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. The journal is owned by 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 has been published monthly online by MDPI since 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 14.1 days after submission; acceptance to publication is undertaken in 3.7 days (median values for papers published in this journal in the second half of 2023).
- 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.
Impact Factor:
2.3 (2022)
Latest Articles
Analysis of Leakage Current in Dynamic Wireless Power Transfer Systems Based on LCC-S Architecture
World Electr. Veh. J. 2024, 15(6), 225; https://doi.org/10.3390/wevj15060225 (registering DOI) - 22 May 2024
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This paper investigates the issue of leakage current at the transmitter in the Dynamic Wireless Power Transfer (DWPT) system for electric vehicles and puts forward a novel bilateral resonant compensation topology structure based on the conventional LCC-S architecture. Based on the LCC-S framework,
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This paper investigates the issue of leakage current at the transmitter in the Dynamic Wireless Power Transfer (DWPT) system for electric vehicles and puts forward a novel bilateral resonant compensation topology structure based on the conventional LCC-S architecture. Based on the LCC-S framework, a circuit model was developed for traditional (unilateral)/bilateral resonant compensation topologies. The Fourier series voltage-to-earth expansions for the power supply rail were deduced for both topologies. Subsequently, the voltage-to-earth waveforms for the power supply rail were obtained by utilizing the Fourier series expansions of the voltage-to-earth and the corresponding circuit simulation models. The results demonstrate the efficacy of the bilateral resonant compensation topology in mitigating higher-order harmonics of the voltage to earth on the power supply rail by effectively suppressing the distortion in the leakage current and minimizing its conduction. The effectiveness of the double-ended resonant compensation topology in suppressing leakage current conduction has been verified through experimental tests and waveform comparisons of the voltage to earth and leakage current on the power supply rail under two different topologies. Through experimental testing, during which the unilateral/bilateral resonant compensation topologies were compared, an analysis was conducted on the waveforms of the voltage to earth and leakage current of the power supply rail. The results verified the effectiveness of the bilateral resonant compensation topology in mitigating the conduction of leakage current. This study provides empirical evidence supporting the use of the bilateral resonant compensation topology for suppressing leakage current in power rail applications.
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Open AccessArticle
A Predictive Cabin Conditioning Strategy for Battery Electric Vehicles
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Patrick Schutzeich, Stefan Pischinger, David Hemkemeyer, Kai Franke and Paul Hamelbeck
World Electr. Veh. J. 2024, 15(6), 224; https://doi.org/10.3390/wevj15060224 - 22 May 2024
Abstract
This paper is based on the work presented at EVS36 in Sacramento. The core of the work deals with the cabin climate control of battery electric vehicles (BEV) using model predictive control (MPC) approaches. These aim to reduce the energy demand for cabin
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This paper is based on the work presented at EVS36 in Sacramento. The core of the work deals with the cabin climate control of battery electric vehicles (BEV) using model predictive control (MPC) approaches. These aim to reduce the energy demand for cabin air conditioning while maintaining comfort and air quality. The first step briefly overviews model predictive control approaches and the respective fundamentals. Afterward, the modeling for the system dynamics is explained. The challenge for the system model considering humid air is discussed, and the first implementation method is presented. With the added equations for the air quality and humidity, a logic to prevent window fogging was developed to improve safety. Ultimately, model-in-the-loop (MiL) investigations identified an energy-saving potential of up to 15.4% for cold and 39.7% for hot conditions compared to a rule-based strategy. In addition, the investigations carried out showed that it was also possible to improve indoor comfort by specifically influencing the air quality and humidity. Together with the safety criteria introduced to prevent window fogging, it was possible to present a strategy that can significantly improve thermal management for the cabin in modern BEVs.
