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Volume 13
Issue 4
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World Electr. Veh. J., Volume 13, Issue 4 (April 2022) – 16 articles

Cover Story (view full-size image): Flux-adjustable permanent magnet (PM) machines have the synergies of high torque density and high efficiency in conventional PM machines and controllable air-gap field in wound-field machines. They are attractive in applications requiring wide speed operation and uncontrolled voltage mitigation capabilities. Numerous novel and new flux-adjustable PM machines have been and/or are being developed, including hybrid excited, mechanically regulated, and variable flux memory machines, which are reviewed in this paper. Their merits and demerits are compared, and potential applications and development trends are highlighted. View this paper.
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11 pages, 3058 KiB  
Article
A State-of-Charge Estimation Method Based on Multi-Algorithm Fusion
by Aihua Tang, Peng Gong, Jiajie Li, Kaiqing Zhang, Yapeng Zhou and Zhigang Zhang
World Electr. Veh. J. 2022, 13(4), 70; https://doi.org/10.3390/wevj13040070 - 18 Apr 2022
Cited by 6 | Viewed by 2357
Abstract
Lithium-ion power batteries are widely used in the electric vehicle (EV) industry due to their high working voltage, high energy density, long cycle life, low self-discharge rate, and environmental protection. A multi-algorithm fusion method is proposed in this paper to estimate the battery [...] Read more.
Lithium-ion power batteries are widely used in the electric vehicle (EV) industry due to their high working voltage, high energy density, long cycle life, low self-discharge rate, and environmental protection. A multi-algorithm fusion method is proposed in this paper to estimate the battery state of charge (SOC), establishing the Thevenin model and collecting the terminal voltage residuals when the extended Kalman filter (EKF), adaptive extended Kalman filter (AEKF), and H infinite filter (HIF) estimate the SOC separately. The residuals are fused by Bayesian probability and the weight is obtained, and then the SOC estimated value of the fusion algorithm is obtained from the weight. A comparative analysis of the estimation accuracy of a single algorithm and a fusion algorithm under two different working conditions is made. Experimental results show that the fusion algorithm is more robust in the whole process of SOC estimation, and its estimation accuracy is better than the EKF algorithm. The estimation result for the fusion algorithm under a Dynamic Stress Test (DST) is better than that under a Hybrid Pulse Power Characterization (HPPC) test. With the emergence of cloud batteries, the fusion algorithm is expected to realize real vehicle online application. Full article
(This article belongs to the Special Issue Towards Intelligent E-Mobility—Selected Papers from The 34th International Electric Vehicles Symposium and Exhibition (Nanjing, China))
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10 pages, 3140 KiB  
Article
An Obstacle Detection Algorithm Suitable for Complex Traffic Environment
by Guantai Luo, Xinwei Chen, Wenwei Lin, Jie Dai, Peidong Liang and Chentao Zhang
World Electr. Veh. J. 2022, 13(4), 69; https://doi.org/10.3390/wevj13040069 - 18 Apr 2022
Cited by 4 | Viewed by 2242
Abstract
For the task of obstacle detection in a complex traffic environment, this paper proposes a road-free space extraction and obstacle detection method based on stereo vision. The proposed method combines the advantages of the V-disparity image and the Stixel method. Firstly, the depth [...] Read more.
