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Carbon-Aware Rolling-Horizon Energy Management of Electric Vehicles via Virtual Power Plants Under Carbon–Grid Conflict
Comparative Analysis of Slow Charging, Fast Charging, and Battery Swapping in Electric Truck Logistics: A Harbor Transport Case
Charging Strategies for Battery Electric Trucks in Germany
Solar Charging—Lessons Learned from Field Observation

Journal Description

World Electric Vehicle Journal

World Electric Vehicle Journal (WEVJ) is the first international, peer-reviewed, open access journal that comprehensively covers all studies related to battery, hybrid, and fuel cell electric vehicles, published monthly online. It is the official journal of the World Electric Vehicle Association (WEVA) and its members, the E-Mobility Europe, Electric Drive Transportation Association (EDTA), and Electric Vehicle Association of Asia Pacific (EVAAP).

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: JCR - Q2 (Engineering, Electrical and Electronic) / CiteScore - Q1 (Automotive Engineering)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 21 days after submission; acceptance to publication is undertaken in 3.8 days (median values for papers published in this journal in the second half of 2025).
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: 3.3 (2025); 5-Year Impact Factor: 3.3 (2025)

Imprint Information Journal Flyer Open Access ISSN: 2032-6653

Latest Articles

24 pages, 12904 KB

Open AccessArticle

Load Torque Feedforward and Dynamic Limiting Control Strategy for Electric Forklift Steering Systems Considering Voltage-Limit Constraints

by Fangbin Wang, Qufei Wu, Jiawei Ji and Xue Gong

World Electr. Veh. J. 2026, 17(6), 323; https://doi.org/10.3390/wevj17060323 (registering DOI) - 22 Jun 2026

For low-speed heavy-load steering of electric forklifts, conventional three-loop proportional–integral (PI) control employs a fixed saturation limit on the position-loop output. Consequently, the maximum allowable speed cannot be adjusted according to load variations. Under light-load conditions, the steering motor speed is excessively constrained, [...] Read more.

For low-speed heavy-load steering of electric forklifts, conventional three-loop proportional–integral (PI) control employs a fixed saturation limit on the position-loop output. Consequently, the maximum allowable speed cannot be adjusted according to load variations. Under light-load conditions, the steering motor speed is excessively constrained, which wastes the available voltage margin. Under heavy-load conditions, the allowable speed may exceed the voltage limit, thereby causing voltage saturation. Moreover, load-torque feedforward compensation is commonly adopted to improve load-carrying capability. However, at medium and high speeds, excessive feedforward action may cause voltage saturation and current-vector offset. This can lead to loss of control of the steering motor. To address these issues, a voltage-limit-constrained dynamic saturation and load-torque feedforward control strategy is proposed for electric forklift steering systems. First, fuzzy PI control is adopted in the position loop. Then, considering the nearly identical direct-axis and quadrature-axis inductances of a surface-mounted permanent magnet synchronous motor (PMSM), the direct-axis current is set to zero. An analytical expression of the maximum safe speed is derived with the quadrature-axis current as the only independent variable. Based on this expression, a dynamic saturation limit is designed for the position-loop output. Finally, a reduced-order disturbance observer (DOB) is utilized to estimate the equivalent load torque in real time. The current feedforward gain is dynamically regulated according to the voltage margin. This compensates for torque limitation caused by speed-loop saturation while preventing voltage saturation. A Simulink simulation platform is developed using a forklift as the case study. The results demonstrate that, compared with the conventional three-loop PI controller, the proposed strategy reduces the no-load 180° step-response time by 30%. Under heavy-load and large-angle steering conditions, the voltage margin is maintained at approximately 10%. Full article

(This article belongs to the Section Vehicle Control and Management)

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28 pages, 18529 KB

Open AccessArticle

Enhancing Voltage Stability in PV-Rich Power Systems Using GA-Optimized FOPID Control of Electric Vehicle Aggregators

by Mlungisi Ntombela

World Electr. Veh. J. 2026, 17(6), 322; https://doi.org/10.3390/wevj17060322 (registering DOI) - 22 Jun 2026

Photovoltaic (PV) generation and electric vehicle (EV) charging infrastructure are changing the dynamic behavior of current power systems, especially in terms of voltage stability and LVRT capabilities. In this work, 50% PV penetration on a modified Kundur two-area power system was tested to [...] Read more.