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(This article belongs to the Special Issue EVS36—International Electric Vehicle Symposium and Exhibition (California, USA))
Open AccessArticle
Analysis of the Driving Range Evaluation Method for Fuel-Cell Electric Vehicles
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Ting Guo, Letian Sun, Guozhuo Wang and Shiyu Wu
World Electr. Veh. J. 2024, 15(6), 223; https://doi.org/10.3390/wevj15060223 - 21 May 2024
Abstract
The range is one of the most important performance indicators for fuel-cell electric vehicles. This article focuses on the analysis of GB/T 43252-2023 “Energy Consumption and Range Test Methods for Fuel-Cell Electric Vehicles” from the perspective of a standard analysis, and conducts actual
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The range is one of the most important performance indicators for fuel-cell electric vehicles. This article focuses on the analysis of GB/T 43252-2023 “Energy Consumption and Range Test Methods for Fuel-Cell Electric Vehicles” from the perspective of a standard analysis, and conducts actual vehicle tests on the range test method and process. It introduces the measurement method of hydrogen gas filling for test vehicles, and explains the main content of the new standard revision and the main differences between the new and old standards. This article takes the fuel-cell dump truck as an example, and analyzed the relationship between the output power of fuel-cell stacks and power batteries during vehicle operation and driving conditions, as well as the proportion of fuel cell output power. The results show that the optimal output power range of fuel cells is 20–40 kW, accounting for 45.2% of the total operating time. When driving at high speeds, the output power of fuel cells is greater than that of power batteries.
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Open AccessArticle
Advancements in Battery Management Systems for Electric Vehicles: A MATLAB-Based Simulation of 4S3P Lithium-Ion Battery Packs
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Rakesh P. Tapaskar, Prashant P. Revankar and Sharanabasava V. Ganachari
World Electr. Veh. J. 2024, 15(6), 222; https://doi.org/10.3390/wevj15060222 - 21 May 2024
Abstract
As electric vehicles (EVs) gain momentum in the shift towards sustainable transportation, the efficiency and reliability of energy storage systems become paramount. Lithium-ion batteries stand at the forefront of this transition, necessitating sophisticated battery management systems (BMS) to enhance their performance and lifespan.
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As electric vehicles (EVs) gain momentum in the shift towards sustainable transportation, the efficiency and reliability of energy storage systems become paramount. Lithium-ion batteries stand at the forefront of this transition, necessitating sophisticated battery management systems (BMS) to enhance their performance and lifespan. This research presents an innovative simulation of a 4S3P lithium-ion battery pack using MATLAB R2023b, designed to refine BMS capabilities by employing advanced mathematical modelling and computational intelligence. The simulation meticulously analyses critical operational metrics such as state of charge (SOC), state of health (SOH), temperature variations, and electrical behaviour under diverse load scenarios, offering deep insights into the intricate dynamics of lithium-ion batteries in EV applications. The results corroborate the simulation model’s accuracy in reflecting actual battery pack performance and underscore significant improvements in BMS strategies, especially concerning predictive maintenance and adaptive charging techniques. By seamlessly integrating computational intelligence into BMS, this study lays the groundwork for more durable, efficient, and intelligent energy storage systems in electric vehicles, marking a significant stride in e-mobility technology.
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(This article belongs to the Special Issue Lithium-Ion Batteries for Electric Vehicle)
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Path-Following Control of Unmanned Vehicles Based on Optimal Preview Time Model Predictive Control
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Xinyu Wang, Xiao Ye, Yipeng Zhou and Cong Li
World Electr. Veh. J. 2024, 15(6), 221; https://doi.org/10.3390/wevj15060221 - 21 May 2024
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In order to reduce the lateral error of path-following control of unmanned vehicles under variable curvature paths, we propose a path-following control strategy for unmanned vehicles based on optimal preview time model predictive control (OP-MPC). The strategy includes the longitudinal speed limit, the
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In order to reduce the lateral error of path-following control of unmanned vehicles under variable curvature paths, we propose a path-following control strategy for unmanned vehicles based on optimal preview time model predictive control (OP-MPC). The strategy includes the longitudinal speed limit, the optimal preview time surface, and the model predictive control (MPC)controller. The longitudinal speed limit controls speed to prevent vehicle rollover and sideslip. The optimal preview time surface adjusts the preview time according to the vehicle speed and path curvature. The preview point determined by the preview time is used as the reference waypoint of OP-MPC controller. Finally, the effectiveness of the strategy was verified through simulation and with the real unmanned vehicle. The maximum lateral deviation obtained by the OP-MPC controller was reduced from 0.522 m to 0.145 m under the simulation compared with an MPC controller. The maximum lateral deviation obtained by the OP-MPC controller was reduced from 0.5185 m to 0.2298 m under the real unmanned vehicle compared with the MPC controller.
