World Electric Vehicle Journal

16 pages, 2601 KiB

Open AccessArticle

Multi-Objective Optimization and Test of a Tractor Drive Motor

by Mengnan Liu, Yanying Li, Sixia Zhao, Bing Han, Shenghui Lei and Liyou Xu

World Electr. Veh. J. 2022, 13(2), 43; https://doi.org/10.3390/wevj13020043 - 19 Feb 2022

Cited by 5 | Viewed by 2561

The design objectives of the structural parameters of the tractor drive motor are diverse, and the constraints are complex. It is difficult to optimize the overall performance of the unit by using the empirical method and single-objective optimization method. This paper proposes a [...] Read more.

The design objectives of the structural parameters of the tractor drive motor are diverse, and the constraints are complex. It is difficult to optimize the overall performance of the unit by using the empirical method and single-objective optimization method. This paper proposes a multi-objective optimization method for tractor drive motors based on an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II). Constraints are formulated according to the inherent characteristics of the motor itself and the characteristics of the tractor’s working conditions. The objective function was established with the heat loss of the drive motor and the total efficiency of the drive system. Based on the designed solution process of NSGA-II algorithm, an example optimization was carried out, and the tractor electromechanical drive system was carried out with the single-objective optimization results of the optimal energy use efficiency of the drive motor and the optimal mechanical transmission efficiency of the transmission system as the control group. The test results show that compared with the control group, the proposed multi-objective optimization method can make the overall tractor system efficiency the highest, and the maximum and rated values of the total efficiency

η_{q}

of the drive system of the multi-objective optimization design scheme. Compared with the optimal design scheme with

η_{me}

as a single objective, it was increased by 2% and 1.4%, respectively, and compared with the optimal design scheme with

η_{tr}

as a single objective, it is improved by 26.5% and 73.6%, respectively. It can provide an effective calculation method for the motor design problem in the subsequent development of the tractor electromechanical drive system. Full article

(This article belongs to the Special Issue Design, Analysis and Optimization of Electrical Machines and Drives for Electric Vehicles)

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23 pages, 9661 KiB

Open AccessEditor’s ChoiceArticle

Influence of Adhesive Tapes as Thermal Interface Materials on the Thermal Load of a Compact Electrical Machine

by Henrik-Christian Graichen, Jörg Sauerhering, Olena Stamann, Frank Beyrau and Gunar Boye

World Electr. Veh. J. 2022, 13(2), 42; https://doi.org/10.3390/wevj13020042 - 19 Feb 2022

Cited by 5 | Viewed by 2963

Abstract

In this article, a novel form of thermal interface material (TIM), represented by three industrially manufactured pressure-sensitive adhesive (PSA) tapes with electrical insulating properties, is characterized regarding its applicability in an electric motor with air-gap winding. Firstly, the adhesion performances, in terms of [...] Read more.

In this article, a novel form of thermal interface material (TIM), represented by three industrially manufactured pressure-sensitive adhesive (PSA) tapes with electrical insulating properties, is characterized regarding its applicability in an electric motor with air-gap winding. Firstly, the adhesion performances, in terms of the winding process, were investigated experimentally. Here, every TIM shows sufficient shear strength for the wire–TIM joints, as well as peel adhesion to the laminated iron core. Secondly, the thermal–physical properties of the TIMs are inspected experimentally via laser flash analysis (LFA) and differential scanning calorimetry (DSC). For every TIM, the value of the thermal resistance can double if the relatively smooth surface (R_a = 0.2 μm) of the adjacent layers is interchanged with a rougher one (R_a = 2.0–3.7 μm). Additionally, the TIM’s performance at the system level is examined. Therefore, a flat test section, according to the specifications of the original motor, is studied experimentally and numerically utilizing infrared (IR) thermography and the finite element method (FEM). The focus is set on the heat flow and temperature distribution in the test section under varying thermal loads, mass flow, and variety of TIMs. Full article

(This article belongs to the Special Issue Advanced Permanent Magnet Machines and Drive Systems for Electric Vehicles)

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21 pages, 23062 KiB

Open AccessArticle

Numerical Analysis of Meshing of Loaded Misaligned Straight Bevel Gear Drives of Automobile Differential

by Qianjin Chen, Shuiming Wang, Pengfei Li, Xinguang Li, Jianhua Liu, Dewu Hu, Zhigang Zhao and Xiaoshuang Xiong

World Electr. Veh. J. 2022, 13(2), 41; https://doi.org/10.3390/wevj13020041 - 17 Feb 2022

Viewed by 2388

Abstract

The main purpose of this paper is to analyze the influence of different types of alignment errors on the meshing performance of loaded straight bevel gears. Based on 3D finite element models of the specific loaded assembling straight bevel gear pair, the contact [...] Read more.

