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World Electr. Veh. J., Volume 14, Issue 12 (December 2023) – 37 articles

Cover Story (view full-size image): Recent years have shown an increase in the adoption of electric vehicles (EVs) and renewable energy sources to address the need for cleaner transport and energy. This transition leads to higher variability in production and consumption in electricity systems. Vehicle-to-grid (V2G) technology with bidirectional power transfer can address this challenge by engaging EVs in grid-balancing services, while potentially adding a new revenue stream for the EV charging business ecosystem. Building on prior studies and a set of real-life data, this study investigates the financial potential of V2G in grid-balancing services. Specifically, it evaluates the incremental profitability of V2G-enabled automated Frequency Restoration Reserve (aFRR) for the entities managing semi-public EV charging infrastructure. View this paper
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21 pages, 752 KiB  
Article
A GRASP Approach for the Energy-Minimizing Electric Vehicle Routing Problem with Drones
World Electr. Veh. J. 2023, 14(12), 354; https://doi.org/10.3390/wevj14120354 - 18 Dec 2023
Viewed by 1328
Abstract
This study addresses the Electric Vehicle Routing Problem with Drones (EVRPD) by implementing and comparing two variants of the Greedy Randomized Adaptive Search Procedure (GRASP). The primary objective of the EVRPD is to optimize the routing of a combined fleet of ground and [...] Read more.
This study addresses the Electric Vehicle Routing Problem with Drones (EVRPD) by implementing and comparing two variants of the Greedy Randomized Adaptive Search Procedure (GRASP). The primary objective of the EVRPD is to optimize the routing of a combined fleet of ground and aerial vehicles, with the aim of improving delivery efficiency and minimizing energy consumption, which is directly influenced by the weight of the packages. The study assumes a standardized packing system consisting of three weight classes, where deliveries are exclusively performed by drones, while ground vehicles function as mobile depots. The two employed GRASP variants vary in their methods of generating the Restricted Candidate List (RCL), with one utilizing a cardinality-based RCL and the other adopting a value-based RCL. To evaluate their performance, benchmark instances from the existing EVRPD literature are utilized, extensive computational experiments are conducted, and the obtained computational results are compared and discussed. The findings of the research highlight the considerable impact of RCL generation strategies on solution quality. Lastly, the study reports four new best-known values. Full article
(This article belongs to the Special Issue Research on Intelligent Vehicle Path Planning Algorithm)
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13 pages, 6044 KiB  
Article
A Novel Approach for a Predictive Online ECMS Applied in Electrified Vehicles Using Real Driving Data
World Electr. Veh. J. 2023, 14(12), 353; https://doi.org/10.3390/wevj14120353 - 18 Dec 2023
Viewed by 1109
Abstract
To increase the efficiency of electrified vehicles, many energy management strategies (driving strategies) have been proposed. These include both offline optimization techniques to identify a system’s theoretical optimum and online optimization techniques created for onboard use in the vehicle. In the field of [...] Read more.
To increase the efficiency of electrified vehicles, many energy management strategies (driving strategies) have been proposed. These include both offline optimization techniques to identify a system’s theoretical optimum and online optimization techniques created for onboard use in the vehicle. In the field of online optimization, predictive approaches can achieve additional savings. However, predictions are challenging, and robust usability in all driving situations of the vehicle is not guaranteed. In this study, a new approach for a predictive energy management strategy is presented. It is demonstrated how this so-called predictive Online Equivalent Consumption Minimization Strategy (ECMS) can achieve additional fuel savings compared to a non-predictive Online ECMS by predicting recuperation events using map data. As long as the route is known, map data are available, and the current position of the global navigation satellite system (GNSS) is given, the predictive Online ECMS can be applied. If these requirements are not met, the non-predictive basic implementation can still be used to ensure robust functionality. The methodology is investigated using a backward simulation model of a D-segment vehicle powered by a 48 V hybrid electric system in a P2 topology. A dataset including real driving cycles including map data from Open Street Map (OSM) is used. However, the investigations are limited to the consideration of traffic signal (TS) positions on the upcoming route. Simulation results focus on the interaction between the energy management strategy (EMS) and usable battery energy. More than 1 % average saving potentials compared to a non-predictive implementation are shown. The highest saving potentials are found with a usable battery energy of 100 Wh. Full article
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13 pages, 4468 KiB  
Article
TF-YOLO: A Transformer–Fusion-Based YOLO Detector for Multimodal Pedestrian Detection in Autonomous Driving Scenes
World Electr. Veh. J. 2023, 14(12), 352; https://doi.org/10.3390/wevj14120352 - 18 Dec 2023
Viewed by 1535
Abstract
Recent research demonstrates that the fusion of multimodal images can improve the performance of pedestrian detectors under low-illumination environments. However, existing multimodal pedestrian detectors cannot adapt to the variability of environmental illumination. When the lighting conditions of the application environment do not match [...] Read more.
Recent research demonstrates that the fusion of multimodal images can improve the performance of pedestrian detectors under low-illumination environments. However, existing multimodal pedestrian detectors cannot adapt to the variability of environmental illumination. When the lighting conditions of the application environment do not match the experimental data illumination conditions, the detection performance is likely to be stuck significantly. To resolve this problem, we propose a novel transformer–fusion-based YOLO detector to detect pedestrians under various illumination environments, such as nighttime, smog, and heavy rain. Specifically, we develop a novel transformer–fusion module embedded in a two-stream backbone network to robustly integrate the latent interactions between multimodal images (visible and infrared images). This enables the multimodal pedestrian detector to adapt to changing illumination conditions. Experimental results on two well-known datasets demonstrate that the proposed approach exhibits superior performance. The proposed TF-YOLO drastically improves the average precision of the state-of-the-art approach by 3.3% and reduces the miss rate of the state-of-the-art approach by about 6% on the challenging multi-scenario multi-modality dataset. Full article
(This article belongs to the Special Issue Electric Vehicle Autonomous Driving Based on Image Recognition)
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27 pages, 470 KiB  
Article
Cost Minimization for Charging Electric Bus Fleets
World Electr. Veh. J. 2023, 14(12), 351; https://doi.org/10.3390/wevj14120351 - 16 Dec 2023
Viewed by 1088
Abstract
Recent attention for reduced carbon emissions has pushed transit authorities to adopt battery electric buses (BEBs). One challenge experienced by BEB users is extended charge times, which create logistical challenges and may force BEBs to charge when energy is more expensive. Furthermore, BEB [...] Read more.
