Journal Description
World Electric Vehicle Journal
World Electric Vehicle Journal
is the first peer-reviewed, international, scientific journal that comprehensively covers all studies related to battery, hybrid, and fuel cell electric vehicles. It is the official journal of the World Electric Vehicle Association (WEVA) and its members, the European Association for e-Mobility (AVERE), Electric Drive Transportation Association (EDTA), and Electric Vehicle Association of Asia Pacific (EVAAP). It is published monthly online by MDPI from Volume 9, Issue 1 (2018).
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), Ei Compendex, and other databases.
- Journal Rank: CiteScore - Q2 (Automotive Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 12.3 days after submission; acceptance to publication is undertaken in 4.6 days (median values for papers published in this journal in the second half of 2022).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Latest Articles
Process and Material Analysis of Laser- and Convection-Dried Silicon–Graphite Anodes for Lithium-Ion Batteries
World Electr. Veh. J. 2023, 14(4), 87; https://doi.org/10.3390/wevj14040087 - 29 Mar 2023
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Drying electrodes is very cost-intensive as it is characterized by high energy and space consumption. Laser drying is considered a promising alternative process due to direct energy input and lower operating costs. However, it is unclear whether the same product and process quality
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Drying electrodes is very cost-intensive as it is characterized by high energy and space consumption. Laser drying is considered a promising alternative process due to direct energy input and lower operating costs. However, it is unclear whether the same product and process quality can be achieved with laser drying. Silicon–graphite anodes with different silicon contents were processed using either a high-power diode laser or a convection oven. The laser-drying process was investigated using thermography, and the effect of laser drying on the electrode quality was examined using adhesion and residual moisture measurements. Furthermore, thermogravimetric analysis, SEM images and electrical conductivity were used to analyse the laser- and convection-dried anodes. It was shown that silicon–graphite anodes can also be manufactured using laser drying, with a significant reduction in drying time of over 80%.
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Open AccessArticle
Bi-Directional Cuk Equalizer-Based Li-Ion Battery Pack Equalization Control Strategy Research
World Electr. Veh. J. 2023, 14(4), 86; https://doi.org/10.3390/wevj14040086 - 28 Mar 2023
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For the secure usage of battery charging and discharging within electric vehicles, the study of cell pack equalization technology is essential. Therefore, in this paper, an improved Bidirectional Cuk equalizer (BCEQ) structure based on a variable-domain fuzzy PID (VFPID) control equalization strategy is
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For the secure usage of battery charging and discharging within electric vehicles, the study of cell pack equalization technology is essential. Therefore, in this paper, an improved Bidirectional Cuk equalizer (BCEQ) structure based on a variable-domain fuzzy PID (VFPID) control equalization strategy is recommended in stages. With the new equalization topology, only half of the capacitive and inductive components are needed to transfer energy between any two individual cells in the power supply. In addition, the proposed VFPID control strategy further improves the efficiency of the equalization model by dynamically adjusting the magnitude of the equalization current parameters. Through simulation experiments, the improved topology was capable of substantially lessening the equalization time and increasing energy utilization by more than 4%. In comparison with the fuzzy PID (FPID) algorithm, around 27.3% faster equalization times can be achieved with the VFPID algorithm; the VFPID algorithm also performed well under the Dynamic Stress Test (DST) condition, demonstrating that the topology and equalization strategy suggested in this paper can successfully address the inconsistency of the FPID algorithm. It has been revealed that the topology and equalization methodology offered in this paper is effective in solving the battery pack inconsistency.
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Open AccessArticle
High-Frequency Signal Injection-Based Sensorless Control for Dual-Armature Flux-Switching Permanent Magnet Machine
World Electr. Veh. J. 2023, 14(4), 85; https://doi.org/10.3390/wevj14040085 - 27 Mar 2023
Abstract
The new topology of the dual-armature flux-switching permanent magnet machine (DA-FSPM) leads to new characteristics and issues in the control of the machine, of which the mutual inductance of the two sets of armature windings is the most important one. This paper proposes
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The new topology of the dual-armature flux-switching permanent magnet machine (DA-FSPM) leads to new characteristics and issues in the control of the machine, of which the mutual inductance of the two sets of armature windings is the most important one. This paper proposes a novel position–sensorless control method based on high-frequency injection (HFI) for DA-FSPM. The high-frequency model of the machine is derived, and the theory of the position estimation method is proposed. Different from the conventional HFI-based position estimation method, the proposed method utilizes the mutual inductance of the DA-FSPM rather than the machine saliency. Meanwhile, because the extracted position information based on the mutual inductance is more obvious, the proposed method also has better steady and dynamic performance. Then, the position observer based on the phase lock loop and the initial position detection method for the DA-FSPM is proposed. The experiments are executed on a DA-FSPM prototype with three-phase stator windings and five-phase rotor windings to prove the effectiveness and superiority of the proposed method.