The main purpose of this paper is to analyze the influence of different types of alignment errors on the meshing performance of loaded straight bevel gears. Based on 3D finite element models of the specific loaded assembling straight bevel gear pair, the contact area, transmission error, vibration and noise for the specific loaded straight bevel gear are investigated. The results show that the alignment errors have different degrees of adverse effects on the contact area and the contact line of the straight bevel gear pair, which can affect the transmission error, vibration, and noise of the straight bevel gear drives. The results also demonstrate that the most dangerous type of combined alignment errors is ΔP, ΔG, ΔE < 0 and Δγ. The results of this research can provide theoretical guidelines for the assembly and modification of straight bevel gears. Full article

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24 pages, 2990 KiB

Open AccessArticle

Collaborative Optimization of the Battery Capacity and Sailing Speed Considering Multiple Operation Factors for a Battery-Powered Ship

by Yan Zhang, Lin Sun, Fan Ma, You Wu, Wentao Jiang and Lijun Fu

World Electr. Veh. J. 2022, 13(2), 40; https://doi.org/10.3390/wevj13020040 - 16 Feb 2022

Cited by 7 | Viewed by 2957

Abstract

In the context of harsh emission control and ecological environment protection, the shipping industry is transforming and upgrading towards greening, decarburization, and electrification. Battery-powered all-electric inland ships have been attracting increasingly attention. However, its initial investment cost is much more expensive than a [...] Read more.

In the context of harsh emission control and ecological environment protection, the shipping industry is transforming and upgrading towards greening, decarburization, and electrification. Battery-powered all-electric inland ships have been attracting increasingly attention. However, its initial investment cost is much more expensive than a traditional diesel-driven mechanical ship because lithium-ion batteries are currently expensive. Hence, a suitable battery size and efficient energy management strategy for ship sailing are very important for a battery-powered ship. In this paper, a novel joint optimization method of the sailing speed and battery capacity, which considers the interaction between battery size and sailing speed as well as multiple operation factors, such as freight demand and battery life, and port electricity price, is proposed to fully exploit the battery-powered ships’ application potential. Moreover, a joint optimization model of the sailing speed and battery energy consumption model considers the battery-powered ship’s characteristics and waterway characteristics. Next, a solution algorithm for the proposed joint optimization model is established to achieve joint decision-making regarding the sailing speed and battery size. Finally, case studies are conducted to demonstrate the flexibility and effectiveness of the proposed method. The results show that the proposed method can obtain the optimal sailing speed and the corresponding battery capacity synchronously when the actual transportation scenario is fixed. Moreover, the battery initial investment cost can be effectively reduced with the prosed method. Full article

(This article belongs to the Special Issue Electric Vehicles Integration in Smart Grids)

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16 pages, 4974 KiB

Open AccessArticle

Development of Electrothermal Models for Electrical Traction

by Wasma Hanini, Sami Mahfoudhi and Moez Ayadi

World Electr. Veh. J. 2022, 13(2), 39; https://doi.org/10.3390/wevj13020039 - 15 Feb 2022

Cited by 1 | Viewed by 1887

Abstract

In this paper, improved electrothermal models of the power diode and IGBT have been developed. The main local physical effects have been considered. The proposed models are able to deal with electrical and thermal effects. The models were confirmed by comparison with other [...] Read more.

In this paper, improved electrothermal models of the power diode and IGBT have been developed. The main local physical effects have been considered. The proposed models are able to deal with electrical and thermal effects. The models were confirmed by comparison with other models having similar characteristics for different circuits and different temperatures. The developed models are implemented in a traction unit to study the electrothermal performance in an electric vehicle system. The models were implemented in the Pspice circuit simulation platform using standard Pspice components and analog behavior modeling (ABM) blocks. The switching performance of the diode and the IGBT have been studied under the influence of different circuit elements in order to study and estimate the on-state and switching losses pre-required for the design of various topologies of converters and inverters. The comparison shows that these models are simple, configurable with the electrical circuit simulator software. They are better able to predict the main circuit parameters needed for power electronics design. Transient thermal responses have been demonstrated for single pulse and repetition modes. The obtained results show that our model is suitable for a fully electrothermal use of power electronic circuit simulations. Full article

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19 pages, 29745 KiB

Open AccessArticle

Analysis and Research on Power Supply Strategies of Electric Vehicles Based on Wind Farms

by Yunjia Liu

World Electr. Veh. J. 2022, 13(2), 38; https://doi.org/10.3390/wevj13020038 - 15 Feb 2022

Viewed by 2333

Abstract

The widespread growth of electric vehicles could pose significant grid and charging infrastructure challenges, especially in areas with underdeveloped infrastructure. This has affected the ease of charging electric vehicles. In this paper, I design a power supply strategy for electric vehicle charging facilities [...] Read more.

