The fuel economy and all-electric range (AER) of hybrid electric vehicles (HEVs) are highly dependent on the onboard energy-storage system (ESS) of the vehicle. Energy-storage devices charge during ...low power demands and discharge during high power demands, acting as catalysts to provide energy boost. Batteries are the primary energy-storage devices in ground vehicles. Increasing the AER of vehicles by 15% almost doubles the incremental cost of the ESS. This is due to the fact that the ESS of HEVs requires higher peak power while preserving high energy density. Ultracapacitors (UCs) are the options with higher power densities in comparison with batteries. A hybrid ESS composed of batteries, UCs, and/or fuel cells (FCs) could be a more appropriate option for advanced hybrid vehicular ESSs. This paper presents state-of-the-art energy-storage topologies for HEVs and plug-in HEVs (PHEVs). Battery, UC, and FC technologies are discussed and compared in this paper. In addition, various hybrid ESSs that combine two or more storage devices are addressed.
Electric and hybrid vehicles are a prominent technology in the transport industry for mitigating air pollution. This study aims to find the key factors which mediate product adoption by assessing the ...main barriers to purchasing, the impact of government financial incentives and other variables such as pro-environmental behavior and social reputation. Data were collected from 404 potential consumers and analyzed through two methods. Firstly, this study approaches a structural equations model. Secondly, neural networks are examined. The obtained results reveal reliability and government financial aids as the most significant motivators. In addition, the three major variables negatively impacting perceived reliability are limited range, charging time and low infrastructure availability.
•Reliability and incentives are the most significant motivators to adopt E&HV.•Three factors inhibit the improvement of perceived reliability.•Social reputation and environmental concern positively influence attitude.•There are some differences between SEM and ANN predictor rankings.
Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, ...advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a hotspot in recent years. Thanks to improved sensing technologies, CAVs are able to interpret sensory information to further detect obstacles, localize their positions, navigate themselves, and interact with other surrounding vehicles in the dynamic environment. Furthermore, leveraging computer vision and other sensing methods, in-cabin humans’ body activities, facial emotions, and even mental states can also be recognized. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in the sensing and control of CAVs.
This work focuses on developing a mobility control system for high-speed series-hybrid electric tracked vehicles, which operate with independent traction motors for each track. The scope of this ...research includes modeling a series-hybrid powertrain specific to military tracked vehicles and conducting an in-depth analysis of its dynamic behavior. Subsequently, this study conducts a critical review of mobility control approaches sourced from the literature, identifying key techniques relevant to high-inertia vehicular applications. Building on foundational models, this study proposes a robust closed-loop mobility control system aimed at ensuring precise and stable off-road vehicle operations. The system’s resilience and adaptability to a variety of driving conditions are emphasized, with a particular focus on handling maneuvers such as steering and pivoting, which are challenging operations for tracked vehicle agility. The performance of the proposed mobility control system is tested through a series of simulations, covering a spectrum of operational scenarios. These tests are conducted in both offline simulation settings, which permit meticulous fine-tuning of system parameters, and real-time environments that replicate actual field conditions. The simulation results demonstrate the system’s capacity to improve the vehicular response and highlight its potential impact on future designs of mobility control systems for the heavy-duty vehicle sector, particularly in defense applications.
•A comprehensive review of surrogate safety measures (SSM).•Pros and cons of various SSM are discussed and compared.•Applications of SSM in CAV safety modeling are summarized.•Suggestions to improve ...CAV safety modeling using SSM are provided.•Potential opportunities and directions for future research are discussed.
Surrogate Safety Measures (SSM) are important for safety performance evaluation, since crashes are rare events and historical crash data does not capture near crashes that are also critical for improving safety. This paper focuses on SSM and their applications, particularly in Connected and Automated Vehicles (CAV) safety modeling. It aims to provide a comprehensive and systematic review of significant SSM studies, identify limitations and opportunities for future SSM and CAV research, and assist researchers and practitioners with choosing the most appropriate SSM for safety studies. The behaviors of CAV can be very different from those of Human-Driven Vehicles (HDV). Even among CAV with different automation/connectivity levels, their behaviors are likely to differ. Also, the behaviors of HDV can change in response to the existence of CAV in mixed autonomy traffic. Simulation by far is the most viable solution to model CAV safety. However, it is questionable whether conventional SSM can be applied to modeling CAV safety based on simulation results due to the lack of sophisticated simulation tools that can accurately model CAV behaviors and SSM that can take CAV’s powerful sensing and path prediction and planning capabilities into crash risk modeling, although some researchers suggested that proper simulation model calibration can be helpful to address these issues. A number of critical questions related to SSM for CAV safety research are also identified and discussed, including SSM for CAV trajectory optimization, SSM for individual vehicles and vehicle platoon, and CAV as a new data source for developing SSM.
