World Electric Vehicle Journal

16 pages, 1925 KiB

Open AccessArticle

Harmonic Resonance Mechanisms and Influencing Factors of Distributed Energy Grid-Connected Systems

by Minrui Xu, Zhixin Li, Shufeng Lu, Tianyang Xu, Zhanqi Zhang and Xiangjun Quan

World Electr. Veh. J. 2024, 15(7), 287; https://0-doi-org.brum.beds.ac.uk/10.3390/wevj15070287 - 26 Jun 2024

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With the rapid development of global energy transformation and new power system, ensuring the stability of distributed energy grid connections is the key to maintaining the reliable operation of the whole power system. This paper constructs detailed impedance models of grid-following (GFL) and [...] Read more.

With the rapid development of global energy transformation and new power system, ensuring the stability of distributed energy grid connections is the key to maintaining the reliable operation of the whole power system. This paper constructs detailed impedance models of grid-following (GFL) and grid-forming (GFM) inverters using a harmonic linearization method and thoroughly investigates the mechanisms of resonance when inverters are connected to the grid, as well as the impact of model parameters on the stability of the grid system. This paper also briefly analyzes the scenario where distributed energy and electric vehicles are integrated into the grid simultaneously, demonstrating that grid system stability can be ensured in complex grid situations through reasonable parameter design. Lastly, the accuracy of the proposed impedance models and analysis is verified through MATLAB/Simulink simulations. Full article

(This article belongs to the Special Issue Active Voltage and Frequency Support Control by the EV, New Energy and Energy Storages)

31 pages, 1778 KiB

Open AccessReview

A Comprehensive Review on Smart Electromobility Charging Infrastructure

by Idowu Adetona Ayoade and Omowunmi Mary Longe

World Electr. Veh. J. 2024, 15(7), 286; https://0-doi-org.brum.beds.ac.uk/10.3390/wevj15070286 - 26 Jun 2024

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Abstract

This study thoroughly analyses Smart Electromobility Charging Infrastructure (SECI), exploring its multifaceted dimensions and advancements. Delving into the intricate landscape of SECI, the study critically evaluates existing technologies, integration methodologies, and emerging trends. Through a systematic examination of literature and empirical studies, the [...] Read more.

This study thoroughly analyses Smart Electromobility Charging Infrastructure (SECI), exploring its multifaceted dimensions and advancements. Delving into the intricate landscape of SECI, the study critically evaluates existing technologies, integration methodologies, and emerging trends. Through a systematic examination of literature and empirical studies, the article elucidates the evolving ecosystem of smart charging solutions, considering aspects including advancements in charging protocols. Additionally, the review highlights challenges and prospects in the SECI domain, providing insightful information for scholars, practitioners, and policymakers involved in the dynamic field of electromobility. Technical potentials, including functionalities and integration with the smart grid, have been thoroughly reviewed. An analysis is conducted on the effects of intelligent charging on power distribution systems and strategies to lessen these effects. This study also examines the development of intelligent charging algorithms, optimisation methods, and security analysis. This paper, therefore, contributes to fostering a more thorough comprehension of the current state and future trajectories of Smart Electromobility Charging Infrastructure. Full article

(This article belongs to the Special Issue Smart Charging Strategies for Plug-In Electric Vehicles)

19 pages, 8867 KiB

Open AccessArticle

CTM-YOLOv8n: A Lightweight Pedestrian Traffic-Sign Detection and Recognition Model with Advanced Optimization

by Qiang Chen, Zhongmou Dai, Yi Xu and Yuezhen Gao

World Electr. Veh. J. 2024, 15(7), 285; https://0-doi-org.brum.beds.ac.uk/10.3390/wevj15070285 - 26 Jun 2024

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Abstract

Traffic-sign detection and recognition (TSDR) is crucial to avoiding harm to pedestrians, especially children, from intelligent connected vehicles and has become a research hotspot. However, due to motion blurring, partial occlusion, and smaller sign sizes, pedestrian TSDR faces increasingly significant challenges. To overcome [...] Read more.