Recent attention for reduced carbon emissions has pushed transit authorities to adopt battery electric buses (BEBs). One challenge experienced by BEB users is extended charge times, which create logistical challenges and may force BEBs to charge when energy is more expensive. Furthermore, BEB charging leads to high power demands, which can significantly increase monthly power costs and may push the electrical infrastructure beyond its present capacity, requiring expensive upgrades. This work presents a novel method for minimizing the monthly cost of BEB charging while meeting bus route constraints. This method extends previous work by incorporating a more novel cost model, effects from uncontrolled loads, differences between daytime and overnight charging, and variable rate charging. A graph-based network-flow framework, represented by a mixed-integer linear program, encodes the charging action space, physical bus constraints, and battery state of the charge dynamics. The results for three scenarios are considered: uncontested charging, which uses equal numbers of buses and chargers; contested charging, which has more buses than chargers; and variable charge rates. Among other findings, we show that BEBs can be added to the fleet without raising the peak power demand for only the cost of the energy, suggesting that conversion to electrified transit is possible without upgrading power delivery infrastructure. Full article
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18 pages, 6738 KiB  
Article
A Methodology for Applying Skew in an Automotive Interior Permanent Magnet Rotor for Robust Electromagnetic and Noise, Vibration and Harshness Performance
World Electr. Veh. J. 2023, 14(12), 350; https://doi.org/10.3390/wevj14120350 - 15 Dec 2023
Viewed by 1288
Abstract
Interior permanent magnet (IPM) motors in traction applications often employ discrete rotor skewing constructions to reduce torsional excitations and back-EMF harmonics. Although skewing is very effective in reducing cogging torque, the impact on torque ripple is not well understood and can vary significantly [...] Read more.
Interior permanent magnet (IPM) motors in traction applications often employ discrete rotor skewing constructions to reduce torsional excitations and back-EMF harmonics. Although skewing is very effective in reducing cogging torque, the impact on torque ripple is not well understood and can vary significantly over the operating envelope of a motor. Skewing also leads to the creation of a non-zero axial force that may compromise the bearing life if not considered. This paper introduces a holistic methodology for analyzing the effect of skewing, aiming to minimize torsional excitations, axial forces and back-EMF harmonics whilst mitigating the impact on performance and costs. Firstly, analytical models are employed for calculating cogging torque, torque ripple and axial forces. Then, 2D and 3D finite element analysis are used to incorporate the influence of non-linear material behavior. A detailed structural model of the powertrain is employed to calculate the radiated noise and identify key areas allowing a motor designer to reduce noise, vibration and harshness (NVH). A meticulous selection process for the skewing angle, the number of skew stacks and the orientation of skew stacks is developed, giving particular attention to the effect of the selected pattern on NVH in both forward and reverse rotating directions. Full article
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30 pages, 2197 KiB  
Review
Sustainable E-Fuels: Green Hydrogen, Methanol and Ammonia for Carbon-Neutral Transportation
World Electr. Veh. J. 2023, 14(12), 349; https://doi.org/10.3390/wevj14120349 - 14 Dec 2023
Viewed by 2421
Abstract
Increasingly stringent sustainability and decarbonization objectives drive investments in adopting environmentally friendly, low, and zero-carbon fuels. This study presents a comparative framework of green hydrogen, green ammonia, and green methanol production and application in a clear context. By harnessing publicly available data sources, [...] Read more.
Increasingly stringent sustainability and decarbonization objectives drive investments in adopting environmentally friendly, low, and zero-carbon fuels. This study presents a comparative framework of green hydrogen, green ammonia, and green methanol production and application in a clear context. By harnessing publicly available data sources, including from the literature, this research delves into the evaluation of green fuels. Building on these insights, this study outlines the production process, application, and strategic pathways to transition into a greener economy by 2050. This envisioned transformation unfolds in three progressive steps: the utilization of green hydrogen, green ammonia, and green methanol as a sustainable fuel source for transport applications; the integration of these green fuels in industries; and the establishment of mechanisms for achieving the net zero. However, this research also reveals the formidable challenges of producing green hydrogen, green ammonia, and green methanol. These challenges encompass technological intricacies, economic barriers, societal considerations, and far-reaching policy implications necessitating collaborative efforts and innovative solutions to successfully develop and deploy green hydrogen, green ammonia, and green methanol. The findings unequivocally demonstrate that renewable energy sources play a pivotal role in enabling the production of these green fuels, positioning the global transition in the landscape of sustainable energy. Full article
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20 pages, 971 KiB  
Review
Review of Intelligent Vehicle Driving Risk Assessment in Multi-Vehicle Interaction Scenarios
World Electr. Veh. J. 2023, 14(12), 348; https://doi.org/10.3390/wevj14120348 - 14 Dec 2023
Viewed by 1604
Abstract
With the rapid breakthroughs in artificial intelligence technology and intelligent manufacturing technology, automotive intelligence has become a research hotspot, and much progress has been made. However, a skeptical attitude is still held towards intelligent vehicles, especially when driving in a complex multi-vehicle interaction [...] Read more.