For the task of obstacle detection in a complex traffic environment, this paper proposes a road-free space extraction and obstacle detection method based on stereo vision. The proposed method combines the advantages of the V-disparity image and the Stixel method. Firstly, the depth information and the V-disparity image are calculated according to the disparity image. Then, the free space on the road surface is calculated through the RANSAC algorithm and dynamic programming (DP) algorithm. Furthermore, a new V-disparity image and a new U-disparity image are calculated by the disparity image after removing the road surface information. Finally, the height and width of the obstacles on the road are extracted from the new V-disparity image and U-disparity image, respectively. The detection of obstacles is realized by the height and width information of obstacles. In order to verify the method, we adopted the object detection benchmarks and road detection benchmarks of the KITTI dataset for verification. In terms of the accuracy performance indicators quality, detection rate, detection accuracy, and effectiveness, the method in this paper reaches 0.820, 0.863, 0.941, and 0.900, respectively, and the time consumption is only 5.145 milliseconds. Compared with other obstacle detection methods, the detection accuracy and real-time performance in this paper are better. The experimental results show that the method has good robustness and real-time performance for obstacle detection in a complex traffic environment. Full article
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16 pages, 2589 KiB  
Article
Research on the Influence of Liquid on Heat Dissipation and Heating Characteristics of Lithium-Ion Battery Thermal Management System
by Chuanwei Zhang, Jing Huang, Weixin Sun, Xusheng Xu and Yikun Li
World Electr. Veh. J. 2022, 13(4), 68; https://doi.org/10.3390/wevj13040068 - 15 Apr 2022
Cited by 4 | Viewed by 2088
Abstract
A battery thermal management system (BTMS) with functions of heat dissipation and heating by using only one liquid and one structure was studied, and a design for a new type of thermal management device structure was proposed. To find the influence factors of [...] Read more.
A battery thermal management system (BTMS) with functions of heat dissipation and heating by using only one liquid and one structure was studied, and a design for a new type of thermal management device structure was proposed. To find the influence factors of the BTMS on heat dissipation and heating characteristics, we selected and simulated three parameters: inlet size, liquid flow rate, and temperature. The convective heat transfer coefficient h and the Nusselt number Nu were used to analyze the influence of inlet size and liquid velocity on heat transfer intensity. The results show that: (1) In the temperature environment of 298 K with different discharge rates, a pipe diameter of 10 mm is the best size of the BTMS; (2) The increase in flow rate can increase the convective heat transfer coefficient h and the Nusselt number Nu. When the flow rate is 0.02 m/s, the growth rate of h and Nu is the largest; (3) The higher the fluid temperature, the faster the temperature of the battery pack increases in cold environments, but the uneven surface temperature of the battery is also more obvious. Full article
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16 pages, 6500 KiB  
Article
Efficient Multi-Phase Converter for E-Mobility
by Suresh Sampath, Zahira Rahiman, Sharmeela Chenniappan, Elango Sundaram, Umashankar Subramaniam and Sanjeevikumar Padmanaban
World Electr. Veh. J. 2022, 13(4), 67; https://doi.org/10.3390/wevj13040067 - 13 Apr 2022
Cited by 9 | Viewed by 2837
Abstract
The recent growth of battery-powered applications has increased the need for high-efficiency step-up dc-dc converters. The step-up conversion is commonly used in several applications, such as electric vehicle (EV); plug-in hybrid electric vehicles (PHEV); photovoltaic (PV) systems; uninterruptible power supplies (UPS); and fuel [...] Read more.
The recent growth of battery-powered applications has increased the need for high-efficiency step-up dc-dc converters. The step-up conversion is commonly used in several applications, such as electric vehicle (EV); plug-in hybrid electric vehicles (PHEV); photovoltaic (PV) systems; uninterruptible power supplies (UPS); and fuel cell systems. The input current is shared among inductors by paralleling the converters; resulting in high reliability and efficiency. In this paper; a detailed analysis for reducing power loss and improving efficiency is discussed. In continuous conduction mode; the converters are tested with a constant duty cycle of 50%. The multi phase interleaved boost converter (MPIBC) is controlled by interleaved switching techniques; which have the same switching frequency but phases are shifted. The efficiency of the six phase IBC model is 93.82% and 95.74% for an input voltage of 20 V and 200 V, respectively. The presented six phase MPIBC is validated by comparing it with the existing six phase IBC. The result shows that the presented converter is better than the existing converter. The prototype of the two phase and six phase IBC is fabricated to test the performance. It is found that the output power at the load end is highest for the 5 kHz switching frequency. Full article
(This article belongs to the Special Issue Power Converters and Electric Motor Drives)
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17 pages, 10466 KiB  
Article
On Unintentional Demagnetization Effect of Switched Flux Hybrid Magnet Memory Machine
by Jingjing Feng, Hui Yang, Yongsheng Ge and Wei Zhang
World Electr. Veh. J. 2022, 13(4), 66; https://doi.org/10.3390/wevj13040066 - 07 Apr 2022
Viewed by 2177
Abstract
This paper investigates the unintentional demagnetization (UD) characteristics of low-coercive-force (LCF) permanent magnets (PMs), in switched flux hybrid magnet memory machines (SF-HMMMs). Although the LCF PM field is magnetically in parallel to the magnetic fields produced by the NdFeB PM, as well as [...] Read more.