Full article
(This article belongs to the Special Issue Vehicle-Road Collaboration and Connected Automated Driving)
Open AccessArticle
Impact of Engine Inertia on P2 Mild HEV Fuel Consumption
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Gulnora Yakhshilikova, Sanjarbek Ruzimov, Andrea Tonoli and Akmal Mukhitdinov
World Electr. Veh. J. 2024, 15(5), 220; https://doi.org/10.3390/wevj15050220 - 19 May 2024
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The energy management system (EMS) of a hybrid electric vehicle (HEV) is an algorithm that determines the power split between the electrical and thermal paths. It defines the operating state of the power sources, i.e., the electric motor (EM) and the internal combustion
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The energy management system (EMS) of a hybrid electric vehicle (HEV) is an algorithm that determines the power split between the electrical and thermal paths. It defines the operating state of the power sources, i.e., the electric motor (EM) and the internal combustion engine (ICE). It is therefore one of the main factors that can significantly influence the fuel consumption and performance of hybrid vehicles. In the transmission path, the power generated by the ICE is in part employed to accelerate the rotating components of the powertrain, such as the crankshaft, flywheel, gears, and shafts. The main inertial components are the crankshaft and the flywheel. This additional power is significant during high-intensity acceleration. Therefore, the actual engine operation is different from that required by the power split unit. This study focuses on exploring the influence of engine inertia on HEV fuel consumption by developing a controller based on an equivalent consumption minimisation strategy (ECMS) that considers crankshaft and flywheel inertia. The optimal solution obtained by the ECMS controller is refined by incorporating the inertia effect of the main rotating components of the engine into the cost function. This reduces the engine operation during high inertial torque transient phases, resulting in a decrease in vehicle CO emissions by 2.34, 2.22, and 1.13 g/km for the UDDS, US06, and WLTC driving cycles, respectively.
Full article
(This article belongs to the Special Issue Vehicle Dynamics Control to Enhance Energy Efficiency and Safety of Electric and Hybrid Vehicles)
Open AccessArticle
Advancements in Battery Cell Finalization: Insights from an Expert Survey and Prospects for Process Optimization
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Tobias Robben, Christian Offermanns, Heiner Heimes and Achim Kampker
World Electr. Veh. J. 2024, 15(5), 219; https://doi.org/10.3390/wevj15050219 - 17 May 2024
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Battery cell finalization is a crucial process chain in battery manufacturing, contributing to a significant share of CAPEX and OPEX. Thus, there is a high cost-saving potential by improving the process chain. This research paper investigates various crucial facets of the cell finalization
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Battery cell finalization is a crucial process chain in battery manufacturing, contributing to a significant share of CAPEX and OPEX. Thus, there is a high cost-saving potential by improving the process chain. This research paper investigates various crucial facets of the cell finalization process in battery cell production through an expert survey. These include investment cost allocation, potential cost savings in sub-processes, reject generation, early detection of faulty cells, quality measurement techniques, and the utilization of inline data for early quality determination and real-time process control during the formation process. A solution approach for the implementation of electrochemical impedance spectroscopy for inline early quality determination is given. The results yield valuable insights for optimizing the formation process and enhancing product quality.
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Open AccessArticle
Analysis of Scalable Resonant DC–DC Converter Using GaN Switches for xEV Charging Stations
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Rajanand Patnaik Narasipuram, Subbarao Mopidevi, Anton Dianov and Amit Singh Tandon
World Electr. Veh. J. 2024, 15(5), 218; https://doi.org/10.3390/wevj15050218 - 17 May 2024
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In this research, an innovative electric vehicle (EV) charger is designed and presented for xEV charging stations. The key feature of our system is a scalable, interleaved inductor–inductor–capacitor (iL2C) DC-DC converter operation. The proposed system employs two parallel L2C
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In this research, an innovative electric vehicle (EV) charger is designed and presented for xEV charging stations. The key feature of our system is a scalable, interleaved inductor–inductor–capacitor (iL2C) DC-DC converter operation. The proposed system employs two parallel L2C converters with 8-GaN switches on the primary side and a shared rectifier circuit on the secondary side. This configuration not only amplifies the resonant tank internal currents and losses generated by the switches but also improves current sharing. A novel closed-loop technique is proposed with a constant-voltage method of operation, along with a hybrid control scheme of variable frequency + phase shift modulation (VFPSM). To examine the controller and converter’s performance, an experimental demonstration is conducted under varying load conditions, including full load, half load, and light load, where the source voltage and load voltage are maintained at constant levels of 400 Vin and 48 V0, respectively. Furthermore, line regulation is conducted and verified to accommodate a broad input voltage range of 300 Vin–500 Vin and 500 Vin–300 Vin while maintaining an output voltage of 48 V0 at 3.3 kW, 1.65 kW, and 0.33 kW with a peak efficiency of 98.2%.