Photovoltaic (PV) generation and electric vehicle (EV) charging infrastructure are changing the dynamic behavior of current power systems, especially in terms of voltage stability and LVRT capabilities. In this work, 50% PV penetration on a modified Kundur two-area power system was tested to mitigate transient instability under severe fault circumstances. With PV units running at unity power factors under steady-state conditions, 50% PV penetration was defined relative to the system’s total active load demand. A steady-state power-flow study ensured generation–load balance before MATLAB/Simulink dynamic simulations. Controllable reactive power compensation was used as an EV aggregator on Bus 7. We constructed and evaluated a genetic algorithm (GA)-optimized fractional-order proportional–integral–derivative (FOPID) controller with a traditional PID controller utilizing identical optimization conditions. An inter-area tie-line critical three-phase fault was applied and removed after 100 ms to evaluate system performance. While the GA-PID controller increased transient performance, it did not restore system stability. Instead, the GA-FOPID controller provided superior dynamic support by restoring Bus 7 voltage to 0.9–1.1 pu within 250 ms after fault clearance and maintaining about 95% LVRT compliance. The suggested controller also reduced rotor angle oscillations and enhanced inter-area damping. Fractional-order control increased EV aggregators’ reactive power response during transient shocks. Thus, in renewable-energy-dominated power systems, the GA-FOPID-controlled EV support technique may improve voltage stability and LVRT compliance. Full article

(This article belongs to the Section Vehicle Control and Management)

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34 pages, 3461 KB

Open AccessReview

Challenges of Electric Vehicle Integration into the South African Power Grid

by Mlungisi Ntombela

World Electr. Veh. J. 2026, 17(6), 321; https://doi.org/10.3390/wevj17060321 (registering DOI) - 22 Jun 2026

The worldwide shift to electric mobility has intensified in recent years owing to heightened apprehensions over greenhouse gas emissions, energy security, and the necessity for sustainable transportation systems. Electric vehicles (EVs) are acknowledged as a viable alternative for diminishing reliance on fossil fuels [...] Read more.

The worldwide shift to electric mobility has intensified in recent years owing to heightened apprehensions over greenhouse gas emissions, energy security, and the necessity for sustainable transportation systems. Electric vehicles (EVs) are acknowledged as a viable alternative for diminishing reliance on fossil fuels and enhancing energy efficiency in the transportation sector. While affluent nations have achieved considerable advancements in electric vehicle adoption and charging infrastructure, numerous developing countries still encounter significant technical and infrastructural obstacles that hinder extensive EV integration. In South Africa, these difficulties are exacerbated by ongoing electrical supply limitations, deteriorating transmission and distribution facilities, and recurrent load shedding, which heighten worries about the dependability and stability of the national power grid. The rising adoption of electric vehicles adds extra electrical demands to power systems, especially at the distribution network level, where most of the charging takes place. Disorganized EV charging can substantially modify current load patterns, leading to heightened peak demand, voltage variations, transformer overload, and network congestion. The technical consequences are especially significant in South Africa, where the power grid functions with constricted generation capacity and minimal reserve margins. Various mitigating measures have been suggested to tackle these difficulties, including intelligent charging, demand-side management, time-of-use pricing, and vehicle-to-grid technologies. This paper establishes a basic theoretical framework through an extensive literature review to investigate the technological problems related to electric vehicle adoption in South Africa, while assessing the environmental and economic ramifications for sustainable urban transportation systems. Full article

(This article belongs to the Section Charging Infrastructure and Grid Integration)

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26 pages, 2171 KB

Open AccessArticle

Two-Stage Orderly Charging Scheduling for Large-Scale Electric Vehicle Charging Stations via the SMPD Framework

by Boyu Wang, Yuxuan Yao, Jingjing Gao and Danchen Luo

World Electr. Veh. J. 2026, 17(6), 320; https://doi.org/10.3390/wevj17060320 (registering DOI) - 20 Jun 2026

Real-time scheduling in large-scale electric vehicle charging stations is challenged by stochastic vehicle arrivals, dynamic departures, limited charging resources, and station-level power constraints. To address this problem, this paper proposes a two-stage Supervised Service Matching and Reinforcement Power Dispatch (SMPD) framework, termed SMPD, [...] Read more.