This paper investigates the unintentional demagnetization (UD) characteristics of low-coercive-force (LCF) permanent magnets (PMs), in switched flux hybrid magnet memory machines (SF-HMMMs). Although the LCF PM field is magnetically in parallel to the magnetic fields produced by the NdFeB PM, as well as the armature reaction in the investigated machines, the UD phenomenon of LCF PMs still possibly occurs, particularly, under on-load operation due to the magnetic saturation effect. First, the UD effect is revealed by the frozen permeability method (FPM), and analytically explained via a magnetic circuit model. Various UD types are then identified with the finite-element (FE) method, coupled with a virtual linear hysteresis curve (VLHC) of LCF PM and FPM. In addition, the dimension and grade of the LCF PM are designed with the aid of VLHC, in order to prevent the UD effect. Finally, a fabricated SF-HMMM prototype is tested to verify the theoretical analyses. Full article
(This article belongs to the Special Issue Advanced Permanent Magnet Machines and Drive Systems for Electric Vehicles)
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28 pages, 46731 KiB  
Article
A Multi-Criteria Analysis and Trends of Electric Motors for Electric Vehicles
by Hicham El Hadraoui, Mourad Zegrari, Ahmed Chebak, Oussama Laayati and Nasr Guennouni
World Electr. Veh. J. 2022, 13(4), 65; https://doi.org/10.3390/wevj13040065 - 07 Apr 2022
Cited by 30 | Viewed by 14520
Abstract
The interest in electric traction has reached a very high level in recent decades; there is no doubt that electric vehicles have become among the main means of transport and will be the first choice in the future, but to dominate the market, [...] Read more.
The interest in electric traction has reached a very high level in recent decades; there is no doubt that electric vehicles have become among the main means of transport and will be the first choice in the future, but to dominate the market, a lot of research efforts are still devoted to this purpose. Electric machines are crucial components of electric vehicle powertrains. The bulk of traction drive systems have converged in recent years toward having some sort of permanent magnet machines because there is a growing trend toward enhancing the power density and efficiency of traction machines, resulting in unique designs and refinements to fundamental machine topologies, as well as the introduction of new machine classes. This paper presents the technological aspect of the different components of the electric powertrain and highlights the important information on the electric vehicle’s architecture. It focuses on a multi-criteria comparison of different electric motors utilized in the electric traction system to give a clear vision to allow choosing the adequate electrical motor for the desired application. The proposed comparative analysis shows that the induction motor better meets the major necessities of the electric powertrain, whereas the permanent magnet synchronous motor is nonetheless the most used by electric vehicle manufacturers. Full article
(This article belongs to the Special Issue Power Converters and Electric Motor Drives)
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19 pages, 835 KiB  
Article
On the Analysis and Torque Enhancement of Flux-Switching Permanent Magnet Machines in Electric Power Steering Systems
by Anis Abdelkefi, Amal Souissi, Imen Abdennadher and Ahmed Masmoudi
World Electr. Veh. J. 2022, 13(4), 64; https://doi.org/10.3390/wevj13040064 - 04 Apr 2022
Cited by 8 | Viewed by 2054
Abstract
Modern road vehicles are more and more often being equipped with electric actuators. These are intended to play critical roles in passengers comfort and safety. Among the electrified components onboard road vehicles, one can distinguish electric power steering (EPS) systems, which have been [...] Read more.