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Open AccessArticle
Estimation of Soil Characteristic Parameters for Electric Mountain Tractor Based on Gauss–Newton Iteration Method
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Zhiqiang Xi, Tian Feng, Zhijun Liu, Huaijun Xu, Jingyang Zheng and Liyou Xu
World Electr. Veh. J. 2024, 15(5), 217; https://doi.org/10.3390/wevj15050217 - 15 May 2024
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Future field work tasks will require mountain tractors to pass through rough terrain with limited human supervision. The wheel–soil interaction plays a critical role in rugged terrain mobility. In this paper, an algorithm for the estimation of soil characteristic parameters based on the
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Future field work tasks will require mountain tractors to pass through rough terrain with limited human supervision. The wheel–soil interaction plays a critical role in rugged terrain mobility. In this paper, an algorithm for the estimation of soil characteristic parameters based on the Simpson numerical integration method and Gauss–Newton iteration method is presented. These parameters can be used for passability prediction or in a traction control algorithm to improve tractor mobility and to plan safe operation paths for autonomous navigation systems. To verify the effectiveness of the solving algorithm, different initial values and soils were selected for simulation calculations of soil characteristic parameters such as internal friction angle, settlement index, and the joint parameter of soil cohesion modulus and friction modulus. The results show that the error was kept within 2%, and the calculation time did not exceed 0.84 s, demonstrating high robustness and real-time performance. To test the applicability of the algorithm model, further research was conducted using different wheel parameters of electric mountain tractors under wet clay conditions. The results show that these parameters also have high accuracy and stability with only a few iterations. Thus, the estimation algorithm can meet the requirements of quickly and accurately identifying soil characteristic parameters during tractor operation. A criterion for the passability of wheeled tractors through unknown terrain is proposed, utilizing identified soil parameters.
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Open AccessArticle
On the Aggregation and Monetization of Flexible Loads in the Context of EV Fleets
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Kelaja Schert, Florian Biedenbach, Thomas Müller, Michael Kluge and Zoltán Nochta
World Electr. Veh. J. 2024, 15(5), 216; https://doi.org/10.3390/wevj15050216 - 14 May 2024
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In this paper, we present an approach to the price-optimized charging of electric vehicles (EVs) based on energy flexibility. Fleet operators determine the minimum and the maximum power demand to charge EVs at a specific time and share this information as so-called power
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In this paper, we present an approach to the price-optimized charging of electric vehicles (EVs) based on energy flexibility. Fleet operators determine the minimum and the maximum power demand to charge EVs at a specific time and share this information as so-called power corridors (PCs) with an energy aggregator. The energy aggregator collects the predicted PCs from the fleet operators located in the same market area and aggregates the PCs. The energy provider periodically sends energy prices from the market to the energy aggregator, which purchases energy when its price is opportune. The energy aggregator calculates and delivers charge plans for each fleet operator involved and thus can pass along the purchase prices. The incentive design must ensure that fleet operators are better off by disclosing their flexibility data to the aggregator. This study can contribute to a new data-driven energy market communication system by providing insights on how to leverage the energy flexibility that EVs can offer to the energy system.