Real-time scheduling in large-scale electric vehicle charging stations is challenged by stochastic vehicle arrivals, dynamic departures, limited charging resources, and station-level power constraints. To address this problem, this paper proposes a two-stage Supervised Service Matching and Reinforcement Power Dispatch (SMPD) framework, termed SMPD, which decomposes the original coupled scheduling problem into supervised service matching and reinforcement learning-based power dispatch. In the first stage, a supervised matching network learns EV-charger service suitability from historical charging-session records and determines service access decisions for feasible EV–charger pairs. In the second stage, a Soft Actor-Critic-based controller allocates continuous charging power to connected EVs under EV-side charging limits, charger capacity constraints, and the station-level total power constraint. The proposed framework is evaluated using public charging-session data from the ElaadNL dataset. Experimental results show that SMPD achieves lower average waiting time, higher average revenue, lower composite penalty, and comparable demand satisfaction compared with rule-based, single-stage reinforcement learning, and multi-agent baselines. Sensitivity and robustness analyses further indicate that SMPD maintains favorable scheduling performance and acceptable online decision time under the tested charger-scale settings and operational disturbance scenarios. These results suggest that the proposed two-stage design provides an effective and computationally tractable approach for real-time scheduling in large-scale EV charging stations. Full article

(This article belongs to the Section Vehicle and Transportation Systems)

25 pages, 12373 KB

Open AccessArticle

Transient Current Protection for Direct Grid-Connected Wireless Charging of Electric Vehicles

by Yuchen Wei, Wei Liu, Chang Liu and K. T. Chau

World Electr. Veh. J. 2026, 17(6), 319; https://doi.org/10.3390/wevj17060319 (registering DOI) - 20 Jun 2026

Direct grid-connected wireless charging based on direct AC–AC conversion is attractive for electric vehicles (EVs) because it can reduce power conversion stages and improve charger compactness. In matrix-converter-based wireless power transfer (WPT) systems, the grid-frequency AC voltage can be directly converted into high-frequency [...] Read more.

Direct grid-connected wireless charging based on direct AC–AC conversion is attractive for electric vehicles (EVs) because it can reduce power conversion stages and improve charger compactness. In matrix-converter-based wireless power transfer (WPT) systems, the grid-frequency AC voltage can be directly converted into high-frequency AC voltage without using bulky DC-link electrolytic capacitors. However, the removal of the intermediate energy-storage stage also makes the EV wireless charger more sensitive to grid-voltage fluctuation. For an LCC-S compensated WPT system, the voltage-source output characteristic makes the charging-side voltage sensitive to grid-voltage disturbance, resulting in severe MC output-current and battery charging-current overshoot. This transient overcurrent may threaten both the power converter and the EV battery charging process. In this paper, a dual-frequency state-space model is developed for the matrix-converter-based electrolytic-capacitor-less LCC-S WPT system to analyze the disturbance propagation from the grid side to the high-frequency resonant stage and the EV battery side. Based on the model, the current-overshoot suppression capability and bandwidth limitation of the conventional dual closed-loop control strategy are investigated. To further enhance transient current protection, a grid-voltage feedforward strategy is proposed to compensate for the disturbance before severe current overshoot is formed. Finally, experimental results verify that the proposed method effectively suppresses the MC output-current and battery charging-current overshoot under grid-voltage fluctuation, thereby improving the grid-disturbance resilience and dynamic safety of direct grid-connected EV wireless charging systems. Full article

(This article belongs to the Section Charging Infrastructure and Grid Integration)

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22 pages, 554 KB

Open AccessArticle

A Monetized Life Cycle Sustainability Assessment Framework for Integrating Environmental, Economic, and Social Impacts: Evidence from Electric Vehicles

by Sining Ma, Zhijian He, Amir Hamzah Sharaai, Yuqing Liu and Haoxuan Cai

World Electr. Veh. J. 2026, 17(6), 318; https://doi.org/10.3390/wevj17060318 (registering DOI) - 19 Jun 2026

Life Cycle Sustainability Assessment (LCSA) has been widely used to assess the environmental, economic, and social impacts of emerging technologies. However, its practical application in decision support remains limited due to incompatibility of units of measurement among sustainability dimensions and a lack of [...] Read more.