The widespread growth of electric vehicles could pose significant grid and charging infrastructure challenges, especially in areas with underdeveloped infrastructure. This has affected the ease of charging electric vehicles. In this paper, I design a power supply strategy for electric vehicle charging facilities based on wind farm power supply. In this strategy, a preliminary selection of line conductors is carried out, and several schemes are preliminarily determined. Further comparative analysis is made from the three aspects of conductor, tower type, and bus. Through the PowerWorld software, a simulation model is established for each scheme, and an optimal strategy that takes into account economy, security, and system stability is obtained (AAC 31.5 mm double split, tower A and bus 5). This can assist in the transformation of electric vehicle power supply and the construction of wind farm power supply facilities. Full article

(This article belongs to the Special Issue Electric Vehicle Smart Charging and V2G)

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24 pages, 4599 KiB

Open AccessReview

A Bibliometric Survey of Research Output on Wireless Charging for Electric Vehicles

by Emmanuel Gbey, Richard Fiifi Turkson and Sohui Lee

World Electr. Veh. J. 2022, 13(2), 37; https://doi.org/10.3390/wevj13020037 - 13 Feb 2022

Cited by 7 | Viewed by 4418

Abstract

Wireless charging modules for electric vehicles are being increasingly studied. Previous research has focused on developing more effective wireless-charging modules for electric vehicles in order to pave the way for a more sustainable urban transportation. The objectives of the study were to identify [...] Read more.

Wireless charging modules for electric vehicles are being increasingly studied. Previous research has focused on developing more effective wireless-charging modules for electric vehicles in order to pave the way for a more sustainable urban transportation. The objectives of the study were to identify the social structure of the field by mapping of research collaborations among authors and countries, measure the influence of authors and sources, identify the interactions between different researchers and the most influential authors, sources, documents and organizations. To achieve these objectives, a bibliometric search in the SCOPUS database was conducted using a combination of keywords and Boolean operators. The initial keyword search returned 2163 documents. The documents retrieved were manually filtered for further analysis. A scientometric analysis was carried out on the remaining 1367 documents using co-authorship, co-citation, and citation analyses for a number of measurement units. The results showed that “object detection” and “shielding effectiveness” were the most current research topics. Authors who were widely cited did not generally produce a large number of papers or collaborate with other authors. Authors from China, the United States, and the United Kingdom have all co-authored published works on the topic, indicating that they have all contributed considerably to the field’s achievements. This strongly highlighted the amount of funding localized in developed countries towards such technologies. The number of international co-authored studies conducted was low. This is most significant with no research conducted in this field in the less developed world. The most cited and influential scholars were G. A. Covic, J. T. Boys, and C. C. Mi. The most influential sources were IEEE Trans. on Power Electronics and IEEE Trans. on Induction Electronics, while the most productive sources were Energies and IEEE Access. The most influential documents were those by Covic G.A. (2013a) and Covic G.A. (2013b). Finally, emerging trends in charging and energy storage in electric vehicles were also discussed. Full article

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21 pages, 5913 KiB

Open AccessArticle

The Impact of Battery-Electric Vehicles on Energy Consumption: A Macroeconomic Evidence from 29 European Countries

by Matheus Koengkan, José Alberto Fuinhas, Matheus Belucio, Nooshin Karimi Alavijeh, Nasrin Salehnia, Daniel Machado, Vinícius Silva and Fatemeh Dehdar

World Electr. Veh. J. 2022, 13(2), 36; https://doi.org/10.3390/wevj13020036 - 09 Feb 2022

Cited by 23 | Viewed by 10182

Abstract

The impact of battery electric vehicles (BEV) on energy consumption was researched modeling energy consumption against BEVs, Gross Domestic Product (GDP) and e-commerce, using annual data from 2010 to 2020, for twenty-nine European countries, with quantile regression and OLS with fixed effects econometric [...] Read more.