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(This article belongs to the Special Issue EVS36—International Electric Vehicle Symposium and Exhibition (California, USA))
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Open AccessReview
Related Work and Motivation for Electric Vehicle Solar/Wind Charging Stations: A Review
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Radwan A. Almasri, Talal Alharbi, M. S. Alshitawi, Omar Alrumayh and Salman Ajib
World Electr. Veh. J. 2024, 15(5), 215; https://doi.org/10.3390/wevj15050215 - 13 May 2024
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The shift towards sustainable transportation is an urgent worldwide issue, leading to the investigation of creative methods to decrease the environmental effects of traditional vehicles. Electric vehicles (EVs) are a promising alternative, but the issue lies in establishing efficient and environmentally friendly charging
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The shift towards sustainable transportation is an urgent worldwide issue, leading to the investigation of creative methods to decrease the environmental effects of traditional vehicles. Electric vehicles (EVs) are a promising alternative, but the issue lies in establishing efficient and environmentally friendly charging infrastructure. This review explores the existing research on the subject of photovoltaic-powered electric vehicle charging stations (EVCSs). Our analysis highlights the potential for economic growth and the creation of robust and decentralized energy systems by increasing the number of EVCSs. This review summarizes the current knowledge in this field and highlights the key factors driving efforts to expand the use of PV-powered EVCSs. The findings indicate that MATLAB was predominantly used for theoretical studies, with projects focusing on shading parking lots. The energy usage varied from 0.139 to 0.295 kWh/km, while the cost of energy ranged from USD 0.0032 to 0.5645 per kWh for an on-grid system. The payback period (PBP) values are suitable for this application. The average PBP was demonstrated to range from 1 to 15 years. The findings from this assessment can guide policymakers, researchers, and industry stakeholders in shaping future advancements toward a cleaner and more sustainable transportation system.
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(This article belongs to the Special Issue Electric Vehicles and Charging Facilities for a Sustainable Transport Sector)
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Open AccessArticle
Efficiency Analysis of Hybrid Extreme Regenerative with Supercapacitor Battery and Harvesting Vibration Absorber System for Electric Vehicles Driven by Permanent Magnet Synchronous Motor 30 kW
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Pataphiphat Techalimsakul and Pakornkiat Sawetmethikul
World Electr. Veh. J. 2024, 15(5), 214; https://doi.org/10.3390/wevj15050214 - 12 May 2024
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This research presents an approach to the hybrid energy harvesting paradigm (HEHP) based on suspended energy harvest. It uses a harvesting vibration absorber (HVA) with an SC/NMC-lithium battery hybrid energy storage paradigm (SCB-HESP) equipped regenerative braking system (SCB-HESP-RBS) for electric vehicles 2 tons
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This research presents an approach to the hybrid energy harvesting paradigm (HEHP) based on suspended energy harvest. It uses a harvesting vibration absorber (HVA) with an SC/NMC-lithium battery hybrid energy storage paradigm (SCB-HESP) equipped regenerative braking system (SCB-HESP-RBS) for electric vehicles 2 tons in gross weight (MEVs) driven by a 30 kW permanent magnet synchronous motor (PMSM). During regenerative braking, the ANN mechanism controls the RBS to adjust the switching waveform of the three-phase power inverter, and the braking energy transfers to the energy storage device. Additionally, a supercapacitor (SC) equipped with HVA can absorb energy from vehicle vibrations and convert it into electrical energy. The energy-harvesting efficiency of MEV based on SCB-HESP-RBS using HVA suspended energy harvesting enhances the efficiency maximum to 50.58% and 15.36% in comparison to MEV with only-HVA and SCB-HESP-RBS, respectively. Further, the MEV with SCB-HESP-RBS using HVA has a driving distance of up to 247.34 km (22.5 cycles) when compared with SCB-HESP-RBS (214.40 km, 19.5 cycles) and only-HVA (164.25 km, 15 cycles).
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(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)
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Open AccessArticle
Multi-Strategical Thermal Management Approach for Lithium-Ion Batteries: Combining Forced Convection, Mist Cooling, Air Flow Improvisers and Additives
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Anikrishnan Mohanan and Kannan Chidambaram
World Electr. Veh. J. 2024, 15(5), 213; https://doi.org/10.3390/wevj15050213 - 11 May 2024
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Maintaining the peak temperature of a battery within limits is a mandate for the safer operation of electric vehicles. In two-wheeler electric vehicles, the options available for the battery thermal management system are minuscule due to the restrictions imposed by factors like weight,
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Maintaining the peak temperature of a battery within limits is a mandate for the safer operation of electric vehicles. In two-wheeler electric vehicles, the options available for the battery thermal management system are minuscule due to the restrictions imposed by factors like weight, cost, availability, performance, and load. In this study, a multi-strategical cooling approach of forced convection and mist cooling over a single-cell 21,700 lithium-ion battery working under the condition of 4C is proposed. The chosen levels for air velocities (10, 15, 20 and 25 m/s) imitate real-world riding conditions, and for mist cooling implementation, injection pressure with three levels (3, 7 and 14 bar) is considered. The ANSYS fluent simulation is carried out using the volume of fluid in the discrete phase modelling transition using water mist as a working fluid. Initial breakup is considered for more accurate calculations. The battery’s state of health (SOH) is determined using PYTHON by adopting the Newton–Raphson estimation. The maximum temperature reduction potential by employing an airflow improviser (AFI) and additives (Tween 80, 1-heptanol, APG0810, Tween 20 and FS3100) is also explored. The simulation results revealed that an additional reduction of about 11% was possible by incorporating additives and AFI in the multi-strategical approach. The corresponding SOH improvement was about 2%. When the electric two-wheeler operated under 4C, the optimal condition (Max. SOH and Min. peak cell temp.) was achieved at an air velocity of 25 m/s, injection pressure of 7 bar with AFI and 3% (by wt.) Tween 80 and a 0.1% deformer.