With the rapid breakthroughs in artificial intelligence technology and intelligent manufacturing technology, automotive intelligence has become a research hotspot, and much progress has been made. However, a skeptical attitude is still held towards intelligent vehicles, especially when driving in a complex multi-vehicle interaction environment. The interaction among multi-vehicles generally involves more uncertainties in vehicle motion and entails higher driving risk, and thus deserves more research concerns and efforts. Targeting the safety assessment issue of complex multi-vehicle interaction scenarios, this article summarizes the existing literature on the relevant data collection methodologies, vehicle interaction mechanisms, and driving risk evaluation methods for intelligent vehicles. The limitations of the existing assessment methods and the prospects for their future development are analyzed. The results of this article can provide a reference for intelligent vehicles in terms of timely and accurate driving risk assessment in real-world multi-vehicle scenarios and help improve the safe driving technologies of intelligent vehicles. Full article
(This article belongs to the Special Issue Advanced Vehicle System Dynamics and Control)
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17 pages, 3206 KiB  
Article
Investigating Investment Plans for Expanding Battery and Electric Vehicle Production in Europe
World Electr. Veh. J. 2023, 14(12), 347; https://doi.org/10.3390/wevj14120347 - 14 Dec 2023
Viewed by 3119
Abstract
There has been significant EV sales growth in Europe, benefiting from its policies for promoting electric vehicles (EVs) and investments in manufacturing. This study investigates the investment announcements for EV and battery production announced by manufacturers and compares them to four scenarios with [...] Read more.
There has been significant EV sales growth in Europe, benefiting from its policies for promoting electric vehicles (EVs) and investments in manufacturing. This study investigates the investment announcements for EV and battery production announced by manufacturers and compares them to four scenarios with different EV penetration levels in Europe. This study projects the required capacities and estimates the investment needs to meet different EV sale targets in each scenario. The investigations show that, for Europe to achieve 60% new EV sales by 2030 and to be on track for 100% by 2035, its 4.8 million planned production capacity of EVs would fall short of the needed 9.2 million in 2030. The gap could close to 2.0 million when tentative announcements are counted. The results for batteries indicate that tentative plans are adequate and firm plans can satisfy most scenarios by 2030. More investments into EV production, along with policy support and incentives, are needed for more rapid scenarios. Full article
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11 pages, 3519 KiB  
Article
Identification Method and Quantification Analysis of the Critical Aging Speed Interval for Battery Knee Points
World Electr. Veh. J. 2023, 14(12), 346; https://doi.org/10.3390/wevj14120346 - 12 Dec 2023
Viewed by 1245
Abstract
The identification of knee points in lithium-ion (Li-ion) batteries is crucial for predicting the battery life, designing battery products, and managing battery health. Knee points (KPs) refer to the transition points in the aging speed and aging trajectory of Li-ion batteries. KPs can [...] Read more.
The identification of knee points in lithium-ion (Li-ion) batteries is crucial for predicting the battery life, designing battery products, and managing battery health. Knee points (KPs) refer to the transition points in the aging speed and aging trajectory of Li-ion batteries. KPs can be identified using a wealth of aging data and various regression-based methods. However, KP identification relies on a large amount of aging data, which is exceedingly time-consuming and resource-intensive. To overcome this issue, we propose a novel method based on KP characteristics to identify the KPs and critical aging speed. Firstly, we extract the main aging trajectory using curve-fitting techniques. Secondly, we calculate the aging speed at each cycle to identify the KPs. We then explore the relationship between the KPs and cycle life and develop a knee point identification algorithm. The correlation coefficient between the KPs and cycle life provides a valuable indicator of the critical aging speed, enabling accurate identification of KPs. To validate our approach, we apply it to the Li(NiCoMn)O2, LiFePO4, and LiCoO2 cell datasets. Our results demonstrate a strong correlation between the KPs and cycle life for these battery types. By employing our proposed method, KPs can be identified for battery life prediction, product design, and health management. Moreover, we summarize a critical degradation speed of −0.03%/cycle can serve as an empirical threshold for warning against capacity diving and KPs. The statistical transition speed threshold can eliminate the dependence on extensive aging data throughout the entire battery’s lifecycle for identifying capacity knee points. Full article
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24 pages, 4003 KiB  
Article
Public Perception of the Introduction of Autonomous Vehicles
World Electr. Veh. J. 2023, 14(12), 345; https://doi.org/10.3390/wevj14120345 - 12 Dec 2023
Viewed by 1394
Abstract
Autonomous vehicles (AVs) will transform transport, but public opinion will play a key role in decisions on how widely and quickly they are adopted. The purpose of the study presented here was to investigate community’s views on that transition. As a method for [...] Read more.
Autonomous vehicles (AVs) will transform transport, but public opinion will play a key role in decisions on how widely and quickly they are adopted. The purpose of the study presented here was to investigate community’s views on that transition. As a method for primary data collection on public awareness, attitudes, and readiness to use autonomous cars, survey was conducted in Saudi Arabia. Following that, we used statistical tools to analyse responses. Our findings indicate that the participants are largely receptive to using new technologies and had favourable attitudes towards the transition. Ordinal logistic regression model showed a wide variation in public opinion regarding the expected benefits that may accompany the transition. Our findings reveal that awareness of AVs’ benefits is positively correlated with the age of participants. Perceived costs on one side, and convenience and safety on the other, were found to have had a substantial impact on the opinions of the participants. Investigation presented here shows a sample of the public’s perception of AVs in Saudi Arabia. This can guide the development of AVs and their deployment in that region as well as worldwide. Full article
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25 pages, 10464 KiB  
Article
Optimization Design of Parking Models Based on Complex and Random Parking Environments
World Electr. Veh. J. 2023, 14(12), 344; https://doi.org/10.3390/wevj14120344 - 12 Dec 2023
Viewed by 1132
Abstract
This paper presents a comprehensive study on autonomous vehicle parking challenges, focusing on kinematic and reverse parking models. The research develops models for various scenarios, including turning, reverse, vertical, and parallel parking while using the minimum turning radius solution. The integration of the [...] Read more.