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(This article belongs to the Special Issue Recent Advances in Novel Permanent Magnet and Magnetless Machines and Control for Electric Vehicles)
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Research on Trajectory Tracking Control of Driverless Electric Formula Racing Car Based on Game Theory
World Electr. Veh. J. 2023, 14(4), 84; https://doi.org/10.3390/wevj14040084 - 25 Mar 2023
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A game theory based trajectory tracking control method is studied for the dual-objective optimization problem of trajectory tracking the accuracy and driving stability of driverless electric formula racing cars in high-speed trajectory conditions. The general control strategy and the model predictive controller based
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A game theory based trajectory tracking control method is studied for the dual-objective optimization problem of trajectory tracking the accuracy and driving stability of driverless electric formula racing cars in high-speed trajectory conditions. The general control strategy and the model predictive controller based on the evolutionary game between the two players are designed to optimize their own decisions to achieve the optimal payoff for themselves, and to obtain the optimal solution to the dual-objective optimization problem, by taking the dual objectives of trajectory tracking accuracy and driving stability as the two players in the game. Considering the influence of the dynamic environment, the time-varying interactive game mechanism between two plays is introduced, the game payoff matrix is established, the weights of each subject are determined, and a dynamic replication system is constructed by weight evolution to find the optimal equilibrium strategy for the model prediction controller. The simulated results show that the designed controller can play a significant role in optimizing the trajectory tracking accuracy and driving stability compared to a single model predictive controller under different speed tracking conditions.
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(This article belongs to the Special Issue Advanced Vehicle System Dynamics and Control)
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Neural Network PID-Based Preheating Control and Optimization for a Li-Ion Battery Module at Low Temperatures
World Electr. Veh. J. 2023, 14(4), 83; https://doi.org/10.3390/wevj14040083 - 25 Mar 2023
Abstract
Low temperatures induce limited charging ability and lifespan in lithium-ion batteries, and may even cause accidents. Therefore, a reliable preheating strategy is needed to address this issue. This study proposes a low-temperature preheating strategy based on neural network PID control, considering temperature increase
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Low temperatures induce limited charging ability and lifespan in lithium-ion batteries, and may even cause accidents. Therefore, a reliable preheating strategy is needed to address this issue. This study proposes a low-temperature preheating strategy based on neural network PID control, considering temperature increase rate and consistency. In this strategy, electrothermal films are placed between cells for preheating; battery module areas are differentiated according to the convective heat transfer rate; a controller regulates heating power to control the maximum temperature difference during the preheating process; and a co-simulation model is established to verify the proposed warm-up strategy. The numerical calculation results indicate that the battery module can be preheated to the target temperature under different ambient temperatures and control targets. The coupling relationship between the preheating time and the maximum temperature difference during the preheating process is studied and multi-objective optimization is carried out based on the temperature increase rate and thermal uniformity. The optimal preheating strategy is proven to ensure the temperature increase rate and effectively suppress temperature inconsistency of the module during the preheating process. Although preheating time is extended by 17%, the temperature difference remains within the safety threshold, and the maximum temperature difference is reduced by 49.6%.
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(This article belongs to the Special Issue Recent Advances in Lithium-Ion Battery Safety and Aging Issues for Electric Vehicles)
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Design of Permanent Magnet-Assisted Synchronous Reluctance Motor with Low Torque Ripple
World Electr. Veh. J. 2023, 14(4), 82; https://doi.org/10.3390/wevj14040082 - 24 Mar 2023
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Permanent magnet-assisted synchronous reluctance motors (PMSRMs) have been widely used in household appliances, national defense and the military, due to their advantages of low cost and high efficiency. However, their excessive torque ripple cause a series of problems, such as high vibration and
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Permanent magnet-assisted synchronous reluctance motors (PMSRMs) have been widely used in household appliances, national defense and the military, due to their advantages of low cost and high efficiency. However, their excessive torque ripple cause a series of problems, such as high vibration and noise. To solve this problem, this paper first considers the important factor that causes the torque ripple—the cogging torque. Firstly, the generating principle of the cogging torque is analyzed, and a method combining magnetic pole migration and the stator auxiliary groove is proposed. On this basis, considering the position, width, depth, quantity and shape of the auxiliary groove, the Taguchi method is used to optimize the proposed improved structure. Finally, a new motor structure that can minimize torque ripple is obtained. Compared with the original structure, the cogging torque is reduced by 57.6%, the torque ripple is reduced by 38%, and the electromagnetic torque is only reduced by 1.6%.