Life Cycle Sustainability Assessment (LCSA) has been widely used to assess the environmental, economic, and social impacts of emerging technologies. However, its practical application in decision support remains limited due to incompatibility of units of measurement among sustainability dimensions and a lack of transparent integration mechanisms. This study constructs a monetized LCSA framework to examine how battery electric vehicles (BEVs) replacing gas-powered vehicles (GVs) in cold regions covered by carbon-intensive power systems affects overall sustainability performance. The results show that over a 15-year lifespan, BEVs reduce life cycle costs by 28.74% and carbon-related environmental costs by 25.27% compared to GVs, demonstrating significant economic and environmental advantages. However, BEVs show a 4.23% decrease in standardized socially perceived performance, primarily due to consumer concerns about transparency, privacy, and end-of-life liability. These findings suggest that incorporating social dimensions can significantly alter sustainability conclusions and reveal trade-offs that traditional single-dimensional assessments cannot capture. This study provides new empirical evidence for the comprehensive application of monetized life cycle sustainability assessment and offers valuable insights for vehicle design improvements, increased social acceptance, and low-carbon transportation policies in cold and carbon-intensive regions. Full article

(This article belongs to the Section Marketing, Promotion and Socio Economics)

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29 pages, 14852 KB

Open AccessArticle

Research on Energy-Saving Control Strategies for Multi-Axis Distributed Heavy-Duty Mining Trucks

by Bin Huang, Jinyu Wei, Lianbing Suo, Guochao Zhang and Guanlun Guo

World Electr. Veh. J. 2026, 17(6), 317; https://doi.org/10.3390/wevj17060317 (registering DOI) - 19 Jun 2026

Considering that conventional heavy-duty mining trucks equipped with centralized drive systems suffer from low transmission efficiency and limited flexibility in power distribution, this study focuses on distributed independent-drive heavy-duty mining trucks and develops energy-saving control strategies from two perspectives: drive torque control and [...] Read more.

Considering that conventional heavy-duty mining trucks equipped with centralized drive systems suffer from low transmission efficiency and limited flexibility in power distribution, this study focuses on distributed independent-drive heavy-duty mining trucks and develops energy-saving control strategies from two perspectives: drive torque control and regenerative braking. For the drive torque control, based on the principle of optimal driving efficiency, the overall efficiency of the drive motors is selected as the objective function, and an adaptive genetic algorithm (AGA) is employed to optimize the torque distribution coefficients among the axles offline. For regenerative braking, a fuzzy-control-based electromechanical braking distribution strategy and a dynamic-load-based inter-axle braking force allocation strategy are proposed. Finally, a co-simulation was conducted using MATLAB/Simulink and TruckSim based on specific open-pit mining conditions. Compared with the conventional baseline without energy-saving control, the simulation results demonstrate that under the single-cycle operation, the proposed strategy increases the driving energy utilization rate by 5.69% and achieves a braking energy recovery rate of 39.41%. Furthermore, under the full-mine cyclic operation, the proposed strategy extends the vehicle’s operational duration on a single charge by 200%. These findings demonstrate the strong potential of the proposed strategy to improve overall driving efficiency and fully exploit the regenerative braking capabilities of heavy-duty mining trucks, thereby providing theoretical support for enhancing their economic efficiency and driving range. Full article

(This article belongs to the Collection Feature Papers in Propulsion Systems and Components in Electric Vehicle)

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44 pages, 2906 KB

Open AccessReview

A Review of the Thermal Management System of Lithium-Ion Batteries in Electric Vehicles According to the Classification of Phase Change Materials

by Juan Serrano-Arellano, Gabriela Y. Ortiz-Lagunas, Juan M. Belman-Flores, Karla M. Aguilar-Castro, Francisco N. Demesa-López, Abisai J. Reséndiz-Barrón, Miguel A. Gómez-Martínez and Jesús A. Moctezuma-Hernández

World Electr. Veh. J. 2026, 17(6), 316; https://doi.org/10.3390/wevj17060316 (registering DOI) - 18 Jun 2026

Thermal regulation of lithium-ion (Li-ion) battery modules is a critical constraint for electric vehicle (EV) safety and durability, particularly during high-C-rate operation. Phase change materials (PCMs) have emerged as promising passive solutions due to their latent heat storage capability; however, current literature is [...] Read more.