The dc-dc bidirectional step-up interleaved converter coupled by a central capacitor in a cascaded topology is used as a Bidirectional Electric Vehicle Charging Station (BEVCS) for charging and ...discharging the battery of an Electric Vehicle (EV). In this paper, a unified (coupled) model is proposed combining all switching intervals in a single model, allowing an accurate analysis and a better design for the controllers. In addition, this solution enables not only stage 1 to regulate the dc-link voltage on the terminals of stage 2, but also to use a classical Proportional-Integral (<inline-formula><tex-math notation="LaTeX">PI</tex-math></inline-formula>) controller or an adaptive <inline-formula><tex-math notation="LaTeX">\boldsymbol{SoC}</tex-math></inline-formula>-sharing function as a control structure. Finally, stability analysis, simulations, and experimental results are accomplished to evaluate the effectiveness of the proposed approach.
This paper studies the platoon formation control problem for unmanned surface vehicles, in the presence of modeling uncertainties and time-varying external disturbances. The control objective is to ...make the vehicular platoons proceed along a given trajectory while maintaining a desired line-of-sight (LOS) range between each vehicle and its predecessor. To provide transient performance specifications on formation errors, including LOS range and angle errors, we enforce prescribed performance guarantees in the control design. The prescribed performance guarantees mean that formation errors evolve always within the predefined regions that are bounded by exponentially decaying functions of time. Using prescribed performance control methodology, neural network approximation, disturbance observers, dynamic surface control technique, and Lyapunov synthesis, we propose an adaptive formation control that ensures internal stability of closed-loop systems with guaranteed prescribed performance. Meanwhile, both collision avoidance and connectivity maintenance between two consecutive vehicles are guaranteed during the whole operation. The proposed formation control is decentralized in the sense that the control action on each vehicle depends only on information from its immediate predecessor. Simulation results demonstrate the performance of the proposed control.
Transportation accounts for 28% of total energy use and 26% of carbon emissions in the US, and battery electric and plug-in hybrid electric vehicles are promising options to decarbonize ...transportation. Federal and state governments, electric utility operators, and a number of other entities have provided support to accelerate electric vehicle purchases via monetary and non-monetary incentives. In this paper, we evaluate the effect of these incentives on the adoption of electric vehicles. We find that every $1000 offered as a rebate or tax credit increases average sales of electric vehicles by 2.6%. We also find that HOV lane access is a significant contributor to adoption, the effect is a 4.7% increase corresponding to density of HOV lanes (every 100 vehicles per hour). In addition, we introduce a novel variable to capture consumer knowledge of EVs and associated incentives in our model to help explain the state level heterogeneity in response to incentives and find that raising consumer awareness is critical to the success of EV incentive programs.
•$1000 in rebate corresponds to increase of 2.6% in sales.•HOV access contributes 4.7% increase per 100 vehicles using lane per hour.•Knowledge of incentives is crucial in explaining differences between state efficacy of incentives.
Plug-in hybrid electric vehicles (PHEVs) offer an immediate solution for emissions reduction and fuel displacement within the current infrastructure. Targeting PHEV powertrain optimization, a ...plethora of energy management strategies (EMSs) have been proposed. Although these algorithms present various levels of complexity and accuracy, they find a limitation in terms of availability of future trip information, which generally prevents exploitation of the full PHEV potential in real-life cycles. This paper presents a comprehensive analysis of EMS evolution toward blended mode (BM) and optimal control, providing a thorough survey of the latest progress in optimization-based algorithms. This is performed in the context of connected vehicles and highlights certain contributions that intelligent transportation systems (ITSs), traffic information, and cloud computing can provide to enhance PHEV energy management. The study is culminated with an analysis of future trends in terms of optimization algorithm development, optimization criteria, PHEV integration in the smart grid, and vehicles as part of the fleet.
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