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(This article belongs to the Special Issue Electrical Machines Design and Control in Electric Vehicles)
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Investigation and Development of the Brushless and Magnetless Wound Field Synchronous Motor Drive System for Electric Vehicle Application
World Electr. Veh. J. 2023, 14(4), 81; https://doi.org/10.3390/wevj14040081 - 24 Mar 2023
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In order to solve the problems of soaring costs and supply fluctuation in permanent magnet materials, this paper investigates and develops a magnetless wound field synchronous motor (WFSM) drive system for electric vehicle (EV) application. As the crucial drive component for EVs, the
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In order to solve the problems of soaring costs and supply fluctuation in permanent magnet materials, this paper investigates and develops a magnetless wound field synchronous motor (WFSM) drive system for electric vehicle (EV) application. As the crucial drive component for EVs, the proposed WFSM in this paper has a two-stage structure which is described as the exciter and the main motor. The excitation characteristics of the exciter that provide power to the rotor field winding are emphatically analyzed. In addition, the discrete time domain armature current regulator and excitation current regulator are designed and analyzed for the high-performance WFSM drive system. A current coordinated control strategy for the full speed range is proposed to expand the constant power region. The experiment shows that the excitation characteristics and torque capability of the WFSM are consistent with the analysis, and proves that the WFSM is a potential solution for the magnetless motor for EV application.
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(This article belongs to the Special Issue Recent Advances in Novel Permanent Magnet and Magnetless Machines and Control for Electric Vehicles)
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Identification of Challenges for Second-Life Battery Systems—A Literature Review
by
, , , , and
World Electr. Veh. J. 2023, 14(4), 80; https://doi.org/10.3390/wevj14040080 - 24 Mar 2023
Abstract
Lithium-ion batteries (LIBs) have been proven to be increasingly popular and are the solution of choice for many companies and business models around the world. One major question for battery owners is how to deal with returning batteries if they still contain sufficient
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Lithium-ion batteries (LIBs) have been proven to be increasingly popular and are the solution of choice for many companies and business models around the world. One major question for battery owners is how to deal with returning batteries if they still contain sufficient capacity for operation. In this case, those energy storages can still be used in different, less-required second-life applications, such as stationary battery storage systems, contributing to increased product sustainability and economic benefits at the same time. However, the second-life business model is still at an early stage of development due to the young EV market in combination with long vehicle lifetimes. As a consequence, there are several barriers in various thematic fields, complicating the rededication process for LIBs. This review paper focuses on a summary of barriers to second-life adoption published with scientific reference. Furthermore, barriers are clustered thematically to provide a transparent landscape picture and valuable insights into the rededication process of LIBs.
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(This article belongs to the Special Issue Battery Production for Electric Vehicles)
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Driving Decisions for Autonomous Vehicles in Intersection Environments: Deep Reinforcement Learning Approaches with Risk Assessment
World Electr. Veh. J. 2023, 14(4), 79; https://doi.org/10.3390/wevj14040079 - 23 Mar 2023
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Intersection scenarios are one of the most complex and high-risk traffic scenarios. Therefore, it is important to propose a vehicle driving decision algorithm for intersection scenarios. Most of the related studies have focused on considering explicit collision risks while lacking consideration for potential
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Intersection scenarios are one of the most complex and high-risk traffic scenarios. Therefore, it is important to propose a vehicle driving decision algorithm for intersection scenarios. Most of the related studies have focused on considering explicit collision risks while lacking consideration for potential driving risks. Therefore, this study proposes a deep-reinforcement-learning-based driving decision algorithm to address these problems. In this study, a non-deterministic vehicle driving risk assessment method is proposed for intersection scenarios and introduced into a learning-based intelligent driving decision algorithm. In addition, this study proposes an attention network based on state information. In this study, a typical intersection scenario was constructed using simulation software, and experiments were conducted. The experimental results show that the algorithm proposed in this paper can effectively derive a driving strategy with both driving efficiency and driving safety in the intersection driving scenario. It is also demonstrated that the attentional neural network designed in this study helps intelligent vehicles to perceive the surrounding environment more accurately, improves the performance of intelligent vehicles, as well as accelerates the convergence speed.