This paper presents a comprehensive study on autonomous vehicle parking challenges, focusing on kinematic and reverse parking models. The research develops models for various scenarios, including turning, reverse, vertical, and parallel parking while using the minimum turning radius solution. The integration of the A* algorithm enhances trajectory optimization and obstacle avoidance. Innovative concepts like NTBPT and B-spline theory improve computational optimization. This study provides a foundation for understanding the dynamics and constraints of autonomous parking. The proposed model enhances efficiency and safety, reducing algorithm complexity and improving trajectory optimization. This research offers valuable insights and methodologies for addressing autonomous vehicle parking challenges and advocates for advancements in automated parking systems. Full article
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22 pages, 4195 KiB  
Article
Research on Stability Control Algorithm of Distributed Drive Bus under High-Speed Conditions
World Electr. Veh. J. 2023, 14(12), 343; https://doi.org/10.3390/wevj14120343 - 12 Dec 2023
Viewed by 1046
Abstract
Aiming at the instability problem of a four-wheel independent drive electric bus under high-speed conditions, this paper first designs a vehicle yaw stability controller based on a linear two-degree-of-freedom model and a linear quadratic programming (LQR) algorithm. A vehicle roll stability controller is [...] Read more.
Aiming at the instability problem of a four-wheel independent drive electric bus under high-speed conditions, this paper first designs a vehicle yaw stability controller based on a linear two-degree-of-freedom model and a linear quadratic programming (LQR) algorithm. A vehicle roll stability controller is then designed based on a linear three-degree-of-freedom model and a model predictive control algorithm (MPC). Moreover, a coordinated control rule based on the lateral load transfer rate (LTR) is designed for the coupled problem of yaw and roll dynamics. Finally, the effectiveness of the proposed control algorithm is verified by simulation. The obtained results show that when the vehicle is running at a high speed of 90 km/h, the stability control algorithm can control the yaw rate tracking error within 0.05 rad/s. In addition, the control algorithm can reduce the maximum amplitude of the side slip angle, the maximum value of the roll angle, the maximum value of the roll angular velocity, and the amplitude of the lateral acceleration by more than 96%, 81.1%, 65.0%, and 11.1%, respectively. Full article
(This article belongs to the Special Issue Dynamics, Control and Simulation of Electrified Vehicles)
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16 pages, 2630 KiB  
Article
Electric Vehicle Drivetrain Efficiency and the Multi-Speed Transmission Question
World Electr. Veh. J. 2023, 14(12), 342; https://doi.org/10.3390/wevj14120342 - 07 Dec 2023
Viewed by 1706
Abstract
The availability of high-fidelity energy consumption estimates and the ability to evaluate drivetrain efficiency are crucial for effectively planning a large-scale transition to electric vehicles. For both new and retrofitted electric vehicles, a key question is the transmission type—single-speed or multi-speed—and the resulting [...] Read more.
The availability of high-fidelity energy consumption estimates and the ability to evaluate drivetrain efficiency are crucial for effectively planning a large-scale transition to electric vehicles. For both new and retrofitted electric vehicles, a key question is the transmission type—single-speed or multi-speed—and the resulting impact on the vehicle’s overall efficiency. This paper presents a comprehensive simulation-based methodology for evaluating the impact of transmission selection on vehicle efficiency using high-fidelity driving cycle data. The method can be used for new vehicles and retrofit applications where a transmission is already present. The efficiency of a single-speed reduction gearbox was compared to that of a five-speed multi-speed transmission in a retrofitted vehicle, of which the impact of the manual transmission on the vehicle dynamics and efficiency was examined. The manual transmission proved to be more efficient for a perfect gear-shifting strategy. Full article
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15 pages, 8227 KiB  
Article
A High-Precision Car-Following Model with Automatic Parameter Optimization and Cross-Dataset Adaptability
World Electr. Veh. J. 2023, 14(12), 341; https://doi.org/10.3390/wevj14120341 - 07 Dec 2023
Viewed by 1063
Abstract
Despite the significant impact of network hyperparameters on deep learning car-following models, there has been relatively little research on network hyperparameters of deep learning car-following models. Therefore, this study proposes a car-following model that combines particle swarm optimization (PSO) and gated recurrent unit [...] Read more.
Despite the significant impact of network hyperparameters on deep learning car-following models, there has been relatively little research on network hyperparameters of deep learning car-following models. Therefore, this study proposes a car-following model that combines particle swarm optimization (PSO) and gated recurrent unit (GRU) networks. The PSO-GRU car-following model is trained and tested using data from the natural driving database. The results demonstrate that compared to the intelligent driver model (IDM) and the GRU car-following model, the PSO-GRU car-following model reduces the mean squared error (MSE) for the speed simulation of following vehicles by 88.36% and 72.92%, respectively, and reduces the mean absolute percentage error (MAPE) by 64.81% and 50.14%, respectively, indicating a higher prediction accuracy. Dataset 3 from the drone video trajectory database of Southeast University and NGSIM’s I-80 dataset are used to study the car-following model’s cross-dataset adaptability, that is, to verify its transferability. Compared to the GRU car-following model, the PSO-GRU car-following model reduces the standard deviation of the test results by 60.64% and 32.89%, highlighting its more robust prediction stability and better transferability. Verifying the ability of the car-following model to produce the stop-and-go phenomenon can evaluate its transferability more comprehensively. The PSO-GRU car-following model outperforms the GRU car-following model in creating stop-and-go sensations through platoon simulation tests, demonstrating its superior transferability. Therefore, the proposed PSO-GRU car-following model has higher prediction accuracy and cross-dataset adaptability compared to other car-following models. Full article
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24 pages, 16826 KiB  
Article
Research on the Multimode Switching Control of Intelligent Suspension Based on Binocular Distance Recognition
World Electr. Veh. J. 2023, 14(12), 340; https://doi.org/10.3390/wevj14120340 - 07 Dec 2023
Viewed by 1247
Abstract
As the upgrade of people’s requirements for automotive driving comfort, conventional passive suspensions for cars have fallen short of existing demands due to their nonadjustable damping and stiffness, so semiactive suspensions and active suspensions have gained growing acceptance. Compared with active suspensions, semiactive [...] Read more.