Traffic-sign detection and recognition (TSDR) is crucial to avoiding harm to pedestrians, especially children, from intelligent connected vehicles and has become a research hotspot. However, due to motion blurring, partial occlusion, and smaller sign sizes, pedestrian TSDR faces increasingly significant challenges. To overcome these difficulties, a CTM-YOLOv8n model is proposed based on the YOLOv8n model. With the aim of extracting spatial features more efficiently and making the network faster, the C2f Faster module is constructed to replace the C2f module in the head, which applies filters to only a few input channels while leaving the remaining ones untouched. To enhance small-sign detection, a tiny-object-detection (TOD) layer is designed and added to the first C2f layer in the backbone. Meanwhile, the seventh Conv layer, eighth C2f layer, and connected detection head are deleted to reduce the quantity of model parameters. Eventually, the original CIoU is replaced by the MPDIoU, which is better for training deep models. During experiments, the dataset is augmented, which contains the choice of categories ‘w55’ and ‘w57’ in the TT100K dataset and a collection of two types of traffic signs around the schools in Tianjin. Empirical results demonstrate the efficacy of our model, showing enhancements of 5.2% in precision, 10.8% in recall, 7.0% in F1 score, and 4.8% in mAP@0.50. However, the number of parameters is reduced to 0.89M, which is only 30% of the YOLOv8n model. Furthermore, the proposed CTM-YOLOv8n model shows superior performance when tested against other advanced TSDR models. Full article

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31 pages, 980 KiB

Open AccessArticle

Factors Influencing the Adoption of Electric Jeepneys: A Philippine Perspective

by Ma. Janice J. Gumasing, Elgene Dayne R. Ramos, Joshua Nathaniel C. Corpuz, Angelo James B. Ofianga, Juan Miguel R. Palad, Lyce Gariel B. Urbina, Mellicynt M. Mascariola and Ardvin Kester S. Ong

World Electr. Veh. J. 2024, 15(7), 284; https://0-doi-org.brum.beds.ac.uk/10.3390/wevj15070284 - 26 Jun 2024

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Abstract

The implementation of e-jeepneys stands as a change process that will eventually transition to the modernization of the public transport system in the Philippines. To address concerns about jeepneys’ effects on the environment, energy use, society, the economy, and policies, their acceptability in [...] Read more.

The implementation of e-jeepneys stands as a change process that will eventually transition to the modernization of the public transport system in the Philippines. To address concerns about jeepneys’ effects on the environment, energy use, society, the economy, and policies, their acceptability in the Philippines must be considered. This research study aims to identify the sources of influence on Filipinos’ adoption of e-jeepney utilization as a mode of transportation using the extended Pro-Environmental Planned Behavior (PEBP) model. A total of 502 commuters voluntarily answered the survey questionnaire. Based on the findings, perceived environmental concern (PEC) is the most significant determinant influencing attitude (AT) and, thus, affecting the Filipinos’ behavioral intention (BI) towards the adoption of e-jeepneys. Conversely, AT was the primary determinant of BI, which strongly supported the notion of AT as a strong driving force shaping behavioral decisions. Moreover, perceived authority support (PAS) emerged as a strong predictor of subjective norms (SNs), demonstrating the influence of institutional support on societal perceptions. As a result, more environmentally conscious people are more likely to view e-jeepneys positively and intend to use them as a mode of transportation. The endorsement or support from authoritative figures or institutions notably influences subjective norms, which are individuals’ perceptions of social pressures regarding the use of e-jeepneys. Full article

13 pages, 4221 KiB

Open AccessArticle

Design, Analysis, and Comparison of Electric Vehicle Drive Motor Rotors Using Injection-Molded Carbon-Fiber-Reinforced Plastics

by Huai Cong Liu, Jang Soo Park and Il Hwan An

World Electr. Veh. J. 2024, 15(7), 283; https://0-doi-org.brum.beds.ac.uk/10.3390/wevj15070283 - 25 Jun 2024

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Abstract

Due to their excellent mechanical strength, corrosion resistance, and ease of processing, carbon fiber and carbon-fiber-reinforced plastics are finding wide application in diverse fields, including aerospace, industry, and automobiles. This research explores the feasibility of integrating carbon fiber solutions into the rotors of [...] Read more.