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(This article belongs to the Special Issue Recent Advance in Intelligent Vehicle)
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Design of Auto-Tuning Nonlinear PID Tracking Speed Control for Electric Vehicle with Uncertainty Consideration
World Electr. Veh. J. 2023, 14(4), 78; https://doi.org/10.3390/wevj14040078 - 23 Mar 2023
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This study presents a new auto-tuning nonlinear PID controller for a nonlinear electric vehicle (EV) model. The purpose of the proposed control was to achieve two aims. The first aim was to enhance the dynamic performance of the EV regarding internal and external
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This study presents a new auto-tuning nonlinear PID controller for a nonlinear electric vehicle (EV) model. The purpose of the proposed control was to achieve two aims. The first aim was to enhance the dynamic performance of the EV regarding internal and external disturbances. The second aim was to minimize the power consumption of the EV. To ensure that these aims were achieved, two famous controllers were implemented. The first was the PID controller based on the COVID-19 optimization. The second was the nonlinear PID (NPID) optimized controller, also using the COVID-19 optimization. Several driving cycles were executed to compare their dynamic performance and the power consumption. The results showed that the auto-tuning NPID had a smooth dynamic response, with a minimum rise and settling time compared to other control techniques (PID and NPID controllers). Moreover, it achieved low continuous power consumption throughout the driving cycles.
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(This article belongs to the Special Issue Vehicle Control and Drive Systems for Electric Vehicles)
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Sector Coupling through Vehicle to Grid: A Case Study for Electric Vehicles and Households in Berlin, Germany
World Electr. Veh. J. 2023, 14(3), 77; https://doi.org/10.3390/wevj14030077 - 22 Mar 2023
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A key factor in limiting global warming is the conversion of conventional electricity generation to renewable energy sources. However, a major obstacle is that renewable energy generation and energy demand often do not coincide in time, and energy must therefore be stored temporarily.
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A key factor in limiting global warming is the conversion of conventional electricity generation to renewable energy sources. However, a major obstacle is that renewable energy generation and energy demand often do not coincide in time, and energy must therefore be stored temporarily. Vehicle to grid (V2G) can be used to store excess renewable energy in battery electric vehicles (BEVs) and feed it back into the electric grid when needed. For effective V2G operation, the grid may have to be expanded, as the energy needs to be transported to BEVs. However, the grid should only be strengthened where renewable energy demand exceeds current grid capacity due to high grid expansion costs. This requires a method that determines the spatial distribution of V2G potential at a high resolution. Since such a method has not yet been reported in the existing literature, and so is developed in this paper. The method is demonstrated for the city of Berlin and its 448 sub-districts. For each sub-district, the method allows determining the percentage of residential and BEV energy demand that can be met by renewables if V2G is deployed, and answers the question of whether a full renewable supply is possible. The results show that BEVs can be effectively used as intermediate storage for renewable energy. If 30% of the BEVs participate in V2G, more than 99% of the energy demand of households and BEVs in Berlin can be covered by renewables on certain days. On the other hand, V2G deployment increases the average peak load in the districts by up to 100% and results in a nearly double load on vehicle batteries. High shares of renewable energy can be observed in districts with a high degree of motorization, which are predominantly found in the outskirts of the city.