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(This article belongs to the Special Issue Thermal Management System for Battery Electric Vehicle)
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Open AccessArticle
Medium- and Long-Term Electric Vehicle Ownership Forecasting for Urban Residents
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Zhao-Xia Xiao, Jiang-Wei Jia, Xiang-Yu Liu, Hong-Kun Bai, Qiu-Yan Li and Yuan-Peng Hua
World Electr. Veh. J. 2024, 15(5), 212; https://doi.org/10.3390/wevj15050212 - 10 May 2024
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With the rapid development of electric vehicles (EVs) in Chinese cities, accurately forecasting the number of EVs used by urban residents in the next five years and more long term is beneficial for the government to adjust industrial policies of EVs, guide the
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With the rapid development of electric vehicles (EVs) in Chinese cities, accurately forecasting the number of EVs used by urban residents in the next five years and more long term is beneficial for the government to adjust industrial policies of EVs, guide the rational planning of urban charging facilities and supporting distribution network, and achieve the rational and orderly development of the EV industry. The paper considers the advantages of using the grey GM(1,1) prediction model to predict the short-term ownership of EVs by urban residents. Then, by forecasting the number of EV users in a certain city in the future and predicting the number of private vehicles in the future, the boundary conditions for long-term year ownership of EVs by residents are determined. Combined with historical data and short-term forecast data generated by the grey prediction model, the model parameters that include the innovation coefficient and imitation coefficient of the Bass model are trained using a genetic algorithm. Finally, the Bass model is used for medium- to long-term ownership forecasting from 2023 to 2040. The prediction error for the target year is provided. The simulation results indicate that the ownership of resident EVs in this city will experience rapid growth in the next five years.
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Open AccessArticle
Driving Profiles of Light Commercial Vehicles of Craftsmen and the Potential of Battery Electric Vehicles When Charging on Company Premises
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Oliver Heilmann, Britta Bocho, Alexander Frieß, Sven Cortès, Ulrich Schrade, André Casal Kulzer and Michael Schlick
World Electr. Veh. J. 2024, 15(5), 211; https://doi.org/10.3390/wevj15050211 - 10 May 2024
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This paper examines the extent to which it is possible to replace conventional light commercial vehicles in the heating, ventilation and air conditioning and plumbing trade with battery electric vehicles with an unchanged usage profile. GPS trackers are used to record the position
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This paper examines the extent to which it is possible to replace conventional light commercial vehicles in the heating, ventilation and air conditioning and plumbing trade with battery electric vehicles with an unchanged usage profile. GPS trackers are used to record the position data of 22 craft vehicles with combustion engines from eleven companies over the duration of one working week. Within this paper, various assumptions (battery capacity and average consumption) are made for battery electric vehicles and the charging power on the company premises. The potential of battery electric vehicles is evaluated based on the assumption that they are charged only on company premises. Using the collected data and the assumptions made, theoretical state of charge curves are calculated for the vehicles. The driving profiles of the individual vehicles differ greatly, and the suitability of battery electric vehicles should be considered individually. Battery capacity, vehicle energy consumption and charging power at the company have a substantial influence on the suitability of battery electric vehicles. Furthermore, there are differences between vehicles that can charge on the company premises at night and those that cannot or can only do so on some days.