Due to their excellent mechanical strength, corrosion resistance, and ease of processing, carbon fiber and carbon-fiber-reinforced plastics are finding wide application in diverse fields, including aerospace, industry, and automobiles. This research explores the feasibility of integrating carbon fiber solutions into the rotors of 85-kilowatt electric vehicle interior permanent magnet synchronous motors. Two novel configurations are proposed: a carbon fiber wire-wound rotor and a carbon fiber injection-molded rotor. A finite element analysis compares the performance of these models against a basic designed rotor, considering factors like no-load back electromotive force, no-load voltage harmonics, cogging torque, load torque, torque ripple, efficiency, and manufacturing cost. Additionally, a comprehensive analysis of system efficiency and energy loss based on hypothetical electric vehicle parameters is presented. Finally, mechanical strength simulations assess the feasibility of the proposed carbon fiber composite rotor designs. Full article

(This article belongs to the Special Issue Design and Control of Electrical Machines in Electric Vehicles, 2nd Edition)

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19 pages, 1237 KiB

Open AccessArticle

Impact of Temperature Variations on Torque Capacity in Shrink-Fit Junctions of Water-Jacketed Permanent Magnet Synchronous Motors (PMSMs)

by David Sebastian Puma-Benavides, Luis Mixquititla-Casbis, Edilberto Antonio Llanes-Cedeño and Juan Carlos Jima-Matailo

World Electr. Veh. J. 2024, 15(7), 282; https://0-doi-org.brum.beds.ac.uk/10.3390/wevj15070282 - 25 Jun 2024

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Abstract

This study investigates the impact of temperature variations on the torque capacity of shrink-fit junctions in water-jacketed permanent magnet synchronous motors. Focusing on both baseline and improved designs; torque capacities were evaluated across a temperature range from −40 °C to 120 °C under [...] Read more.

This study investigates the impact of temperature variations on the torque capacity of shrink-fit junctions in water-jacketed permanent magnet synchronous motors. Focusing on both baseline and improved designs; torque capacities were evaluated across a temperature range from −40 °C to 120 °C under different material conditions: Least material condition, nominal, and maximum material condition. The baseline design exhibited torque capacities from 7648 Nm to 9032 Nm at −40 °C, decreasing significantly to 549 Nm to 1533 Nm at 120 °C. The improved design showed enhanced performance, with torque capacities ranging from 8055 Nm to 9247 Nm at −40 °C and from 842 Nm to 1618 Nm at 120 °C. The maximum improvement was observed at 120 °C for least material conditions, with a 55.4% increase, and the minimum improvement at −40 °C for maximum material conditions, with a 2.4% increase. Our findings demonstrate a significant increase in torque capacity by up to 20% under varied thermal conditions. These results underscore the effectiveness of design modifications in enhancing thermal stability and torque capacity, making the improved design a more reliable choice for high-performance applications subject to significant thermal fluctuations. This research highlights the critical role of material selection, thermal management, and precise design adjustments in optimizing the performance and reliability of permanent magnet synchronous motors. Full article

(This article belongs to the Special Issue The Energy Efficiency of Electric Vehicle Charging Stations with Minimal Grid Impact)

16 pages, 17931 KiB

Open AccessArticle

Motor Bearing Fault Diagnosis Based on Current Signal Using Time–Frequency Channel Attention

by Zhiqiang Wang, Chao Guan, Shangru Shi, Guozheng Zhang and Xin Gu

World Electr. Veh. J. 2024, 15(7), 281; https://0-doi-org.brum.beds.ac.uk/10.3390/wevj15070281 - 24 Jun 2024

Viewed by 295

Abstract

As they are the core components of the drive motor in electric vehicles, the accurate fault diagnosis of rolling bearings is the key to ensuring the safe operation of electric vehicles. At present, intelligent diagnostic methods based on current signals (CSs) are widely [...] Read more.