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Optimizing Structural Parameters of PEMFC Based on Taguchi Method
World Electr. Veh. J. 2023, 14(3), 76; https://doi.org/10.3390/wevj14030076 - 20 Mar 2023
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Proton exchange membrane fuel cell (PEMFC) has become one of the new energy vehicle powertrains due to its special advantages, such as no pollution to the environment, high energy efficiency and power density. In order to improve the performance, a three-dimensional simulation model
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Proton exchange membrane fuel cell (PEMFC) has become one of the new energy vehicle powertrains due to its special advantages, such as no pollution to the environment, high energy efficiency and power density. In order to improve the performance, a three-dimensional simulation model of the actual PEMFC is constructed. Combined with the mathematical models such as the electrochemical model and current conservation model, the model is calibrated by experiments. When the working voltage is 0.64 V, the error of the simulation results is 0.73%, compared with the experimental data. Then, the Taguchi method is used to design a multi-factor and multi-level orthogonal experimental scheme of PEMFC. Based on the orthogonal experimental table, the effects of different anode wave channel distortion, gas diffusion layer thickness and gas diffusion layer porosity on the current density are studied with a simulation experiment. The influence of the above factors on the orthogonal experiment results is analyzed by the signal-to-noise ratio. The regression equation is obtained by calculating the orthogonal experimental data. The t-test results are greater than 3.49, which indicates that each independent variable in the regression equation is important. R2 test is 0.915, and the F test is 53.508, indicating that the regression equation is significant and the optimal and worst structural parameter combinations are predicted. The current density reaches 14,190.18.04 under the optimal structure combination, which is 6.14% higher than the calibrated model. Single factor experiments are carried out on these three different structural parameters to verify the effectiveness of the Taguchi method, and the best combination of structural parameters is obtained.
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Open AccessArticle
Flicker-Free LED Driver Based on Cuk Converter with Integrated Magnetics
World Electr. Veh. J. 2023, 14(3), 75; https://doi.org/10.3390/wevj14030075 - 19 Mar 2023
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Electric vehicles contain various types of light emitting diode (LED) devices. A significant twice-line-frequency ripple current is usually produced in a conventional offline LED driver with a high power factor. In this paper, a flicker-free LED driver based on isolated Cuk converter with
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Electric vehicles contain various types of light emitting diode (LED) devices. A significant twice-line-frequency ripple current is usually produced in a conventional offline LED driver with a high power factor. In this paper, a flicker-free LED driver based on isolated Cuk converter with integrated magnetic technique is proposed. Two inductors and power transformer are combined into one magnetic core to eliminate the wave current as much as possible. With time domain analysis in electrical circuit and magnetic circuit, the operation principle, operational waveforms, and transfer function are analyzed in detail. Finally, experimental results from a 30 W laboratory prototype supplied by a 220 V grid validate the effectiveness of proposed LED driver.
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(This article belongs to the Topic Energy Management and Efficiency in Electric Motors, Drives, Power Converters and Related Systems)
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TD3-Based EMS Using Action Mask and Considering Battery Aging for Hybrid Electric Dump Trucks
World Electr. Veh. J. 2023, 14(3), 74; https://doi.org/10.3390/wevj14030074 - 17 Mar 2023
Cited by 1
Abstract
The hybrid electric dump truck is equipped with multiple power sources, and each powertrain component is controlled by an energy management strategy (EMS) to split the demanded power. This study proposes an EMS based on deep reinforcement learning (DRL) algorithm to extend the
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The hybrid electric dump truck is equipped with multiple power sources, and each powertrain component is controlled by an energy management strategy (EMS) to split the demanded power. This study proposes an EMS based on deep reinforcement learning (DRL) algorithm to extend the battery life and reduced total usage cost for the vehicle, namely the twin delayed deep deterministic policy gradient (TD3) based EMS. Firstly, the vehicle model is constructed and the optimization objective function, including battery aging cost and fuel consumption cost, is designed. Secondly, the TD3-based EMS is used for continuous action control of ICE power based on vehicle state, and the action mask is applied to filter out invalid actions. Thirdly, the simulations of the EMSs are trained under the CHTC-D driving cycle and C-WTVC driving cycle. The results show that the action mask improves the convergence efficiency of the strategies, and the proposed TD3-based EMS outperforms the deep deterministic policy gradient (DDPG) based EMS. Meanwhile, the battery life is extended by 36.17% under CHTC-D and 35.49% under C-WTVC, and the total usage cost is reduced by 4.30% and 2.49% when the EMS considers battery aging. In summary, the proposed TD3-based EMS can extend the battery life and reduce usage cost, and provides a method to solve the optimization problem for the EMS of hybrid power systems.
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(This article belongs to the Topic Electric Vehicles Energy Management)
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Exploring Factors Affecting People’s Willingness to Use a Voice-Based In-Car Assistant in Electric Cars: An Empirical Study
World Electr. Veh. J. 2023, 14(3), 73; https://doi.org/10.3390/wevj14030073 - 14 Mar 2023
Abstract
Voice-based digital assistants are growing in popularity and have been acknowledged as a crucial part of in-car interaction. Currently, academic attention is being paid to various voice assistant scenarios. However, sparse literature focuses on the adoption of voice assistants within the in-vehicle context.