As the upgrade of people’s requirements for automotive driving comfort, conventional passive suspensions for cars have fallen short of existing demands due to their nonadjustable damping and stiffness, so semiactive suspensions and active suspensions have gained growing acceptance. Compared with active suspensions, semiactive suspensions offer the advantages of a low manufacturing cost and reliable structure, and thus have become the preferred choice for most vehicles. To optimize the control effect of semiactive suspensions under different working conditions, this paper completed the modeling of magnetorheological semiactive suspension system dynamics and road inputs; then, the design of binocular camera sensing algorithms was performed to obtain the real-time distance of the target using the point cloud ranging function, and the parameters required for suspension control were also obtained. This was followed by the completion of the control-mode-switching rules and the design of the suspension controller. According to the different control objectives, the mode could be divided into the obstacle-road mode, straight-road mode, and curved-road mode. The suspension controller included the BP-PID (neural network PID controller) controller and the force distributor. Finally, the effectiveness of the mode-switching rules and the control method was verified through system simulation and the hardware-in-the-loop test. Full article
(This article belongs to the Special Issue New Energy Special Vehicle, Tractor and Agricultural Machinery)
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13 pages, 1362 KiB  
Article
Incremental Profitability Evaluation of Vehicle-to-Grid-Enabled Automated Frequency Restoration Reserve Services for Semi-Public Charging Infrastructure: A Case Study in Belgium
World Electr. Veh. J. 2023, 14(12), 339; https://doi.org/10.3390/wevj14120339 - 06 Dec 2023
Viewed by 2478
Abstract
The current paper defines a framework for the introduction of automated frequency restoration reserve services, enabled by vehicle-to-grid technology, into the business model of an entity owning and operating a network of semi-public Electric Vehicle Supply Equipment. It assesses the profitability of this [...] Read more.
The current paper defines a framework for the introduction of automated frequency restoration reserve services, enabled by vehicle-to-grid technology, into the business model of an entity owning and operating a network of semi-public Electric Vehicle Supply Equipment. It assesses the profitability of this introduction by performing a case study based on the real-life electric vehicle charging data from the EVSE network located in a hospital parking lot. From the results of the study, it is clearly visible that the introduction of vehicle-to-grid-enabled automated frequency restoration reserve services has a significant positive incremental profitability; however, this is heavily dependent on the plug-in ratio of the charging network, determined by electric vehicle users’ behavior. Full article
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22 pages, 2873 KiB  
Article
PLUG: A City-Friendly Navigation Model for Electric Vehicles with Power Load Balancing upon the Grid
World Electr. Veh. J. 2023, 14(12), 338; https://doi.org/10.3390/wevj14120338 - 06 Dec 2023
Viewed by 1085
Abstract
Worldwide, in many cities, electric vehicles (EVs) have started to spread as a green alternative in transportation. Several well-known automakers have announced their plans to switch to all-electric engines very soon, although for EV drivers, battery range is still a significant concern—especially when [...] Read more.
Worldwide, in many cities, electric vehicles (EVs) have started to spread as a green alternative in transportation. Several well-known automakers have announced their plans to switch to all-electric engines very soon, although for EV drivers, battery range is still a significant concern—especially when driving on long-distance trips and driving EVs with limited battery ranges. Cities have made plans to serve this new form of transportation by providing adequate coverage of EV charging stations in the same way as traditional fuel ones. However, such plans may take a while to be fully deployed and provide the required coverage as appropriate. In addition to the coverage of charging stations, cities need to consider the potential loads over their power grids not only to serve EVs but also to avoid any shortages that may affect existing clients at their various locations. This may take a decade or so. Consequently, in this work, we propose a novel city-friendly navigation model that is oriented to serve EVs in particular. The methodology of this model involves reading real-time power loads at the grid’s transformer nodes and accordingly choosing the routes for EVs to their destinations. Our methodology follows a real-time pricing model to prioritize routes that pass through less-loaded city zones. The model is developed to be self-aware and adaptive to dynamic price changes, and hence, it nominates the shortest least-loaded routes in an automatic and autonomous way. Moreover, the drivers have further routing preferences that are modeled by a preference function with multiple weight variables that vary according to a route’s distance, cost, time, and services. Different from other models in the literature, this is the first work to address the dynamic loads of the electricity grids among various city zones for load-balanced EV routing in an automatic way. This allows for the easy integration of EVs through a city-friendly and anxiety-free navigation model. Full article
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28 pages, 4696 KiB  
Article
PerfECT Design Tool: Electric Vehicle Modelling and Experimental Validation
World Electr. Veh. J. 2023, 14(12), 337; https://doi.org/10.3390/wevj14120337 - 05 Dec 2023
Cited by 2 | Viewed by 1599
Abstract
This article addresses a common issue in the design of battery electric vehicles (BEVs) by introducing a comprehensive methodology for the modeling and simulation of BEVs, referred to as the “PerfECT Design Tool”. The primary objective of this study is to provide engineers [...] Read more.
This article addresses a common issue in the design of battery electric vehicles (BEVs) by introducing a comprehensive methodology for the modeling and simulation of BEVs, referred to as the “PerfECT Design Tool”. The primary objective of this study is to provide engineers and researchers with a robust and streamlined approach for the early stages of electric vehicle (EV) design, offering valuable insights into the performance, energy consumption, current flow, and thermal behavior of these advanced automotive systems. Recognizing the complex nature of contemporary EVs, the study highlights the need for efficient design tools that facilitate decision-making during the conceptual phases of development. The PerfECT Design Tool is presented as a multi-level framework, divided into four logically sequential modules: Performance, Energy, Currents, and Temperature. These modules are underpinned by sound theoretical foundations and are implemented using a combination of MATLAB/Simulink and the vehicle dynamics software VI-CRT. The research culminates in the validation of the model through a series of experimental maneuvers conducted with a Tesla Model 3, establishing its accuracy in representing the mechanical, electrical, and thermal behavior of BEVs. The study’s main findings underscore the viability of the design tool as an asset in the initial phases of BEV design. Beyond its primary application, the tool holds promise for broader utilization, including the development of active control systems, advanced driver assistance systems (ADAS), and solutions for autonomous driving within the domain of electric vehicles. Full article
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15 pages, 2248 KiB  
Article
A Novel Dynamic Li-Ion Battery Model for the Aggregated Charging of EVs
World Electr. Veh. J. 2023, 14(12), 336; https://doi.org/10.3390/wevj14120336 - 04 Dec 2023
Viewed by 1385
Abstract
Implementing successful aggregated charging strategies for electric vehicles to participate in the wholesale market requires an accurate battery model that can operate at scale while capturing critical battery dynamics. Existing models either lack precision or pose computational challenges for fleet-level coordination. To our [...] Read more.