As they are the core components of the drive motor in electric vehicles, the accurate fault diagnosis of rolling bearings is the key to ensuring the safe operation of electric vehicles. At present, intelligent diagnostic methods based on current signals (CSs) are widely used owing to the advantages of the easy collection, low cost, and non-invasiveness of CSs. However, in practical applications, the fault characteristics of the CS are weak, resulting in diagnostic performance that fails to meet the expected standards. In this paper, a diagnosis method is proposed to address this problem and enhance the diagnosis accuracy. Firstly, CSs from two phases are processed by periodic resampling to enhance data features, which are then fused through splicing operations. Subsequently, a feature enhancement module is constructed using multi-scale feature fusion for decomposing the input. Finally, a diagnosis model is constructed by using an improved channel attention module (CAM) for enhancing the diagnosis performance. The results from experiments containing two different types of bearing datasets show that the proposed method can extract high-quality fault features and improve the diagnosis accuracy, presenting great potential in intelligent fault diagnosis and the maintenance of electric vehicles. Full article

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22 pages, 4121 KiB

Open AccessArticle

Lithium-Ion Battery SOH Estimation Method Based on Multi-Feature and CNN-BiLSTM-MHA

by Yujie Zhou, Chaolong Zhang, Xulong Zhang and Ziheng Zhou

World Electr. Veh. J. 2024, 15(7), 280; https://0-doi-org.brum.beds.ac.uk/10.3390/wevj15070280 - 24 Jun 2024

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Abstract

Electric vehicles can reduce the dependence on limited resources such as oil, which is conducive to the development of clean energy. An accurate battery state of health (SOH) is beneficial for the safety of electric vehicles. A multi-feature and Convolutional Neural Network–Bidirectional Long [...] Read more.

Electric vehicles can reduce the dependence on limited resources such as oil, which is conducive to the development of clean energy. An accurate battery state of health (SOH) is beneficial for the safety of electric vehicles. A multi-feature and Convolutional Neural Network–Bidirectional Long Short-Term Memory–Multi-head Attention (CNN-BiLSTM-MHA)-based lithium-ion battery SOH estimation method is proposed in this paper. First, the voltage, energy, and temperature data of the battery in the constant current charging phase are measured. Then, based on the voltage and energy data, the incremental energy analysis (IEA) is performed to calculate the incremental energy (IE) curve. The IE curve features including IE, peak value, average value, and standard deviation are extracted and combined with the thermal features of the battery to form a complete multi-feature sequence. A CNN-BiLSTM-MHA model is set up to map the features to the battery SOH. Experiments were conducted using batteries with different charging currents, and the results showed that even if the nonlinearity of battery SOH degradation is significant, this method can still achieve a fast and accurate estimation of the battery SOH. The Mean Absolute Error (MAE) is 0.1982%, 0.1873%, 0.1652%, and 0.1968%, and the Root-Mean-Square Error (RMSE) is 0.2921%, 0.2997%, 0.2130%, and 0.2625%, respectively. The average Coefficient of Determination (R²) is above 96%. Compared to the BiLSTM model, the training time is reduced by an average of about 36%. Full article

(This article belongs to the Special Issue Intelligent Modelling & Simulation Technology of E-Mobility)

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14 pages, 4607 KiB

Open AccessArticle

Conceptual Design of an Unmanned Electrical Amphibious Vehicle for Ocean and Land Surveillance

by Hugo Policarpo, João P. B. Lourenço, António M. Anastácio, Rui Parente, Francisco Rego, Daniel Silvestre, Frederico Afonso and Nuno M. M. Maia

World Electr. Veh. J. 2024, 15(7), 279; https://0-doi-org.brum.beds.ac.uk/10.3390/wevj15070279 - 22 Jun 2024

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Abstract

Unmanned vehicles (UVs) have become increasingly important in various scenarios of civil and military operations. The present work aims at the conceptual design of a modular Amphibious Unmanned Ground Vehicle (A-UGV) that can be easily adapted for different types of land and/or water [...] Read more.