The impact of battery electric vehicles (BEV) on energy consumption was researched modeling energy consumption against BEVs, Gross Domestic Product (GDP) and e-commerce, using annual data from 2010 to 2020, for twenty-nine European countries, with quantile regression and OLS with fixed effects econometric techniques. It was found that GDP and e-commerce impact energy consumption positively, and BEVs reduce energy consumption. These findings support that efficiency gains could not reduce energy consumption, and e-commerce, via extra packaging, further usage of computer processors, and cryptocurrencies to purchase products are hampering the environment. BEVs were revealed to be more energy-efficient than conventional cars. Thus, energy conservation policies to combat global warming and climate change arise. First, policies should offer an alternative packaging system to lower the negative environmental impacts of additional packaging for online purchases, stimulate smaller packages, free up additional space on the transport, enhance the delivery system efficiency, and promote alternative delivery systems. Second, offering subsidies for purchasing BEVs or tax rebates will increase the adoption rate of electric vehicles and combine this policy with the CO₂ emissions’ regulations to stimulate the demand for BEVs. Finally, affordable charging points should be provided and customer awareness of the benefits of BEVs should be improved. Full article

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13 pages, 4424 KiB

Open AccessArticle

Virtual Flux Voltage-Oriented Vector Control Method of Wide Frequency Active Rectifiers Based on Dual Low-Pass Filter

by Kai Bi, Yamei Xu, Pin Zeng, Wei Chen and Xinmin Li

World Electr. Veh. J. 2022, 13(2), 35; https://doi.org/10.3390/wevj13020035 - 07 Feb 2022

Cited by 4 | Viewed by 2270

Abstract

This article presents a non-AC-side voltage sensor control method applied to More Electric Aircraft rectifiers. The control strategy can operate properly over a wide range of frequencies. This strategy calculates the AC supply frequency through an instantaneous phase-locked loop and feeds it back [...] Read more.

This article presents a non-AC-side voltage sensor control method applied to More Electric Aircraft rectifiers. The control strategy can operate properly over a wide range of frequencies. This strategy calculates the AC supply frequency through an instantaneous phase-locked loop and feeds it back to a dual low-pass filter. The reconstructed rectifier-side voltage is filtered using two low-pass filters with different scale factors. Then, the values of the two filter outputs are subtracted and the effect of the DC bias due to the initial value of the integration is eliminated. The subtracted value is amplitude-phase compensated to calculate the virtual flux value. The phase angle can then be calculated from the virtual flux value. This phase angle is used for the implementation of the voltage-oriented vector control and as an input to the instantaneous phase-locked loop. Simulation and experimental results show that the use of dual low-pass filters under different frequency conditions improves the speed and accuracy of virtual flux estimation and eliminates DC-side bias errors. Full article

(This article belongs to the Special Issue Power Converters and Electric Motor Drives)

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18 pages, 4181 KiB

Open AccessArticle

A Distributed and Hierarchical Optimal Control Method for Intelligent Connected Vehicles in Multi-Intersection Road Networks

by Jie Yu, Fachao Jiang, Weiwei Kong and Yugong Luo

World Electr. Veh. J. 2022, 13(2), 34; https://doi.org/10.3390/wevj13020034 - 04 Feb 2022

Cited by 4 | Viewed by 2325

Abstract

Intelligent connected vehicles (ICVs) technologies will bring significant changes to future transportation, and urban intersections will be an important scenario for the application of ICVs. There exists one significant challenge to address for the control of ICVs in unsignalized, multi-intersection road networks, that [...] Read more.

Intelligent connected vehicles (ICVs) technologies will bring significant changes to future transportation, and urban intersections will be an important scenario for the application of ICVs. There exists one significant challenge to address for the control of ICVs in unsignalized, multi-intersection road networks, that is, how to realize the comprehensive optimization of traffic efficiency and energy saving. To solve this problem, the distributed and hierarchical optimal control architecture is first established in this paper, consisting of a cloud decision layer and a vehicle control layer. For the cloud decision layer, the distributed model predictive control (DMPC) method is utilized for distributed optimization control of multi-intersection road network systems, to achieve optimization in terms of traffic efficiency. For the vehicle control layer, based on the reference speed optimized from the cloud decision layer, the DMPC method is further utilized for distributed optimal control of each vehicle platoon, to achieve optimization in terms of energy saving. Finally, the comparative simulation tests are carried out based on MATLAB and SUMO. The feasibility and effectiveness of the proposed method were verified, and the improvement of traffic efficiency and energy saving was achieved. Full article

(This article belongs to the Special Issue Emerging Technologies in Electrification of Urban Mobility)

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21 pages, 4860 KiB

Open AccessArticle

Adaptive Model Predictive Control Including Battery Thermal Limitations for Fuel Consumption Reduction in P2 Hybrid Electric Vehicles

by Ethelbert Ezemobi, Gulnora Yakhshilikova, Sanjarbek Ruzimov, Luis Miguel Castellanos and Andrea Tonoli

World Electr. Veh. J. 2022, 13(2), 33; https://doi.org/10.3390/wevj13020033 - 01 Feb 2022

Cited by 4 | Viewed by 2795

Abstract

The primary objective of a hybrid electric vehicle (HEV) is to optimize the energy consumption of the automotive powertrain. This optimization has to be applied while respecting the operating conditions of the battery. Otherwise, there is a risk of compromising the battery life [...] Read more.