Modern road vehicles are more and more often being equipped with electric actuators. These are intended to play critical roles in passengers comfort and safety. Among the electrified components onboard road vehicles, one can distinguish electric power steering (EPS) systems, which have been the subject of intensive investigations covering both design and control aspects. The abilities of several AC motor topologies to fulfil the EPS systems’ requirements have been assessed by a large scientific community in both academia and industry. The present work was aimed at the prediction of the electromagnetic features of the flux-switching permanent magnet machines (FSPMMs), with an emphasis on the air gap flux density. The latter was firstly formulated while neglecting the slotting effect at both sides of the air gap. Then, stator and rotor permeance functions, taking into account the slotting effect and the PM flux concentrating arrangement, were incorporated into the derived flux density spatial repartition. Moreover, the accuracy of the latter was improved through two dedicated correction functions that take into account the rotor position and the magnetic saturation. The last part of the paper presents a simple approach to enhance the developed torque of FSPMMs in an attempt to meet the EPS requirements. Full article
(This article belongs to the Special Issue Advanced Permanent Magnet Machines and Drive Systems for Electric Vehicles)
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12 pages, 4772 KiB  
Article
IPTVisual: Visualisation of the Spatial Energy Flows in Inductive Power Transfer Systems with Arbitrary Winding Shapes
by Cheng Zhang, Xiaoyun Chen, Kunyu Chen and Deyan Lin
World Electr. Veh. J. 2022, 13(4), 63; https://doi.org/10.3390/wevj13040063 - 02 Apr 2022
Cited by 2 | Viewed by 1978
Abstract
Mid-ranged wireless power transfer by induction or inductive power transfer (IPT), including the strong magnetic resonance method, has been widely adopted, in numerous applications where wires are restricted. The energy flow in space, of course, is invisible to engineers. The windings are often [...] Read more.
Mid-ranged wireless power transfer by induction or inductive power transfer (IPT), including the strong magnetic resonance method, has been widely adopted, in numerous applications where wires are restricted. The energy flow in space, of course, is invisible to engineers. The windings are often required to be irregular shapes to accommodate the industrial designs of the products, thus, a visualisation method for energy transfer paths could greatly help the design and optimization of such systems. A time-efficient methodology, including the model, analysis and plot of the three-dimensional energy flow for IPT systems, is proposed in this paper. Algorithms of fast describing arbitrarily shaped windings are proposed and the time complexities are evaluated. A software tool, IPTVisual, is developed. It takes the inputs of key coordinates of the windings, the assignments of voltage and/or current sources, any compensation capacitors and auxiliary circuits, and the required observation points to generate the 3D models of the windings and the Poynting vectors, rendered in web browsers for the most extendable compatibility. Several example scenarios have been tested and the results match with the expected operations. Full article
(This article belongs to the Special Issue Towards Intelligent E-Mobility—Selected Papers from The 34th International Electric Vehicles Symposium and Exhibition (Nanjing, China))
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8 pages, 1283 KiB  
Article
Driving Behavior and Decision Mechanisms in Emergency Conditions
by Ying Lyu, Yiteng Sun, Tianyao Zhang, Debao Kong, Zheng Lv, Yujie Liu and Zhenhai Gao
World Electr. Veh. J. 2022, 13(4), 62; https://doi.org/10.3390/wevj13040062 - 01 Apr 2022
Viewed by 1903
Abstract
In this article we used simulator experiments to explore the intelligent mechanisms of human decision-making. Three types of typical emergency scenarios were used in the experiment, in which Scenario 1 was used to analyze the driver’s choice to protect themselves or to protect [...] Read more.