Implementing successful aggregated charging strategies for electric vehicles to participate in the wholesale market requires an accurate battery model that can operate at scale while capturing critical battery dynamics. Existing models either lack precision or pose computational challenges for fleet-level coordination. To our knowledge, most of the literature widely adopts battery models that neglect critical battery polarization dynamics favoring scalability over accuracy, donated as constant power models (CPMs). Thus, this paper proposes a novel linear battery model (LBM) intended specifically for use in aggregated charging strategies. The LBM considers battery dynamics through a linear representation, addressing the limitations of existing models while maintaining scalability. The model dynamic behavior is evaluated for the four commonly used lithium-ion chemistries in EVs: lithium iron phosphate (LFP), nickel manganese cobalt (NMC), lithium manganese oxide (LMO), and nickel cobalt aluminum (NCA). The results showed that the LBM closely matches the high-fidelity Thevenin equivalent circuit model (Th-ECM) with substantially improved accuracy over the CPM, especially at higher charging rates. Finally, a case study was carried out for bidding in the wholesale energy market, which proves the ability of the model to scale. Full article
(This article belongs to the Special Issue Electric Vehicles and Smart Grid Interaction)
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17 pages, 5020 KiB  
Article
A System for the Efficient Charging of EV Fleets
World Electr. Veh. J. 2023, 14(12), 335; https://doi.org/10.3390/wevj14120335 - 02 Dec 2023
Viewed by 1408
Abstract
Smart charging is a means of monitoring and actively controlling EV chargers to optimize the distribution and consumption of energy with a focus on peak-load avoidance. This paper describes the most important requirements that have influenced the design and implementation of the “Smart [...] Read more.
Smart charging is a means of monitoring and actively controlling EV chargers to optimize the distribution and consumption of energy with a focus on peak-load avoidance. This paper describes the most important requirements that have influenced the design and implementation of the “Smart Charging System” (SCS). It presents the architecture and main functional building blocks of the SCS, which have been realized in an iterative development process as an extension component of the already existing open-source solution “Open e-Mobility”. We also provide details on the functionality of the core smart charging algorithm within SCS and show how various data sources can be utilized by the system to increase the safety and efficiency of EV charging processes. Furthermore, we describe our iterative approach to developing the system, introduce the real-world testbed at SAP Labs France in Mougins/France, and share evaluation results and experiences gathered over a three-year period. Full article
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26 pages, 4103 KiB  
Article
Determination of the Reliability of Urban Electric Transport Running Autonomously through Diagnostic Parameters
World Electr. Veh. J. 2023, 14(12), 334; https://doi.org/10.3390/wevj14120334 - 01 Dec 2023
Cited by 4 | Viewed by 1321
Abstract
The urban transport network involves complex processes, operating 24 h a day and 365 days a year. The sustainable development of the urban transport network using electric buses and trolleybuses that run autonomously is an urgent task since the transport network performs integral [...] Read more.
The urban transport network involves complex processes, operating 24 h a day and 365 days a year. The sustainable development of the urban transport network using electric buses and trolleybuses that run autonomously is an urgent task since the transport network performs integral social functions and is the transport artery of any urban center. The social and economic life of a city as a whole depends on the reliability of the transportation network. A theory is proposed for the technical and economic evaluation of reliability improvement in electric buses and trolleybuses running autonomously, which enables the determination of the reliability parameters of electric buses and forecasts for the future from the point of view of optimal economic costs for the operation of electric equipment in electric buses. As a result of the application of the proposed theory, it was found that increasing the reliability of the transportation fleet can lead to a decrease in both specific operating costs and capital investments in the development of the fleet. This is achieved as a result of increasing the annual productivity of vehicles by reducing the time they are out of service to eliminate the consequences of failures and carry out maintenance and repair. The conducted experiments confirmed that the theory and methodology of optimal reliability level selection not only enable the rational use of the material resources of the urban transport network but also the release of funds for its scientific and technical development by reducing the number of failures in the electrical equipment of transport systems by 14%. Full article
(This article belongs to the Special Issue Electric Vehicle Networking and Traffic Control)
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15 pages, 3093 KiB  
Article
Assessment of the On-Road Performance of Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs) in Urban Road Conditions in the Philippines
World Electr. Veh. J. 2023, 14(12), 333; https://doi.org/10.3390/wevj14120333 - 01 Dec 2023
Viewed by 1786
Abstract
This current and pioneering work aimed to assess the on-road performance of selected hybrid electric vehicles (HEVs) and electric vehicles (EVs) in local urban road conditions following the World Harmonized Light Vehicles Test Procedure (WLTP) and the chase car protocol. An experimental research [...] Read more.