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Open AccessArticle
A Multi-Sensor 3D Detection Method for Small Objects
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Yuekun Zhao, Suyun Luo, Xiaoci Huang and Dan Wei
World Electr. Veh. J. 2024, 15(5), 210; https://doi.org/10.3390/wevj15050210 - 10 May 2024
Abstract
In response to the limited accuracy of current three-dimensional (3D) object detection algorithms for small objects, this paper presents a multi-sensor 3D small object detection method based on LiDAR and a camera. Firstly, the LiDAR point cloud is projected onto the image plane
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In response to the limited accuracy of current three-dimensional (3D) object detection algorithms for small objects, this paper presents a multi-sensor 3D small object detection method based on LiDAR and a camera. Firstly, the LiDAR point cloud is projected onto the image plane to obtain a depth image. Subsequently, we propose a cascaded image fusion module comprising multi-level pooling layers and multi-level convolution layers. This module extracts features from both the camera image and the depth image, addressing the issue of insufficient depth information in the image feature. Considering the non-uniform distribution characteristics of the LiDAR point cloud, we introduce a multi-scale voxel fusion module composed of three sets of VFE (voxel feature encoder) layers. This module partitions the point cloud into grids of different sizes to improve detection ability for small objects. Finally, the multi-level fused point features are associated with the corresponding scale’s initial voxel features to obtain the fused multi-scale voxel features, and the final detection results are obtained based on this feature. To evaluate the effectiveness of this method, experiments are conducted on the KITTI dataset, achieving a 3D AP (average precision) of 73.81% for the hard level of cars and 48.03% for the hard level of persons. The experimental results demonstrate that this method can effectively achieve 3D detection of small objects.
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(This article belongs to the Special Issue Deep Learning Applications for Electric Vehicles)
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Open AccessArticle
Hardware Implementation of a Resilient Energy Management System for Networked Microgrids
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Hossam M. Hussein, S M Sajjad Hossain Rafin, Mahmoud S. Abdelrahman and Osama A. Mohammed
World Electr. Veh. J. 2024, 15(5), 209; https://doi.org/10.3390/wevj15050209 - 10 May 2024
Abstract
A networked microgrid is composed of multiple nearby microgrids linked together to gain additional flexibility for resilient operations. Networked microgrids collaborate to prevent power shortages in microgrid clusters by sharing critical renewable and energy storage resources. However, controlling the local resources of each
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A networked microgrid is composed of multiple nearby microgrids linked together to gain additional flexibility for resilient operations. Networked microgrids collaborate to prevent power shortages in microgrid clusters by sharing critical renewable and energy storage resources. However, controlling the local resources of each microgrid, including the energy storage systems’ charging and discharging, maintaining the DC bus voltage, and even overseeing the power shared by multiple microgrids, is challenging. Therefore, a microgrid control technique and distributed energy management are used cooperatively in this study to handle the shared power between a system of networked microgrids incorporating photovoltaics and battery energy storage systems. Numerical simulation results from a networked microgrid system verify the accuracy and soundness of the suggested distributed energy management under several operating conditions, including renewable uncertainties and sequential load variations in different zones. The applicability of the suggested technique is confirmed by hardware implementation, and several operational scenarios further evaluate the proposed system on a practical two-microgrid system located in the Florida International University (FIU) testbed.
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(This article belongs to the Special Issue Power and Energy Systems for E-mobility)
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Open AccessReview
Application of Digital Twin in Electric Vehicle Powertrain: A Review
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Xiaokang Li, Wenxu Niu and Haobin Tian
World Electr. Veh. J. 2024, 15(5), 208; https://doi.org/10.3390/wevj15050208 - 10 May 2024
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Digital Twin (DT) is widely regarded as a highly promising technology with the potential to revolutionize various industries, making it a key trend in the Industry 4.0 era. In a cost-effective and risk-free setting, digital twins facilitate the interaction and merging of the
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Digital Twin (DT) is widely regarded as a highly promising technology with the potential to revolutionize various industries, making it a key trend in the Industry 4.0 era. In a cost-effective and risk-free setting, digital twins facilitate the interaction and merging of the physical and informational realms. The application of digital twins spans across different sectors, including aerospace, healthcare, smart manufacturing, and smart cities. As electric vehicles have experienced rapid growth, there is a growing demand for the development of innovative technologies. One potential area for digital twins application is within the automotive sector. The powertrain system of electric vehicles (EVs) consists of three parts, power source, power electronic system, and electric motor, which are considered as the core components of electric vehicles. The focus of this paper is to conduct a methodical review regarding the use of digital twins in the powertrain of electric vehicles (EVs). While reviewing the development of digital twin technology, its main application scenarios and its use in electric vehicle powertrains are analysed. Finally, the digital twins currently encounter several challenges that need to be addressed, and so the future development of their application to electric vehicles are summarized.