In this article we used simulator experiments to explore the intelligent mechanisms of human decision-making. Three types of typical emergency scenarios were used in the experiment, in which Scenario 1 was used to analyze the driver’s choice to protect themselves or to protect pedestrians in emergency situations. Scenario 2 was compared with Scenario 1 to verify whether the driver’s avoidance behavior to protect pedestrians was instinctive or selective. Scenario 3 was to verify whether the driver would follow the principle of damage minimization. The driver’s decisions and actions in emergency situations, from the cumulative frequency of time to collision (TTC) to the maximum steering wheel angle rate during the experiments, were recorded. The results show that the driver was not just instinctively avoiding the immediate obstacle, but more selectively protecting pedestrians. At the same time, the time taken up by the driver’s instinctive avoidance response also had a negative impact on decision-making. The actual decisions of the driver were analyzed to provide a basis for building up the ethical decision-making of autonomous vehicles. Full article
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21 pages, 5224 KiB  
Article
Life-Cycle CO2-Equivalent Emissions of Cars Driven by Conventional and Electric Propulsion Systems
by Mario Hirz and Thu Trang Nguyen
World Electr. Veh. J. 2022, 13(4), 61; https://doi.org/10.3390/wevj13040061 - 31 Mar 2022
Cited by 11 | Viewed by 7754
Abstract
As an important trend in the automotive industry, electrification of propulsion systems has potential to significantly reduce greenhouse-gas emissions of the transportation sector. Whereas electric vehicles do not produce exhaust emissions during driving, the impact of electricity provision for charging batteries, as well [...] Read more.
As an important trend in the automotive industry, electrification of propulsion systems has potential to significantly reduce greenhouse-gas emissions of the transportation sector. Whereas electric vehicles do not produce exhaust emissions during driving, the impact of electricity provision for charging batteries, as well as the impact of vehicle production play an essential role in a holistic consideration of the carbon footprint. The paper introduces a comprehensive evaluation of greenhouse gas-emission-related factors of cars driven by different propulsion technologies, considering the entire product life cycle. This comprises vehicle production, including battery system, electric powertrain and other relevant components, the car’s use phase under consideration of different electricity mixes and the end-of-life phase. The results of the study give insights of influencing factors on life-cycle-related carbon-dioxide-equivalent emissions of cars driven by combustion engines, hybrid powertrains and battery-electric propulsion systems. In addition, a comparison of actual mass-production cars is made and the total life-cycle carbon footprints are discussed under different boundary conditions of electric power supply. In this way, the article comprehensively introduces an automotive life-cycle assessment and provides fundamental information, contributing to an objective discussion of different propulsion technologies. Full article
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32 pages, 10424 KiB  
Review
Flux-Adjustable Permanent Magnet Machines in Traction Applications
by Zicheng Zhou, Hao Hua and Ziqiang Zhu
World Electr. Veh. J. 2022, 13(4), 60; https://doi.org/10.3390/wevj13040060 - 29 Mar 2022
Cited by 3 | Viewed by 3152
Abstract
This paper overviews the recent advances in flux-adjustable permanent magnet (PM) machines for traction applications. The flux-adjustable PM machines benefit from the synergies of the high torque density and high efficiency in conventional PM machines as well as the controllable air-gap field in [...] Read more.
This paper overviews the recent advances in flux-adjustable permanent magnet (PM) machines for traction applications. The flux-adjustable PM machines benefit from the synergies of the high torque density and high efficiency in conventional PM machines as well as the controllable air-gap field in wound-field machines, which are attractive for the traction applications requiring enhanced capabilities of speed regulation and uncontrolled voltage mitigation. In general, three solutions have been presented, namely the hybrid excited (HE), the mechanically regulated (MR), and the variable flux memory (VFM) machines. Numerous innovations were proposed on these topics during the last two decades, while each machine topology has its own merits and demerits. The purpose of this paper is to review the development history and trend of the flux-adjustable PM machines, with particular reference to their topologies, working mechanism, and electromagnetic performance. Full article
(This article belongs to the Special Issue Advanced Permanent Magnet Machines and Drive Systems for Electric Vehicles)
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18 pages, 3657 KiB  
Article
Modification of Cycle Life Model for Normal Aging Trajectory Prediction of Lithium-Ion Batteries at Different Temperatures and Discharge Current Rates
by Xinyu Jia, Caiping Zhang, Leyi Wang, Weige Zhang and Linjing Zhang
World Electr. Veh. J. 2022, 13(4), 59; https://doi.org/10.3390/wevj13040059 - 28 Mar 2022
Cited by 2 | Viewed by 2647
Abstract
Battery life is of critical importance for the reliable and economical operation of electric vehicles (EVs). Normal aging accounts for more than 80% of the battery available cycle range. Accurate and robust battery life models of normal aging are essential for battery health [...] Read more.