Unmanned vehicles (UVs) have become increasingly important in various scenarios of civil and military operations. The present work aims at the conceptual design of a modular Amphibious Unmanned Ground Vehicle (A-UGV) that can be easily adapted for different types of land and/or water missions with low monetary cost (EUR < 5 k, without sensors). Basing the design on the needs highlighted in the 2021 review of the Strategic Directive of the Portuguese Navy, the necessary specifications and requirements are established for two mission scenarios. Then, a market research analysis focused on vehicles currently available and their technological advances is conducted to identify existing UV solutions and respective characteristics/capabilities of interest to the current work. To study and define the geometry of the hull and the configuration of the A-UGV itself, preliminary computational structural and fluid analyses are carried out to ensure it complies with the specifications initially established. As a result, one obtains a fully electric vehicle with approximate dimensions of 1050 × 670 × 450 mm (length–width–height), enabled with 6 × 6 traction capable of reaching 20 km/h on land, which possesses amphibious capabilities of independent propulsion in water up to 8 kts and an estimated autonomy of over 60 min. Full article

(This article belongs to the Special Issue Design Theory, Method and Control of Intelligent and Safe Vehicles)

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25 pages, 1093 KiB

Open AccessArticle

Improvement of the Cybersecurity of the Satellite Internet of Vehicles through the Application of an Authentication Protocol Based on a Modular Error-Correction Code

by Igor Anatolyevich Kalmykov, Aleksandr Anatolyevich Olenev, Natalya Vladimirovna Kononova, Tatyana Aleksandrovna Peleshenko, Daniil Vyacheslavovich Dukhovnyj, Nikita Konstantinovich Chistousov and Natalya Igorevna Kalmykova

World Electr. Veh. J. 2024, 15(7), 278; https://0-doi-org.brum.beds.ac.uk/10.3390/wevj15070278 - 21 Jun 2024

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Abstract

The integration of the Internet of Vehicles (IoV) and low-orbit satellite Internet not only increases the efficiency of traffic management but also contributes to the emergence of new cyberattacks. Spoofing interference occupies a special place among them. To prevent a rogue satellite from [...] Read more.

The integration of the Internet of Vehicles (IoV) and low-orbit satellite Internet not only increases the efficiency of traffic management but also contributes to the emergence of new cyberattacks. Spoofing interference occupies a special place among them. To prevent a rogue satellite from imposing unauthorized content on vehicle owners, a zero-knowledge authentication protocol (ZKAP) based on a modular polyalphabetic polynomial code (MPPC) was developed. The use of MPPC allowed for increasing the authentication speed of the satellite performing the role of RSU. As a result, a reduction in the time needed to guess the prover’s signal also reduces the probability of granting a rogue satellite the communication session and increases the imitation resistance of the satellite IoV. At the same time, the MPPC allows for improving the noise resistance of the ZKAP. An algorithm for calculating the control residuals for a noise-resistant MPPC was developed for this purpose, as well as an algorithm for correcting errors arising in the communication channel due to interference. Thus, the developed authentication protocol based on a noise-resistant modular code allows for simultaneously reducing the probabilities of the first-order and second-order errors, which leads to the increased cybersecurity of satellite IoV. Full article

(This article belongs to the Special Issue Recent Developments and Research in Vehicular Ad Hoc Networks (VANETs))