Thermal regulation of lithium-ion (Li-ion) battery modules is a critical constraint for electric vehicle (EV) safety and durability, particularly during high-C-rate operation. Phase change materials (PCMs) have emerged as promising passive solutions due to their latent heat storage capability; however, current literature is heavily biased toward organic paraffin-based systems and lacks structured benchmarking across PCM categories and integration architectures. This review provides a systematic comparative assessment of PCM-based battery thermal management systems (BTMSs) comprising organic, inorganic, and eutectic materials under EV-relevant discharge conditions. The review is structured according to the conventional classification of PCMs; however, the available literature is predominantly focused on organic materials, particularly paraffin-based PCMs, leading to greater depth of analysis for this category. Thermophysical properties are analyzed in conjunction with discharge rate, module configuration, and hybrid cooling strategies. The results indicate that peak temperature mitigation is weakly correlated with latent heat magnitude when thermal conductivity remains below critical values. Conductivity-enhanced composites incorporating expanded graphite or metal foams significantly improve heat diffusion, reducing hotspot intensity and inter-cell temperature gradients under medium-to-high C-rates. Pure passive PCM systems exhibit thermodynamic limitations during sustained high-power operation due to saturation effects, underscoring the need for hybrid architectures for continuous heat rejection. This work establishes a structured benchmarking framework and demonstrates that effective thermal conductivity, integration strategy, and discharge-dependent design dominate BTMS performance over latent heat alone. The findings also reveal that inorganic and eutectic PCM-based BTMSs remain comparatively less explored in the literature, particularly at the battery module level and under realistic electric vehicle operating conditions, highlighting opportunities for future research. Full article

(This article belongs to the Section Storage Systems)

28 pages, 2265 KB

Open AccessArticle

Architectural Pathways and Integration Constraints for Feasible Onboard Electrochemical Impedance Spectroscopy for Battery Electric Vehicles

by Roger Bautista-Florensa, Daniel Montesinos-Miracle, Alberto Gómez-Núñez and Carlos Abomailek

World Electr. Veh. J. 2026, 17(6), 315; https://doi.org/10.3390/wevj17060315 (registering DOI) - 18 Jun 2026

Reliable battery health assessment is essential to accelerate battery electric vehicle (BEV) adoption, yet most existing in-vehicle methods do not capture the complex processes driving ageing. Electrochemical impedance spectroscopy (EIS) offers deeper diagnostic insight but faces significant architectural and integration constraints. This study [...] Read more.

Reliable battery health assessment is essential to accelerate battery electric vehicle (BEV) adoption, yet most existing in-vehicle methods do not capture the complex processes driving ageing. Electrochemical impedance spectroscopy (EIS) offers deeper diagnostic insight but faces significant architectural and integration constraints. This study establishes a rigorous system-level framework for practicable onboard EIS implementation, focusing on the integration within Battery Management System (BMS) and powertrain architectures. Various integration topologies for cell-, module- and pack-level EIS are evaluated, highlighting their key trade-offs. The viability of the presented architectures is assessed through an application-specific Multi-Criteria Decision Analysis (MCDA) for mass-market, high-performance and circular economy use-cases. This study confirms the feasibility of onboard EIS while providing industry and scientific stakeholders with practical guidance to advance battery diagnostics for next-generation BEVs. Full article

(This article belongs to the Special Issue EVS38—International Electric Vehicle Symposium and Exhibition (Gothenburg, Sweden))

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27 pages, 17972 KB

Open AccessArticle

Low-Cost Instrumentation for Energy-Based Assessment of Electric Vehicles Under High-Altitude and High-Gradient Real-World Driving Conditions

by David Sebastian Puma-Benavides, Bolivar Alejandro Cuaical-Angulo, Alex Santiago Cevallos-Carvajal, Guillermo Mauricio Cruz-Arcos, Edilberto Antonio Llanes-Cedeño and Pablo Javier Guagalango-Gómez

World Electr. Veh. J. 2026, 17(6), 314; https://doi.org/10.3390/wevj17060314 (registering DOI) - 18 Jun 2026

This study presents an energy-based assessment of a battery electric sport utility vehicle (SUV) tested under high-altitude and high-gradient real-world conditions in Ambato, Ecuador, at approximately 2500 m above sea level. A low-cost instrumentation setup composed of a Global Navigation Satellite System (GNSS) [...] Read more.