Battery life is of critical importance for the reliable and economical operation of electric vehicles (EVs). Normal aging accounts for more than 80% of the battery available cycle range. Accurate and robust battery life models of normal aging are essential for battery health management systems and life evaluation before accelerated aging. Capacity recovery, test errors and accelerated aging all affect life model building during normal aging. Therefore, this paper proposes an improved life model based on wavelet transform (WT) signal processing to accurately predict the decline trend of the battery in the normal aging stage. In this paper, the capacity recovery, test noise and capacity diving in the aging trend are effectively removed by wavelet transform. We obtained an optimized life model through the analysis of the model structure and the analysis of the parameter sensitivity of the life model. The particle swarm algorithm (PSO) is employed to identify the parameters of the empirical models with the normal aging data extracted by the WT. Through verification, it is found that the modified cycle life model proposed in this paper can accurately predict the normal aging trajectory of batteries under different discharge rates and temperatures. The prediction error of the improved life model for normal aging is 1.09%. Full article
(This article belongs to the Special Issue Smart Lithium-Ion Battery Systems: Advanced Modeling, State Estimation, and Control)
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22 pages, 2443 KiB  
Article
The Capacity of Battery-Electric and Plug-in Hybrid Electric Vehicles to Mitigate CO2 Emissions: Macroeconomic Evidence from European Union Countries
by Matheus Koengkan, José Alberto Fuinhas, Mônica Teixeira, Emad Kazemzadeh, Anna Auza, Fatemeh Dehdar and Fariba Osmani
World Electr. Veh. J. 2022, 13(4), 58; https://doi.org/10.3390/wevj13040058 - 24 Mar 2022
Cited by 26 | Viewed by 4142
Abstract
The decarbonisation of the transportation sector is crucial to reducing carbon dioxide (CO2) emissions. This study analyses evidence from European countries regarding achievement of the European Commission’s goal of achieving carbon neutrality by 2050. Using panel quantile econometric techniques, the impact [...] Read more.
The decarbonisation of the transportation sector is crucial to reducing carbon dioxide (CO2) emissions. This study analyses evidence from European countries regarding achievement of the European Commission’s goal of achieving carbon neutrality by 2050. Using panel quantile econometric techniques, the impact of battery-electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) on CO2 emissions in twenty-nine European Union (EU) countries from 2010–2020 was researched. The results show that BEVs and PHEVs are capable of mitigating CO2 emissions. However, each type of technology has a different degree of impact, with BEVs being more suited to minimizing CO2 emissions than PHEVs. We also found a statistically significant impact of economic development (quantile regression results) and energy consumption in increasing the emissions of CO2 in the EU countries in model estimates for both BEVs and PHEVs. It should be noted that BEVs face challenges, such as the scarcity of minerals for the production of batteries and the increased demand for mineral batteries, which have significant environmental impacts. Therefore, policymakers should adopt environmentally efficient transport that uses clean energy, such as EVs, to reduce the harmful effects on public health and the environment caused by the indiscriminate use of fossil fuels. Full article
(This article belongs to the Special Issue Vehicle Electrification and the Environment)
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17 pages, 6584 KiB  
Article
Performance Comparison of High-Speed Motors for Electric Vehicle
by Kohei Aiso and Kan Akatsu
World Electr. Veh. J. 2022, 13(4), 57; https://doi.org/10.3390/wevj13040057 - 23 Mar 2022
Cited by 11 | Viewed by 5546
Abstract
It is predicted that the maximum speed of EV traction motors will increase in the future due to reductions in size and weight. The high-speed motors are required to have high mechanical strength of the rotor for high-speed rotation, in addition to satisfying [...] Read more.