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Open AccessArticle
Suppression of Initial Charging Torque for Electric Drive-Reconfigured On-Board Charger
by
Yang Xiao, Kangwei Wang, Zhi Geng, Kai Ni, Mingdi Fan and Yong Yang
World Electr. Veh. J. 2024, 15(5), 207; https://doi.org/10.3390/wevj15050207 - 9 May 2024
Abstract
This paper presents a new electric drive-reconfigured on-board charger and initial electromagnetic torque suppression method. This proposed reconfigured on-board charger does not need many components added to the original electric drive system: only a connector is needed, which is easy to add. Specifically,
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This paper presents a new electric drive-reconfigured on-board charger and initial electromagnetic torque suppression method. This proposed reconfigured on-board charger does not need many components added to the original electric drive system: only a connector is needed, which is easy to add. Specifically, the inverter for propulsion is reconfigured as a buck chopper and a conduction path to match the reconfigured windings. Two of the machine phase windings serve as inductors, while the third phase winding is reutilized as a common-mode inductor. In addition, the initial charging torque is generated at the outset of the charging process, which may cause an instant shock or even rotational movement. In order to prevent vehicle movement, the reason for the charging torque and suppression method were analyzed. Further, predictive control of the model based on mutual inductance analysis was adopted, where the charging torque was directly used as a control object in the cost function. Finally, experimental performances were applied to verify the proposed reconfigured on-board charger under constant current and constant voltage charging.
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(This article belongs to the Special Issue Emerging Topologies and Control of Electric-Drive-Reconstructed Onboard Charger for Electric Vehicles)
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Open AccessArticle
Modeling an Investment Framework for BMTA Electric Bus Fleet Development
by
Sorawit Wanitanukul, Kuskana Kubaha and Roongrojana Songprakorp
World Electr. Veh. J. 2024, 15(5), 206; https://doi.org/10.3390/wevj15050206 - 9 May 2024
Abstract
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In Thailand, diesel buses are notorious for their poor energy efficiency and contribution to air pollution. To combat these issues, battery electric buses (BEBs) have emerged as a promising alternative. However, their high initial costs have posed challenges for fleet management, especially for
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In Thailand, diesel buses are notorious for their poor energy efficiency and contribution to air pollution. To combat these issues, battery electric buses (BEBs) have emerged as a promising alternative. However, their high initial costs have posed challenges for fleet management, especially for agencies such as the Bangkok Mass Transit Authority (BMTA). This study aims to revolutionize BEB fleet management by developing an energy model tailored to the BMTA’s needs. The methodology consists of two crucial steps: analyzing BMTA bus routes and designing fleet management and charging systems. Through this process, the study seeks to determine the maximum number of BEBs that can be operated on each route with the fewest chargers possible. The results reveal exciting possibilities. Within the city bus landscape, two out of five BMTA bus routes show potential for transitioning to BEBs, provided they meet a maximum energy requirement of 200 kWh every two rounds. This analysis identifies routes ripe for BEB adoption while considering the limitations of battery size. In the next step, the study unveils a game-changing strategy: a maximum of 13 BEBs can operate on two routes with just four chargers requiring 150 kW each. This means fewer chargers and more efficient operations. Plus, the charging profile peaks at 600 kW from 4:00 to 8:00 p.m., showing when and where the fleet needs power the most. However, the real eye-opener? Significant energy savings of THB 10.44 million per year compared to diesel buses, with an initial investment cost savings of over 37%. These findings underscore the potential for BEB fleet management to revolutionize public transportation and save money in the long run. However, there is more work to be done. The study highlights the need for real-time passenger considerations, the development of post-service charging strategies, and a deeper dive into total lifetime costs. These areas of improvement promise even greater strides in the future of sustainable urban transportation.
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