This study presents an energy-based assessment of a battery electric sport utility vehicle (SUV) tested under high-altitude and high-gradient real-world conditions in Ambato, Ecuador, at approximately 2500 m above sea level. A low-cost instrumentation setup composed of a Global Navigation Satellite System (GNSS) device, a Fluke 393 FC clamp meter, and an On-Board Diagnostics II (OBD-II) interface was used to evaluate zero, positive, and negative road-gradient conditions in Normal and Sport driving modes. The results show that positive gradients increased the acceleration energy from 0.0454 to 0.0658 kWh in Normal mode and from 0.0351 to 0.0535 kWh in Sport mode. In contrast, negative gradients favored regenerative braking, with Normal mode reaching a net energy balance of

- 0.0249

kWh and a segment-level recovery ratio of 194.38%. This value reflects the contribution of gravitational potential energy. Sport mode showed lower regenerative performance, particularly during uphill operation, where the recovery ratio decreased to 8.96%. These findings demonstrate that low-cost instrumentation can capture representative route-level energy trends and support real-world electric vehicle (EV) energy assessment in topographically complex high-altitude environments. Full article

(This article belongs to the Section Energy Supply and Sustainability)

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27 pages, 5742 KB

Open AccessArticle

Spatiotemporal Assessment of Solar Powered EV Charging Infrastructure: A Case Study of Kampala-Wakiso Area in Uganda

by Jane Namaganda-Kiyimba, Jade Kinobe Ssewagudde, Roy Muhangi, Esther Kabajurizi, Jérémy Dumoulin, Nicolas Wyrsch and Jonathan Serugunda

World Electr. Veh. J. 2026, 17(6), 313; https://doi.org/10.3390/wevj17060313 - 18 Jun 2026

The rapid adoption of electric vehicles (EVs) creates a planning challenge for the Kampala-Wakiso metropolitan region in Uganda, where the electricity grid already faces local network constraints. This study applies the EVPV-Simulator, an open-source geospatial modelling framework that links mobility demand, charging demand, [...] Read more.

The rapid adoption of electric vehicles (EVs) creates a planning challenge for the Kampala-Wakiso metropolitan region in Uganda, where the electricity grid already faces local network constraints. This study applies the EVPV-Simulator, an open-source geospatial modelling framework that links mobility demand, charging demand, and EV-PV complementarity, to assess projected charging demand and solar integration potential in the Kampala-Wakiso metropolitan region. By simulating the charging requirements of a projected fleet of 60,000 EVs, the study identifies a pronounced evening charging peak concentrated in residential areas and weakly aligned with daytime solar availability. Under the base-case charging pattern, increasing PV capacity raises the self-sufficiency potential, but has limited influence on the evening peak. In the base-case with 40 MW of installed PV capacity, the self-sufficiency ratio reaches 39.6%, while peak demand falls by only 0.20%. A charging location sensitivity analysis then shows that temporal alignment improves substantially when charging shifts from home towards workplaces and Points of Interest (POI). In a selected daytime oriented scenario with 40% workplace charging and 60% POI charging, the self-sufficiency potential reaches 68.97% and the mean daily maximum net load falls to about 18 MW at 40 MW of installed PV capacity. These results show that the value of solar integration depends strongly on where charging occurs, and that daytime charging access should be treated as a central variable in EV infrastructure planning. The study provides a planning oriented basis for future work incorporating feeder level validation, explicit PV siting constraints, and storage. Full article

(This article belongs to the Section Charging Infrastructure and Grid Integration)

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13 pages, 2127 KB

Open AccessArticle

Wallbox Inspection—Evaluating Solar Controlled Charging of EV Charging Equipment

by Bernhard Wille-Haussmann, Jan Körber, Vishnu Karthik Senthil Kumar, Nico Orth and Joseph Bergner

World Electr. Veh. J. 2026, 17(6), 312; https://doi.org/10.3390/wevj17060312 - 18 Jun 2026

To make electric mobility possible and acceptable on a large scale, it is necessary to integrate electric vehicle (EV) charging infrastructure in residential energy systems. Solar surplus charging, a special case of controlled charging, is a popular and promising operating mode of installed [...] Read more.

To make electric mobility possible and acceptable on a large scale, it is necessary to integrate electric vehicle (EV) charging infrastructure in residential energy systems. Solar surplus charging, a special case of controlled charging, is a popular and promising operating mode of installed systems. Comparison of different home energy management systems (HEMSs) in combination with a dedicated EV charging station reveals differences in control quality. Within the research project Wallbox-Inspektion, a test setup has been developed. The derived procedures determine the main criteria for evaluating the quality of solar surplus charging. The core question is: “How well does the EV charging power follow the reference?”. This contribution explains the tests for standby consumption and control quality of control steps and presents an approach to determine the impact on use case scenarios. Further, different solar charging systems (i.e., charging station, HEMS, energy meter) available on the market are compared and discussed regarding the quality of implemented solar charging strategies. Full article