The primary objective of a hybrid electric vehicle (HEV) is to optimize the energy consumption of the automotive powertrain. This optimization has to be applied while respecting the operating conditions of the battery. Otherwise, there is a risk of compromising the battery life and thermal runaway that may result from excessive power transfer across the battery. Such considerations are critical if factoring in the low battery capacity and the passive battery cooling technology that is commonly associated with HEVs. The literature has proposed many solutions to HEV energy optimization. However, only a few of the solutions have addressed this optimization in the presence of thermal constraints. In this paper, a strategy for energy optimization in the presence of thermal constraints is developed for P2 HEVs based on battery sizing and the application of model predictive control (MPC) strategy. To analyse this approach, an electro-thermal battery pack model is integrated with an off-axis P2 HEV powertrain. The battery pack is properly sized to prevent thermal runaway while improving the energy consumption. The power splitting, thermal enhancement and energy optimization of the complex and nonlinear system are handled in this work with an adaptive MPC operated within a moving finite prediction horizon. The simulation results of the HEV SUV demonstrate that, by applying thermal constraints, energy consumption for a 0.9 kWh battery capacity can be reduced by 11.3% relative to the conventional vehicle. This corresponds to about a 1.5% energy increase when there is no thermal constraint. However, by increasing the battery capacity to 1.5 kWh (14s10p), it is possible to reduce the energy consumption by 15.7%. Additional benefits associated with the predictive capability of MPC are reported in terms of energy minimization and thermal improvement. Full article

(This article belongs to the Special Issue Fuel Consumption and Emissions from Vehicles)

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12 pages, 1868 KiB

Open AccessArticle

LiDAR-IMU-UWB-Based Collaborative Localization

by Chuanwei Zhang, Xiaowen Ma and Peilin Qin

World Electr. Veh. J. 2022, 13(2), 32; https://doi.org/10.3390/wevj13020032 - 01 Feb 2022

Cited by 5 | Viewed by 2492

Abstract

This article introduced a positioning system composed of different sensors, such as LiDAR, IMU, and ultra-wideband (UWB), for the positioning method in autonomous driving technology under closed coal mine tunnels. First, we processed the LiDAR data, extracted its feature points and merged the [...] Read more.

This article introduced a positioning system composed of different sensors, such as LiDAR, IMU, and ultra-wideband (UWB), for the positioning method in autonomous driving technology under closed coal mine tunnels. First, we processed the LiDAR data, extracted its feature points and merged the extracted feature point clouds to generate a skewed combined feature point cloud. Then, we used the skew combined feature point clouds for feature matching, performed pre-integration processing on the IMU sensor data, and completed the LiDAR-IMU odometer with the LiDAR. Finally, we added UWB data to IMU pose node as a one-dimensional over-edge constraint. By updating the sliding window, the positioning accuracy was further improved. Moreover, we have conducted experiments to verify the proposed positioning system in a simulated roadway. The experimental results showed that the method proposed in this paper is superior to the single LiDAR method and the single UWB method in terms of positioning accuracy. Full article

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20 pages, 23357 KiB

Open AccessEditor’s ChoiceArticle

High Gain Converter with Improved Radial Basis Function Network for Fuel Cell Integrated Electric Vehicles

by Balasubramanian Girirajan, Himanshu Shekhar, Wen-Cheng Lai, Hariraj Kumar Jagannathan and Parameshachari Bidare Divakarachar

World Electr. Veh. J. 2022, 13(2), 31; https://doi.org/10.3390/wevj13020031 - 31 Jan 2022

Cited by 6 | Viewed by 2705

Abstract

In a recent trend, electric vehicles (EV) have been facing various power quality issues, so fuel cells (FC) are considered the best choice for integrating EV technology to enhance performance. A fuel cell electric vehicle (FCEV) is a type of EV that uses [...] Read more.