This current and pioneering work aimed to assess the on-road performance of selected hybrid electric vehicles (HEVs) and electric vehicles (EVs) in local urban road conditions following the World Harmonized Light Vehicles Test Procedure (WLTP) and the chase car protocol. An experimental research design was also implemented to investigate the effects of the different payload conditions on vehicle performance, and corresponding drive cycle patterns for the test vehicles were generated from each on-road test. From the series of these on-road tests, it was revealed that there was high variability in speed profiles, and vehicle speed was generally found to be inversely related to payload weight. The variations in the state of charge, fuel fill-up, and fuel and energy parameters exhibited no significant differences in terms of payload conditions. When compared to both the Canada fuel consumption guide and the US fuel consumption guide, the resulting fuel consumption and energy consumption indicated that the Mitsubishi Outlander PHEV and Mitsubishi iMiEV exceeded energy efficiency standards, unlike the Toyota Prius. Meanwhile, in terms of CO2 emissions, all vehicles demonstrated around 40–70% lower emissions compared to conventional vehicles according to the 2023 estimates of the US Environmental Protection Agency. Being the first of its kind in the Philippines, this study on the on-road performance assessments of HEVs and EVs is essential because it provides empirical data on these vehicles’ actual performance in everyday driving conditions. The data are important for evaluating the potential to address environmental concerns, promote sustainable transportation solutions, influence consumer adoption, and shape government policies. With ongoing improvements in technology and expanding charging infrastructure, HEVs and EVs are poised for significant adoption in the coming years. Full article
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18 pages, 12989 KiB  
Article
Energy Management Strategy for P1 + P3 Plug-In Hybrid Electric Vehicles
World Electr. Veh. J. 2023, 14(12), 332; https://doi.org/10.3390/wevj14120332 - 30 Nov 2023
Viewed by 1182
Abstract
In order to simultaneously improve the fuel economy and overall performance of plug-in hybrid electric vehicles (PHEVs), this study selected the P1 + P3 configuration as its research object. Through a configuration analysis of hybrid vehicles, it confirmed the feasibility of P1 + [...] Read more.
In order to simultaneously improve the fuel economy and overall performance of plug-in hybrid electric vehicles (PHEVs), this study selected the P1 + P3 configuration as its research object. Through a configuration analysis of hybrid vehicles, it confirmed the feasibility of P1 + P3 configuration-PHEV operating modes. Based on this, a rule-based control strategy was developed, and simulation models for the entire vehicle and control strategy were constructed in both Cruise and MATLAB/Simulink software. The study conducted simulation analysis by combining three sets of Worldwide Harmonized Light vehicles Test Cycle (WLTC) driving cycles to assess the fuel-saving potential of the dual-motor P1 + P3 configuration. The simulation results showed that the vehicle model was reasonably constructed and the proposed control strategy had good control effects on the entire vehicle. Compared to conventional gasoline vehicles, the P1 + P3 configuration PHEV achieved a 67.4% fuel economy improvement, demonstrating a significant enhancement in fuel efficiency with the introduction of electric motors. Full article
(This article belongs to the Special Issue Vehicle System Dynamics and Intelligent Control for Electric Vehicles)
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3 pages, 184 KiB  
Editorial
Emerging Technologies in the Electrification of Urban Mobility
World Electr. Veh. J. 2023, 14(12), 331; https://doi.org/10.3390/wevj14120331 - 30 Nov 2023
Viewed by 1045
Abstract
The Paris Agreement limits the long-term global warming goal to well below 2 and preferably to 1 [...] Full article
(This article belongs to the Special Issue Emerging Technologies in Electrification of Urban Mobility)
17 pages, 4441 KiB  
Article
Energy Cost Analysis and Operational Range Prediction Based on Medium- and Heavy-Duty Electric Vehicle Real-World Deployments across the United States
World Electr. Veh. J. 2023, 14(12), 330; https://doi.org/10.3390/wevj14120330 - 30 Nov 2023
Viewed by 1813
Abstract
While the market for medium- and heavy-duty battery-electric vehicles (MHD EVs) is still nascent, a growing number of these vehicles are being deployed across the U.S. This study used over 2.3 million miles of operational data from multiple types of MHD EVs across [...] Read more.
While the market for medium- and heavy-duty battery-electric vehicles (MHD EVs) is still nascent, a growing number of these vehicles are being deployed across the U.S. This study used over 2.3 million miles of operational data from multiple types of MHD EVs across various regions and operating conditions to address knowledge gaps in total cost of ownership and operational range. First, real-world energy cost savings were determined: MHD fleets should experience energy cost savings each year from 2021 to 2035, regardless of vehicle platform, with the greatest savings seen in transit buses (up to USD 4459 annually) and HD trucks (up to USD 3284 annually). Second, to help fleets across various geographies throughout the U.S. assess the suitability of EVs for their year-round operating needs, operational range was modeled using the XGBoost algorithm (R2: 70%) given 22 input features relevant to vehicle efficiency. Finally, this paper recommends (1) that MHD fleets apply energy-saving practices to minimize the impacts of cold temperatures and high congestion levels on vehicle efficiency and range, and (2) that local hauling fleets select trucks with a nominal range nearly double the expected maximum daily range to account for range losses under local, urban driving conditions. Full article
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15 pages, 4325 KiB  
Article
Data-Driven Algorithm Based on Energy Consumption Estimation for Electric Bus
World Electr. Veh. J. 2023, 14(12), 329; https://doi.org/10.3390/wevj14120329 - 29 Nov 2023
Viewed by 1186
Abstract
The accurate estimation of battery state of charge (SOC) for modern electric vehicles is crucial for the range and performance of electric vehicles. This paper focuses on the historical driving data of electric buses and focuses on the extraction of driving condition feature [...] Read more.
The accurate estimation of battery state of charge (SOC) for modern electric vehicles is crucial for the range and performance of electric vehicles. This paper focuses on the historical driving data of electric buses and focuses on the extraction of driving condition feature parameters and data preprocessing. By selecting relevant parameters, a set of characteristic parameters for specific driving conditions is established, a process of constructing a battery SOC prediction model based on a Long short-term memory (LSTM) network is proposed, and different hyperparameters of the model are identified and adjusted to improve the accuracy of the prediction results. The results show that the prediction results can reach 1.9875% Root Mean Square Error (RMSE) and 1.7573% Mean Absolute Error (MAE) after choosing appropriate hyperparameters; this approach is expected to improve the performance of battery management systems and battery utilization efficiency in the field of electric vehicles. Full article
(This article belongs to the Special Issue Deep Learning Applications for Electric Vehicles)
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15 pages, 3770 KiB  
Article
Impact of V2G Flexibility on Congestion Management in the German Transmission Grid
World Electr. Veh. J. 2023, 14(12), 328; https://doi.org/10.3390/wevj14120328 - 29 Nov 2023
Viewed by 1101
Abstract
In this study, we investigate the effect of vehicle-to-grid (V2G) flexibility potential on solving transmission grid congestion in Germany using congestion management measures. We extend existing work on effects of V2G on transmission grid congestion by determining the flexibility provided for improving grid [...] Read more.