It is predicted that the maximum speed of EV traction motors will increase in the future due to reductions in size and weight. The high-speed motors are required to have high mechanical strength of the rotor for high-speed rotation, in addition to satisfying the required output and high efficiency in the wide operation area. Therefore, it is necessary to evaluate the advantages and disadvantages of motors in terms of both electrical and mechanical points of view. In this research, three motor types, PMSM, SRM, and IM, which targeted the output power of 85 kW and the maximum speed of 52,000 min−1, are designed for use with EV traction motors, and the study clarifies which the type of motor is most suitable for application in high-speed motors of EVs in terms of their mechanical and electrical characteristics. Full article
(This article belongs to the Special Issue Advanced Permanent Magnet Machines and Drive Systems for Electric Vehicles)
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29 pages, 8655 KiB  
Article
Placing BEV Charging Infrastructure: Influencing Factors, Metrics, and Their Influence on Observed Charger Utilization
by Lennart Adenaw and Sebastian Krapf
World Electr. Veh. J. 2022, 13(4), 56; https://doi.org/10.3390/wevj13040056 - 22 Mar 2022
Cited by 6 | Viewed by 3730
Abstract
The automotive sector’s transition to Battery Electric Vehicles (BEVs) requires extensive deployment of additional charging infrastructure. To determine optimal new locations, planners consider and rate a multitude of factors that influence the charging demand at candidate sites. Researchers have proposed a variety of [...] Read more.
The automotive sector’s transition to Battery Electric Vehicles (BEVs) requires extensive deployment of additional charging infrastructure. To determine optimal new locations, planners consider and rate a multitude of factors that influence the charging demand at candidate sites. Researchers have proposed a variety of placement criteria and methods to automate site selection. However, no common set of criteria has emerged. In addition, due to the lack of usage data, the applicability of existing criteria remains unclear. Therefore, the goals of this article are to extract the most relevant factors from literature and to evaluate their ability to characterize charging point usage. First, we review the literature base to collect, analyze, and cluster existing influencing factors and to analyze how they affect charging demand. Second, we conduct a case study using real-life charging station data from Hamburg, Germany. Based on the extracted influencing factors, we identify four clusters within Hamburg’s public charging infrastructure. While the mean performance indicators duration, daily transactions, and connection ratio hardly differ among these clusters, the temporal occupancy curves clearly show distinct charging behavior for each cluster. This work contributes to the state of the art by structuring the diverse landscape of charging station location placement criteria, by deriving a set of measurable influencing factors, and by analyzing their effect on a location’s charging demand, yielding an open source data set of charging point usage. Full article
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15 pages, 2974 KiB  
Article
Adaptive Pre-Aim Control of Driverless Vehicle Path Tracking Based on a SSA-BP Neural Network
by Yinggang Huang, Wenguang Luo and Hongli Lan
World Electr. Veh. J. 2022, 13(4), 55; https://doi.org/10.3390/wevj13040055 - 22 Mar 2022
Cited by 9 | Viewed by 2022
Abstract
Aiming at the problem that the tracking accuracy of unmanned vehicle path tracking preview control is greatly affected by the preview time, a BP neural network adaptive preview control method is proposed. Considering that the prediction effect of the BP neural network is [...] Read more.
Aiming at the problem that the tracking accuracy of unmanned vehicle path tracking preview control is greatly affected by the preview time, a BP neural network adaptive preview control method is proposed. Considering that the prediction effect of the BP neural network is limited to the initial value setting, a preview time adjuster based on the SSA-BP neural network was established; by establishing the relationship between the front wheel steering angle and the preview time, a new direction control driver model was formed. The driver model and the preview time adjuster together constitute an adaptive steering controller. In order to solve the influence of the longitudinal speed change on the vehicle stability, a PID variable-speed controller was designed to realize the horizontal and vertical coordinated control of the path tracking of the unmanned vehicle. Compared with the fixed preview time and the BP preview time control method, the results show that the proposed method has strong tracking ability when driving at various speeds on three consecutive curves and Alt 3 test roads, and can be used when driving at a variable speed. Full article
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