In a recent trend, electric vehicles (EV) have been facing various power quality issues, so fuel cells (FC) are considered the best choice for integrating EV technology to enhance performance. A fuel cell electric vehicle (FCEV) is a type of EV that uses a fuel cell combined with a small battery or super-capacitor to power its on-board electric motor. However, the power obtained from the FC system is much less and is not enough to drive the EV. So, another energy source is required to deliver the demanded power, which should contain high voltage gain with high conversion efficiency. The traditional converter produces a high output voltage at a high duty cycle, which generates various problems, such as reverse recovery issues, voltage spikes, and less lifespan. High switching frequency and voltage gain are essential for the propulsion of FC-based EV. Therefore, this paper presents an improved radial basis function (RBF)-based high-gain converter (HGC) to enhance the voltage gain and conversion efficiency of the entire system. The RBF neural model was constructed using the fast recursive algorithm (FRA) strategy to prune redundant hidden-layer neurons. The improved RBF technique reduces the input current ripple and voltage stress on the power semiconductor devices to increase the conversion ratio of the HGC without changing the duty cycle value. In the end, the improved RBF with HGC achieved an efficiency of 98.272%, vehicle speed of 91 km/h, and total harmonic distortion (THD) of 3.12%, which was simulated using MATLAB, and its waveforms for steady-state operation were analyzed and compared with existing methods. Full article

(This article belongs to the Special Issue Artificial Intelligence Applied to Edge Computing of Electric Vehicle Applications)

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16 pages, 3539 KiB

Open AccessArticle

Optimal Design of a Short Primary Double-Sided Linear Induction Motor for Urban Rail Transit

by Hanming Wang, Jinghong Zhao, Yiyong Xiong, Hao Xu and Sinian Yan

World Electr. Veh. J. 2022, 13(2), 30; https://doi.org/10.3390/wevj13020030 - 31 Jan 2022

Viewed by 2407

Abstract

Linear induction motors (LIMs) have been widely used in rail transit. However, Due to the breaking of the primary core and the large air gap, the efficiency and power factor of LIMs are seriously damaged, causing a large amount of energy waste. To [...] Read more.

Linear induction motors (LIMs) have been widely used in rail transit. However, Due to the breaking of the primary core and the large air gap, the efficiency and power factor of LIMs are seriously damaged, causing a large amount of energy waste. To improve the efficiency and power factor of LIMs for urban rail transit, we present a new optimization method for the design of a short primary double-sided linear induction motor (SP-DLIM) with a rated speed of 45 km/h and small thrust. The method is based on a steady state equivalent circuit model and the differential evolutionary algorithm (DEA). Moreover, the design constraints and the objective functions are proposed for the optimization problem. Finally, the optimized SP-DLIM is simulated by 2D transient finite element method (FEM). The 2-D transient FEM results verify the accuracy of the optimization method proposed in this paper. Full article

(This article belongs to the Special Issue Electric Vehicles Integration in Smart Grids)

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24 pages, 8237 KiB

Open AccessArticle

Configuration of Electric Vehicles for Specific Applications from a Holistic Perspective

by José I. Huertas, Antonio E. Mogro and Juan P. Jiménez

World Electr. Veh. J. 2022, 13(2), 29; https://doi.org/10.3390/wevj13020029 - 28 Jan 2022

Cited by 3 | Viewed by 5105

Abstract

Electrification of heavy-duty vehicles (HDVs) used for passengers and goods transportation is a key strategy to reduce the high levels of air pollution in large urban centers. However, the high investment cost of the commercially available electrified HDVs has limited their adoption. We [...] Read more.

Electrification of heavy-duty vehicles (HDVs) used for passengers and goods transportation is a key strategy to reduce the high levels of air pollution in large urban centers. However, the high investment cost of the commercially available electrified HDVs has limited their adoption. We hypothesized that there are applications where the operation with tailored electrified HDVs results in a lower total cost of ownership and lower well-to-wheel emissions of air pollutants, with higher acceleration capacity and energy efficiency than the fossil-fueled counterparts. The road transportation services running on fixed routes with short span distances (<50 km), such as the last mile cargo distribution and the passenger shuttle services, is a clear example with a high possibility of cost reduction through tailored electric HDVs. In this work, we present a methodology to define the most appropriate configuration of the powertrain of an electric vehicle for any given application. As a case study, this work aimed to define an electric powertrain configuration tailored for a university shuttle service application. A multi-objective weighted-sum optimization was performed to define the best geometrical gearbox ratios, energy management strategy, size of the motor, and batteries required. Based on three different driving profiles and five battery technologies, the results showed that, based on a 50 km autonomy, the obtained powertrain configuration satisfies the current vehicle operation with a reduced cost in every driving profile and battery technology compared. Furthermore, by using lithium-based batteries, the vehicle’s acceleration capacity is improved by 33% while reducing energy consumption by 37%, CO₂ emissions by 31%, and the total cost of ownership by 29% when compared to the current diesel-fueled buses. Full article

(This article belongs to the Special Issue Fuel Consumption and Emissions from Vehicles)