(This article belongs to the Special Issue EVS38—International Electric Vehicle Symposium and Exhibition (Gothenburg, Sweden))

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19 pages, 4200 KB

Open AccessReview

Optimized Air-Conditioning Strategy Employing a Circular-Vent-Hole-Assisted Battery Thermal Management System for Electric Vehicles

by Wandee Onreabroy and Amornrat Kaewpradap

World Electr. Veh. J. 2026, 17(6), 311; https://doi.org/10.3390/wevj17060311 - 17 Jun 2026

Lithium-ion batteries used in electric vehicles (EVs) are highly sensitive to temperature variations, and excessive heat accumulation can adversely affect their performance, lifespan, and safety. Therefore, an effective battery thermal management system (BTMS) is essential for maintaining safe operating conditions. This study proposes [...] Read more.

Lithium-ion batteries used in electric vehicles (EVs) are highly sensitive to temperature variations, and excessive heat accumulation can adversely affect their performance, lifespan, and safety. Therefore, an effective battery thermal management system (BTMS) is essential for maintaining safe operating conditions. This study proposes a novel air-cooled BTMS incorporating circular vent holes in an acrylic enclosure to enhance airflow distribution and convective heat transfer around LiNiCoMnO₂ batteries. A computational fluid dynamics (CFD) model was developed to investigate the effects of discharge rate (1C–2C), inlet air velocity (1.0–3.0 m/s), and inlet air temperature (25–35 °C) on thermal behavior. The results indicate that the proposed BTMS effectively maintains battery temperatures below the critical limit of 40 °C. Optimal cooling performance was achieved at inlet air temperatures of 25–35 °C, 25–30 °C, and 25 °C for discharge rates of 1C, 1.5C, and 2C, respectively. The proposed design provides a simple, effective, and practical BTMS solution for EV applications. These findings confirm that the combination of forced air cooling and optimized vent design significantly improves thermal management performance. Full article

(This article belongs to the Section Storage Systems)

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24 pages, 8208 KB

Open AccessArticle

Deep Koopman Observer for Lithium-Ion Battery Temperature Estimation

by Mohamed H. Abdullah and Sarah M. Kandil

World Electr. Veh. J. 2026, 17(6), 310; https://doi.org/10.3390/wevj17060310 - 16 Jun 2026

Temperature monitoring is critical for lithium-ion battery (LIB) safety and performance, yet instrumenting every cell in a commercial pack remains impractical due to cost and wiring constraints. Existing sensorless methods rely on either physics-based thermal models requiring extensive parameterization or nonlinear recurrent estimators [...] Read more.

Temperature monitoring is critical for lithium-ion battery (LIB) safety and performance, yet instrumenting every cell in a commercial pack remains impractical due to cost and wiring constraints. Existing sensorless methods rely on either physics-based thermal models requiring extensive parameterization or nonlinear recurrent estimators that cannot integrate sensor feedback when measurements become available. Motivated by these limitations, this paper proposes a Deep Koopman observer that enforces linear latent dynamics, enabling direct compatibility with Kalman filtering. The observer estimates surface temperature from four standard BMS signals and two exponential moving averages of squared current that capture thermal memory at distinct time scales, operating in two modes: fully sensorless for uninstrumented cells, or sensor-fused via a one-state EKF when a thermistor is available. Evaluated under strict cell-to-cell split across twelve drive cycles and five ambient temperatures, the open-loop observer achieves 17% lower error than the strongest reproduced CNN-LSTM baseline without online resistance identification or thermal-model simulation, and the EKF path delivers a further 35% reduction over the open-loop estimate. The evaluation is limited to a single cell chemistry and manufacturing batch; cross-chemistry and aging validation remain for future work. Full article

(This article belongs to the Section Storage Systems)

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20 pages, 1694 KB

Open AccessArticle

Baseline Assessment of ESCALATE Zero-Emission Long-Haul Truck Demonstrations Regarding Total Cost of Ownership

by Mikko Pihlatie, Mikaela Ranta, Sai Santhosh Tota, Erik Skeel, Pekka Rahkola, Joel Anttila, Tsegawu Kercho, Dimitrios Kontses, Umit Utku Turkan, Ahu Ece Hartavi, Petri Kananen, Topi Nenonen, Tapio Puranen, Pasi Salmela, Haluk Atasoy, Kezban Pilic, Betül Erdör Türk, Sinem Boyaci, Stephen Storrar, Emre Özgül and Adrián Valverde Show full author list Hide full author list

World Electr. Veh. J. 2026, 17(6), 309; https://doi.org/10.3390/wevj17060309 - 15 Jun 2026

The baseline assessment analysis for total cost of ownership of the pilot demonstrations of the ESCALATE project was carried out for four different powertrain configurations, dealing with modular and scalable powertrains for various vehicle configurations in long-haul trucking. The baseline TCO methodology and [...] Read more.

