergence speed and smaller training error. It is demonstrated that faster convergence speed and smaller training error are reflected in the proposed health diagnosis framework, which can significantly reduce computational costs.

In the face of the electrification trend in transportation, the internal combustion engine (ICE) is expected to continue playing a vital role in generating electricity for power systems or directly propelling vehicles in certain sectors. However, ICEs are also under significant pressure to achieve carbon neutrality, with the key lying in carbon-free fuels. Ammonia, compared to hydrogen, offers advantages in terms of hydrogen-carrying capacity, storage and transportation convenience, and safety, making it a promising carbon-free fuel for large-scale use in ICEs. Nonetheless, ammonia's combustion inertness poses challenges for its application, requiring efforts to enhance its combustion. Hydrogen, as a carbon-free and highly reactive fuel, serves as a powerful combustion promoter, maximizing the carbon-free effect of ammonia. Furthermore, on-board ammonia decomposition can produce hydrogen, ensuring a stable hydrogen supply and enabling ammonia-hydrogen synergy combustion while carrying only ammonia. This ammonia-hydrogen synergy combustion, based on on-board hydrogen production, presents a highly promising development direction for ammonia engines. When combined with hybridization, it further enhances the overall energy efficiency of ammonia. The objective of this paper is to review recent advancements in ammonia-hydrogen engines, covering topics such as ignition methods and combustion strategies, fuel supply, pollutants, and after-treatment. Based on this review, a conceptual ammonia-hydrogen engine for hybrid power systems is proposed. This engine ignites the ammonia-hydrogen mixture in the main chamber using hydrogen active jet ignition, achieving spark-assisted compression ignition. Technical measures for efficient engine combustion, synergistic utilization of exhaust heat for hydrogen production, and effective after-treatment of NO_x, unburned NH₃, and N₂O are discussed. At last, some perspectives on the development of ammonia-hydrogen engines are also presented.

All-solid-state batteries (ASSBs) are regarded as the most promising next-generation batteries for electric vehicles in virtue of their potential advantages of enhanced safety, high energy density and power capability. Among the ASSBs based on various solid electrolytes (SEs), sulfide-based ASSBs have attracted increasing attention due to the high ionic conductivity of sulfide SEs which is comparable to that of liquid electrolytes. Extensive efforts from academia and industry have been made to develop sulfide-based ASSBs, and several significant progress has been achieved in recent years. However, successful fabrication of high-performance sulfide-based ASSBs has been rarely reported, and the practical application of sulfide-based ASSBs still faces a variety of challenges. Herein, following a bottom-up approach, we present a comprehensive review of the critical issues of practical sulfide-based ASSBs from the material, interface, composite electrode to cell levels. The existing challenges, recent advances, and future research directions of sulfide-based ASSBs at multiple levels are discussed. Finally, several fabrication processes for scaling up sulfide-based ASSBs and existing pilot/mass production schedules of sulfide-based ASSBs of the leading companies are also introduced. Facing the existing challenges and future opportunities, we highly encourage joint efforts and cooperation across the battery community to promote the practical application of sulfide-based ASSBs.

Nowadays, multi-energy supply utility grid system has witnessed the destruction of increasing natural disasters. Under the disasters, the energy supply capability from the utility grid system to the end-user microgrids is decreased, which is due to the destruction of the system infrastructure. Thus, how to improve the resilience of the microgrids under disasters is an essential problem. In this paper, a mobile hydrogen truck-assisted methodology is proposed to deliver hydrogen tanks to end-user microgrids via transportation network to resist to the natural disasters. First, a temporal–spatial destructive model of the natural disasters based on the grid division is presented, and the dynamical energy supply ability of an IEEE30+gas20+heat14 utility grid system is derived. Second, a hydrogen tank delivering model from hydrogen company to microgrids based on transportation network is presented. Third, a real-world transportation network based on SUMO simulator is linked with Matlab to simulate the real-time coupling between transportation network and power network. Last, microgrids optimal operation based on the temporal–spatial destructive model and hydrogen tank delivering model is presented. The simulation results show that with the assistance of the arrived hydrogen tanks through real-world transportation network in microgrid, one can indeed reduce load shedding. However, when considering the damaged transportation network, the saving loads are reduced due to the increase of the mobile hydrogen storage delivery time. It reveals that delivering mobile hydrogen tanks to end-user microgrids can effectively improve the system resilience.