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4 pages, 175 KiB

Open AccessEditorial

Acknowledgment to Reviewers of World Electric Vehicle Journal in 2021

by World Electric Vehicle Journal Editorial Office

World Electr. Veh. J. 2022, 13(2), 28; https://doi.org/10.3390/wevj13020028 - 27 Jan 2022

Cited by 1 | Viewed by 1733

Abstract

Rigorous peer-reviews are the basis of high-quality academic publishing [...] Full article

17 pages, 4462 KiB

Open AccessArticle

Development of a Flywheel Hybrid Power System in Vehicles without the Electric Drive Device Rated Capacity Limit

by Hong Li, Jiangwei Chu and Shufa Sun

World Electr. Veh. J. 2022, 13(2), 27; https://doi.org/10.3390/wevj13020027 - 21 Jan 2022

Cited by 3 | Viewed by 3285

Abstract

At present, most studies are focused on converting the vehicle kinetic energy into electrochemical energy for battery storage. During each deceleration period, the kinetic energy is first converted into electromagnetic energy and then stored in the chemical form before being released as the [...] Read more.

At present, most studies are focused on converting the vehicle kinetic energy into electrochemical energy for battery storage. During each deceleration period, the kinetic energy is first converted into electromagnetic energy and then stored in the chemical form before being released as the kinetic energy in next acceleration period, which leads to a low transmission efficiency. Secondly, the efficiency of the kinetic energy recovery is limited by the rated capacity of electric drive devices. Thirdly, a single-axis front-drive electric powertrain can only recover the kinetic energy of front wheels. The system proposed in this paper, which included a flywheel, an electromagnetic coupler, and two gear pairs, was arranged in the rear axis. This new configuration could recycle the kinetic energy of the rear wheels for front-driving vehicles. Most of the energy between the wheels and the flywheel was transmitted in the form of mechanical energy, and the power transmitted by the mechanical port of the electromagnetic coupler was not limited by its rated power. Moreover, the battery only needs to recover the slip power of the coupler. Finally, a test bench based on the proposed system was designed and built under deceleration and cruising conditions. The experimental results also proved the functionality of the proposed system. Full article

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15 pages, 1542 KiB

Open AccessArticle

A Study to Investigate What Tempts Consumers to Adopt Electric Vehicles

by Imran Ali and Mohammad Naushad

World Electr. Veh. J. 2022, 13(2), 26; https://doi.org/10.3390/wevj13020026 - 20 Jan 2022

Cited by 19 | Viewed by 7927

Abstract

Pollution has become a major source of concern for the majority of people at present. Pollution is primarily caused by automobiles. Everybody wants to live in a pollution-free society. Nevertheless, India’s automobile registrations are growing at a rapid pace. Increased automobile usage will [...] Read more.

Pollution has become a major source of concern for the majority of people at present. Pollution is primarily caused by automobiles. Everybody wants to live in a pollution-free society. Nevertheless, India’s automobile registrations are growing at a rapid pace. Increased automobile usage will have a negative effect on the environment. As a result, our modes of transportation must be sustainable and environmentally friendly. The solution to this dilemma is electric vehicles. However, electric vehicle adoption is not occurring at a rate that is desirable in India, although it is anticipated to grow in the coming years. Numerous automobile manufacturers are ramping up production of electric automobiles. The purpose of this study is to ascertain the primary factors that influence the adoption of electric vehicles. This study includes five independent variables: financial incentives, charging infrastructure, social reinforcement, environmental concern, and price, and one dependent variable, electrical vehicle adoption. The data for the present study was collected from 366 randomly selected respondents across India. Structural Equation Modeling (SEM) and Confirmatory Factor Analysis (CFA) were used to analyze the data. The study’s findings demonstrate that pricing has a substantial impact on the adoption of electric vehicles. Full article

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17 pages, 2639 KiB

Open AccessArticle

Prediction for the Remaining Useful Life of Lithium–Ion Battery Based on RVM-GM with Dynamic Size of Moving Window

by Jinrui Nan, Bo Deng, Wanke Cao and Zihao Tan

World Electr. Veh. J. 2022, 13(2), 25; https://doi.org/10.3390/wevj13020025 - 19 Jan 2022

Cited by 6 | Viewed by 2166

Abstract

Accurate prediction of the remaining useful life of a lithium–ion battery (LiB) is of paramount importance for ensuring its durable operation. To achieve more accurate prediction with limited data, this paper proposes an RVM-GM algorithm based on dynamic window size. The method combines [...] Read more.