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Voice-based digital assistants are growing in popularity and have been acknowledged as a crucial part of in-car interaction. Currently, academic attention is being paid to various voice assistant scenarios. However, sparse literature focuses on the adoption of voice assistants within the in-vehicle context. The objective of this paper is to examine key factors influencing people’s willingness to use voice assistance in electric cars. First, eight general variables were identified based on the literature review, as well as four demographic variables. These factors were then integrated to construct a hypothetical research model. After that, we carried out an empirical study to examine the structural relationships in the model based on the questionnaire survey results (N = 427). The hypothesis testing results indicated that most path relationships among variables were validated. Finally, we discussed the research findings and developed corresponding design strategies to enhance user acceptance towards in-car voice assistants, both from designers’ and car enterprises’ viewpoints. This article offers valuable theoretical and practical implications for the development of such technologies.
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(This article belongs to the Topic Advanced Electric Vehicle Technology)
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Pricing Strategy for a Virtual Power Plant Operator with Electric Vehicle Users Based on the Stackelberg Game
World Electr. Veh. J. 2023, 14(3), 72; https://doi.org/10.3390/wevj14030072 - 14 Mar 2023
Abstract
With the popularity and promotion of electric vehicles (EVs), virtual power plants (VPPs) provide a new means for the orderly charging management of decentralized EVs. How to set the price of electricity sales for VPP operators to achieve a win–win situation with EV
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With the popularity and promotion of electric vehicles (EVs), virtual power plants (VPPs) provide a new means for the orderly charging management of decentralized EVs. How to set the price of electricity sales for VPP operators to achieve a win–win situation with EV users is a hot topic of current research. Based on this, this paper first proposes a Stackelberg game model in which the VPP participates in the orderly charging management of EVs as a power sales operator, where the operator guides the EV users to charge in an orderly manner by setting a reasonable power sales price and coordinates various distributed resources to jointly participate in the power market. Furthermore, taking into account the impact of wind power output uncertainty on VPP operation, a robust optimization method is used to extend the deterministic Stackelberg game pricing model into a robust optimization model, and a robust adjustment factor is introduced to flexibly adjust the conservativeness of the VPP operator’s bidding scheme in the energy market. The model is then transformed into a robust mixed-integer linear programming (RMILP) problem solved by Karush–Kuhn–Tucker (KKT) conditions and strong dyadic theory. Finally, the effectiveness of the solution method is verified in the calculation example, which gives the optimal pricing strategy for the VPP operator, the optimal charging scheme for EV users, and the remaining internal resources’ contribution plan, providing an important idea for the VPP to centrally manage the charging behavior of EVs and improve its own operating revenue.
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(This article belongs to the Special Issue Novel Electric Vehicle Technology towards Low Carbon Future: Advanced Powertrain, Energy Management and Grid Interaction)
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Academic and Corporate Vehicle Electrification Research
by
and
World Electr. Veh. J. 2023, 14(3), 71; https://doi.org/10.3390/wevj14030071 - 10 Mar 2023
Abstract
We developed and used methodology to analyze scientific publications in Scopus relating to vehicle electrification and associated key enabling technologies: batteries, fuel cells and electric machines with power electronics. The global research landscape was mapped, and an analysis of the 16 most active
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We developed and used methodology to analyze scientific publications in Scopus relating to vehicle electrification and associated key enabling technologies: batteries, fuel cells and electric machines with power electronics. The global research landscape was mapped, and an analysis of the 16 most active countries was carried out. Vehicle electrification publications are rewarded with a high citation impact, and they include corporate actors to a great extent. China dominates in vehicle electrification research as well as in the enabling technologies, and China’s position is set to become even more dominating. Battery research has grown rapidly with a high citation impact, whereas the volume of research for the other enabling technologies was more constant during 2017–2021. Automakers’ research that has led to scientific publications was specifically studied. Ford Motor Company was the automaker with the highest number of vehicle electrification publications during 2017–2021. A large share of the automakers’ publications was co-authored with academic actors, and such publications were rewarded with a higher citation impact than those without. However, the share of international co-publications among the automakers was meager. It is concluded that the analysis of vehicle electrification publications gives an overview of the rapidly developing field. Moreover, the analysis of automakers’ involvement in such research is one way of obtaining one perspective on their strategies and priorities.