18 pages, 11000 KiB

Open AccessArticle

A Finite-Set Integral Sliding Modes Predictive Control for a Permanent Magnet Synchronous Motor Drive System

by Hector Hidalgo, Rodolfo Orosco, Hector Huerta, Nimrod Vazquez, Leonel Estrada, Sergio Pinto and Angel de Castro

World Electr. Veh. J. 2024, 15(7), 277; https://0-doi-org.brum.beds.ac.uk/10.3390/wevj15070277 - 21 Jun 2024

Viewed by 406

Abstract

Finite-set model predictive control (FS-MPC) is an easy and intuitive control technique. However, parametric uncertainties reduce the accuracy of the prediction. Classical MPC requires many calculations; therefore, the calculation time generates a considerable time delay in the actuation. This delay deteriorates the performance [...] Read more.

Finite-set model predictive control (FS-MPC) is an easy and intuitive control technique. However, parametric uncertainties reduce the accuracy of the prediction. Classical MPC requires many calculations; therefore, the calculation time generates a considerable time delay in the actuation. This delay deteriorates the performance of the system and generates a significant current ripple. This paper proposes a finite-set integral sliding modes predictive control (FS-ISMPC) for a permanent magnet synchronous motor (PMSM). The conventional decision function is replaced by an integral sliding cost function, which has several advantages, such as robustness to parameter uncertainties, and convergence in finite time. The proposed decision function does not require the inductance and resistance parameters of the motor. In addition, the proposal includes compensation for the calculation delay of the control vector. The proposed control strategy was compared with traditional predictive control with delay compensation using a real-time hardware-in-the-loop (HIL) simulation. The results obtained from the comparison indicated that the proposed controller has a lower THD and computational burden. Full article

(This article belongs to the Special Issue Electric Vehicle Technology Development, Energy and Environmental Implications, and Decarbonization)

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25 pages, 4849 KiB

Open AccessArticle

Providing an Intelligent Frequency Control Method in a Microgrid Network in the Presence of Electric Vehicles

by Mousa Alizadeh, Lilia Tightiz and Morteza Azimi Nasab

World Electr. Veh. J. 2024, 15(7), 276; https://0-doi-org.brum.beds.ac.uk/10.3390/wevj15070276 - 21 Jun 2024

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Abstract

Due to the reduction in fossil fuel abundance and the harmful environmental effects of burning them, the renewable resource potentials of microgrid (MG) structures have become highly highly. However, the uncertainty and variability of MGs leads to system frequency deviations in islanded or [...] Read more.

Due to the reduction in fossil fuel abundance and the harmful environmental effects of burning them, the renewable resource potentials of microgrid (MG) structures have become highly highly. However, the uncertainty and variability of MGs leads to system frequency deviations in islanded or stand-alone mode. Usually, battery energy storage systems (BESSs) reduce this frequency deviation, despite limitations such as reducing efficiency in the long term and increasing expenses. A suitable solution is to use electric vehicles (EVs) besides BESSs in systems with different energy sources in the microgrid structure. In this field, due to the fast charging and discharging of EVs and the fluctuating character of renewable energy sources, controllers based on the traditional model cannot ensure the stability of MGs. For this purpose, in this research, an ultra-local model (ULM) controller with an extended state observer (ESO) for load frequency control (LFC) of a multi-microgrid (MMG) has been systematically developed. Specifically, a compensating controller based on the single-input interval type fuzzy logic controller (FLC) was used to remove the ESO error and improve the LFC performance. Since the performance of the ULM controller based on SIT2-FLC depends on specific parameters, all of these coefficients were adjusted by an improved harmony search algorithm (IHSA). Simulation and statistical analysis results show that the proposed controller performs well in reducing the frequency fluctuations and power of the system load line and offers a higher level of resistance than conventional controllers in different MG scenarios. Full article

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World Electr. Veh. J., Volume 15, Issue 7 (July 2024) – 12 articles

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