Accurate prediction of the remaining useful life of a lithium–ion battery (LiB) is of paramount importance for ensuring its durable operation. To achieve more accurate prediction with limited data, this paper proposes an RVM-GM algorithm based on dynamic window size. The method combines the advantages of the relevance vector machine (RVM) algorithm and grey predictive model (GM). The RVM is applied to provide the relevance vectors of fitting function and output probability prediction, and the GM is used to obtain the trend prediction with limited data information. The algorithm is further verified by the NASA PCoE lithium–ion battery data repository. The experimental prediction results of different batteries data show that the proposed algorithm has less error while applying a dynamic window size compared with a fixed window size, while it has higher prediction accuracy than particle filter algorithm (PF) and convolutional neural network (CNN), which has verified the effectiveness of the proposed algorithm. 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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14 pages, 17710 KiB

Open AccessArticle

A Reference Voltage Self-Correction Method for Capacitor Voltage Offset Suppression of Three-Phase Four-Switch Inverter-Fed PMSM Drives

by Wei Chen, Sai Wang, Xinmin Li and Guozheng Zhang

World Electr. Veh. J. 2022, 13(2), 24; https://doi.org/10.3390/wevj13020024 - 19 Jan 2022

Cited by 3 | Viewed by 2077

Abstract

This paper proposes a capacitor voltage offset suppression method based on reference voltage self-correction for a three-phase four-switch (TPFS) inverter-fed permanent magnet synchronous motor (PMSM) drive system to improve the motor control performance. Firstly, the αβ-axis reference voltage deviation caused by capacitor voltage [...] Read more.

This paper proposes a capacitor voltage offset suppression method based on reference voltage self-correction for a three-phase four-switch (TPFS) inverter-fed permanent magnet synchronous motor (PMSM) drive system to improve the motor control performance. Firstly, the αβ-axis reference voltage deviation caused by capacitor voltage offset is analyzed, and the relationship between the voltage to be compensated and the offset is obtained. Then, the capacitor voltage offset is calculated according to the motor speed, rotor position, current vector amplitude, and capacitance on the capacitor bridge arm of the TPFS inverter. Finally, the reference voltage is corrected according to the voltage to be compensated and the capacitor voltage offset. This method is simple and easy to implement, and there is no need to add voltage sensors or filters in the system to extract the capacitor voltage offset, and there is no complex parameter adjustment. The effectiveness of the proposed method is verified by experiments on a 20 kW interior permanent magnet synchronous motor. Full article

(This article belongs to the Special Issue Design, Analysis and Optimization of Electrical Machines and Drives for Electric Vehicles)

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16 pages, 4667 KiB

Open AccessArticle

Real-Time Fire Detection Method for Electric Vehicle Charging Stations Based on Machine Vision

by Shiyu Zhang, Qing Yang, Yuchen Gao and Dexin Gao

World Electr. Veh. J. 2022, 13(2), 23; https://doi.org/10.3390/wevj13020023 - 18 Jan 2022

Cited by 4 | Viewed by 3895

Abstract

During the charging process of electric vehicles (EV), the circuit inside the charger plug is connected in series, the charger input voltage does not match the rated input voltage, the temperature caused by the severe heating of the charging time is too high [...] Read more.

During the charging process of electric vehicles (EV), the circuit inside the charger plug is connected in series, the charger input voltage does not match the rated input voltage, the temperature caused by the severe heating of the charging time is too high for too long, and other factors are very likely to trigger a fire in the vehicle charging pile. In this paper, an improved You Only Look Once v4 (YOLOv4) real-time target detection algorithm based on machine vision is proposed to monitor the site based on existing monitoring equipment, transmit live video information in real-time, expand the monitoring range, and significantly reduce the cost of use. During the experiment, the improved neural network model was trained by a homemade fire video image dataset, and a K-means clustering algorithm iwasintroduced to recalculate the anchor frame size for the specific object of flame; the existing dataset was used to perform multiple divisions by using a tenfold cross-validation algorithm, thus avoiding the selection of chance hyperparameters and models that do not have generalization ability because of special divisions. The experimental results show that the improved algorithm is fast and accurate in detecting large-size flames in real-time and small-size flames at the beginning of a fire, with a detection speed of 43 fps/s, mAP value of 91.53%, and F1 value of 0.91. Compared with YOLOv3 and YOLOv4 models, the improved model is sensitive to detecting different sizes of flames. It can suppress false alarms well in a variety of complex lighting environments. The prediction frame size fits the area where the target is located, the detection accuracy remains stable, and the comprehensive performance of the network model is significantly improved to meet the demand of real-time monitoring. It is significant for developing the EV industry and enhancing emergency response capability. Full article

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World Electr. Veh. J., Volume 13, Issue 2 (February 2022) – 21 articles

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