In this study, we investigate the effect of vehicle-to-grid (V2G) flexibility potential on solving transmission grid congestion in Germany using congestion management measures. We extend existing work on effects of V2G on transmission grid congestion by determining the flexibility provided for improving grid operation based on mobility behavior and findings on V2G user requirements from real-world electric vehicle users. Furthermore, the impact on transmission grid operation is analyzed using an optimal congestion management model with high temporal and spatial resolution. Using a scenario for the year 2030 with ambitious targets for European renewable generation development and electrification of private vehicles, our findings show that by enabling the available fleet of V2G vehicles to participate in congestion management, cost and amount can be reduced by up to 11%. However, the required capacity is shown to be lower than installed capacities in ambitious future scenarios, implying that a limited number of vehicles close to congestion centers will be utilized for transmission grid operation. Our results further suggest that high numbers of vehicles with low availability of V2G for grid operation purposes can lead to an increase in congestion management measures, while V2G proves beneficial for congestion management emissions and cost in all scenarios. Full article
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16 pages, 3235 KiB  
Article
Low-Carbon Incentive Guidance Strategy for Electric Vehicle Agents Based on Carbon Emission Flow
World Electr. Veh. J. 2023, 14(12), 327; https://doi.org/10.3390/wevj14120327 - 28 Nov 2023
Viewed by 1072
Abstract
The cleanliness of charging power determines whether electric vehicles can fully utilize their low-carbon properties. This paper, taking into account the impact of temperature on the energy consumption of electric vehicle air conditioning, uses the Monte Carlo algorithm to calculate the typical daily [...] Read more.
The cleanliness of charging power determines whether electric vehicles can fully utilize their low-carbon properties. This paper, taking into account the impact of temperature on the energy consumption of electric vehicle air conditioning, uses the Monte Carlo algorithm to calculate the typical daily charging load of electric vehicle clusters in different seasons. Secondly, based on the Shapley value carbon responsibility allocation method, a reasonable range of carbon emission responsibilities for different electric vehicle agents is calculated, and a tiered carbon pricing method is proposed accordingly. Then, using carbon emission flow theory, we calculate the carbon emissions generated by the different agents’ charging amounts and corresponding carbon emission costs. Finally, a low-carbon incentive guidance model is constructed with the signal of tiered carbon prices and the goal of minimizing operating costs to re-optimize the charging load distribution of electric vehicles. Case studies showcase that the proposed method is effective in reducing power system carbon emissions and electric vehicle charging costs. Full article
(This article belongs to the Special Issue Electric Vehicles and Smart Grid Interaction)
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9 pages, 257 KiB  
Article
Acceptance of E-Motorcycles: A Longitudinal Survey at Loewensteiner Platte, South Germany
World Electr. Veh. J. 2023, 14(12), 326; https://doi.org/10.3390/wevj14120326 - 28 Nov 2023
Viewed by 1192
Abstract
The acceptance of e-motorcycles among German motorcyclists is the focus of this quantitative longitudinal study. By comparing survey results from 2017 and 2022, questions about changes in perception of e-motorcycles over time as well as possible stimulating factors are analyzed. The research design [...] Read more.
The acceptance of e-motorcycles among German motorcyclists is the focus of this quantitative longitudinal study. By comparing survey results from 2017 and 2022, questions about changes in perception of e-motorcycles over time as well as possible stimulating factors are analyzed. The research design is built upon literature research, a secondary literature analysis, and a survey of motorcyclists. Statistical procedures are used for data analysis and interpretation. The literature analysis enables the present study to be integrated into the current state of research. The findings show that the willingness to consider an e-motorcycle as the next purchase was low in 2017 and dropped from 20% to 5% in 2022, which contrasts with the rising sales figures of e-motorcycles in the German market. Based on these findings, conclusions are drawn about the market potential of e-motorcycles in Germany and an overview of the general assessments and concerns of motorcyclists is provided. Full article
33 pages, 3019 KiB  
Review
Review of Management System and State-of-Charge Estimation Methods for Electric Vehicles
World Electr. Veh. J. 2023, 14(12), 325; https://doi.org/10.3390/wevj14120325 - 27 Nov 2023
Viewed by 1913
Abstract
Energy storage systems (ESSs) are critically important for the future of electric vehicles. Due to the shifting global environment for electrical distribution and consumption, energy storage systems (ESS) are amongst the electrical power system solutions with the fastest growing market share. Any ESS [...] Read more.
Energy storage systems (ESSs) are critically important for the future of electric vehicles. Due to the shifting global environment for electrical distribution and consumption, energy storage systems (ESS) are amongst the electrical power system solutions with the fastest growing market share. Any ESS must have the capacity to regulate the modules from the system in the case of abnormal situations as well as the ability to monitor, control, and maximize the performance of one or more battery modules. Such a system is known as a battery management system (BMS). One parameter that is included in the BMS is the state-of-charge (SOC) of the battery. The BMS is used to enhance battery performance while including the necessary safety measures in the system. SOC estimation is a key BMS feature, and precise modelling and state estimation will improve stable operation. This review discusses the current methods used in BEV LIB SOC modelling and estimation. It also efficiently monitors all of the electrical characteristics of a battery-pack system, including the voltage, current, and temperature. The main function of a BMS is to safeguard a battery system for machine electrification and electric propulsion. The major responsibility of the BMS is to guarantee the trustworthiness and safety of the battery cells coupled to create high currents at high voltage levels. This article examines the advancements and difficulties in (i) cutting-edge battery technology and (ii) cutting-edge BMS for electric vehicles (EVs). This article’s main goal is to outline the key characteristics, benefits and drawbacks, and recent technological developments in SOC estimation methods for a battery. The study follows the pertinent industry standards and addresses the functional safety component that concerns BMS. This information and knowledge will be valuable for vehicle manufacturers in the future development of new SOC methods or an improvement in existing ones. Full article
(This article belongs to the Special Issue Dynamics, Control and Simulation of Electrified Vehicles)
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