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(This article belongs to the Special Issue EVS35—International Electric Vehicle Symposium and Exhibition (Oslo, Norway))
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Open AccessArticle
Effect of Directional Auditory Takeover Request on Takeover Behavior and Eye Movement in Conditionally Automated Driving
World Electr. Veh. J. 2023, 14(3), 70; https://doi.org/10.3390/wevj14030070 - 09 Mar 2023
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Conditionally automated driving (CAD) systems allow the driver to temporarily disengage from driving tasks. The significant concern of CAD is to ensure a safe and timely transition to the manual driving mode when the system exceeds its limits and issues a takeover request
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Conditionally automated driving (CAD) systems allow the driver to temporarily disengage from driving tasks. The significant concern of CAD is to ensure a safe and timely transition to the manual driving mode when the system exceeds its limits and issues a takeover request (TOR). The aim of this study was to investigate the effect of directional auditory TOR on the driver takeover process. A within-subject experimental design was used: twenty-four participants drove four times in an automated driving simulation scenario and received two non-directional auditory TORs and two directional auditory TORs (TOR directions corresponding to the orientation of potential hazards). The takeover behavior and eye movement characteristics relevant to the takeover process were collected. The results showed that directional auditory TOR enabled drivers to shift their visual attention to the hazards’ area faster than non-directional auditory TOR, accelerating the driver’s understanding of the road environment and improving takeover behavior. The study may provide a reference for the design of takeover requests for conditionally automated driving.
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Open AccessArticle
Sensorless Control Method of High-Speed Permanent Magnet Synchronous Motor Based on Discrete Current Error
World Electr. Veh. J. 2023, 14(3), 69; https://doi.org/10.3390/wevj14030069 - 09 Mar 2023
Abstract
When the Surface-Mounted Permanent Magnet Synchronous Motor (SPMSM) is in the condition of high-speed and low carrier-wave ratio, the performance of sensorless control is more affected by digital control delay, parameter inaccuracy, and other factors. This paper presents a sensorless control method based
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When the Surface-Mounted Permanent Magnet Synchronous Motor (SPMSM) is in the condition of high-speed and low carrier-wave ratio, the performance of sensorless control is more affected by digital control delay, parameter inaccuracy, and other factors. This paper presents a sensorless control method based on the static error between the discrete d-axis current and the corresponding reference value. If there is no error in position angle, the discrete d-axis current should have no static error approximately. In addition, the static error of the d-axis current is related to the speed, so the PI controller with a variable proportional integral coefficient is used to ensure a stable error compensation performance in a wide speed range. The proposed method can accurately compensate the estimated rotor position of the motor under high-speed and low carrier ratio conditions and improve the accuracy of sensorless control. It provides an effective measure for the stable and reliable acceleration of electric vehicles and has specific practical significance for the development of electric vehicle control.
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(This article belongs to the Special Issue Electrical Machines Design and Control in Electric Vehicles)
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GridShield—Optimizing the Use of Grid Capacity during Increased EV Adoption
World Electr. Veh. J. 2023, 14(3), 68; https://doi.org/10.3390/wevj14030068 - 07 Mar 2023
Abstract
With the increasing adoption rate of electric vehicles, power peaks caused by many cars simultaneously charging on the same low-voltage grid can cause local overloading and power outages. Smart charging solutions should spread this load, but there is a residual risk of incidental
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With the increasing adoption rate of electric vehicles, power peaks caused by many cars simultaneously charging on the same low-voltage grid can cause local overloading and power outages. Smart charging solutions should spread this load, but there is a residual risk of incidental peaks. A decentralized and autonomous technology called GridShield is being developed to reduce the likelihood of a transformer’s fuse blowing when other congestion solutions have failed. It serves as a measure of last resort to protect the grid against local power failures from unpredicted congestion by temporarily limiting the virtual capacity of charging stations. This paper describes the technical development and demonstrates how GridShield can keep a transformer load below a critical limit using simulations and real-world tests. It optimizes grid capacity while ensuring grid reliability.
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(This article belongs to the Special Issue EVS35—International Electric Vehicle Symposium and Exhibition (Oslo, Norway))
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