The baseline assessment analysis for total cost of ownership of the pilot demonstrations of the ESCALATE project was carried out for four different powertrain configurations, dealing with modular and scalable powertrains for various vehicle configurations in long-haul trucking. The baseline TCO methodology and results for battery electric trucks (BETs), fuel cell electric trucks (FCETs) and FC range-extending BETs are analysed based on the final designs of the demonstrator vehicles and their foreseen pilot use cases and operational scenarios. As real operation data is not yet available, the analysis relies on energy use and pilot mission analysis through simulation. Overall, the TCO analysis shows several key factors affecting the relative competitiveness of the different zero-emission powertrains and vehicles. Long-haul operations pose clear challenges to vehicle design and long-range vehicles on single charge or refill show increased curb weight, limiting allowable payload due to GVW limits. The best payload capacity is shown for opportunity charging BETs and FCETs. BETs are generally the closest competitor to conventional trucks, but a key factor is the relative energy price difference between diesel, electricity (private or public) and hydrogen. Energy sourcing will be an important factor for end users to enable competitive shift to zero-emission options. Access to cheap private electricity or local green hydrogen may facilitate a choice between the options. Full article

(This article belongs to the Special Issue EVS38—International Electric Vehicle Symposium and Exhibition (Gothenburg, Sweden))

32 pages, 1039 KB

Open AccessArticle

NSGA-II-Based Stochastic Multi-Objective Optimization for Demand Response–Enabled Smart Meter Placement in EVCS/PV-Integrated Distribution Networks

by Hossein Lotfi and Hossein Parsadust

World Electr. Veh. J. 2026, 17(6), 308; https://doi.org/10.3390/wevj17060308 - 12 Jun 2026

The growing penetration of electric vehicles (EVs) and distributed photovoltaic (PV) generation is increasing operational uncertainty in distribution networks and intensifying long-standing challenges such as higher power losses, rising peak demand, and voltage instability. To address these issues, this paper proposes a multi-objective [...] Read more.

The growing penetration of electric vehicles (EVs) and distributed photovoltaic (PV) generation is increasing operational uncertainty in distribution networks and intensifying long-standing challenges such as higher power losses, rising peak demand, and voltage instability. To address these issues, this paper proposes a multi-objective optimization framework for the strategic placement of smart meters equipped with demand response (DR) capability in radial distribution systems. Unlike conventional placement approaches that mainly focus on monitoring or reducing non-technical losses, the proposed method integrates active load control into the planning stage and explicitly considers the stochastic behavior of loads, PV generation, and electric vehicle charging stations (EVCSs). The problem is formulated with four objectives: minimizing total power losses, substation peak demand, voltage deviation penalty, and installation cost. A scenario-based stochastic model is employed to represent operational variability across the network. The resulting nonlinear mixed discrete optimization problem is solved using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), an evolutionary multi-objective optimization technique that generates a set of Pareto-optimal solutions representing trade-offs among conflicting objectives. Smart meters are allowed to curtail a portion of controllable demand during critical loading conditions, which helps reduce feeder loading and improve voltage profiles. The proposed approach is evaluated on the IEEE 33-bus and IEEE 69-bus distribution systems. Simulation results demonstrate significant reductions in power losses and peak demand, with the IEEE 33-bus system achieving up to a 26.2% reduction in power losses and 52.5% reduction in substation peak demand compared with existing metaheuristic approaches. The results also indicate improved voltage stability and effective performance in the IEEE 69-bus system, confirming the importance of topology-aware DR-enabled planning. Overall, the findings show that embedding demand response capability within smart meter allocation can significantly enhance the resilience and operational efficiency of modern distribution networks with high EV and PV penetration. Full article

(This article belongs to the Section Charging Infrastructure and Grid Integration)

17 pages, 1459 KB

Open AccessArticle

Market Dynamics of Electric Single-Person Vehicles in Sweden: Opportunities and Challenges

by Hans Lindh ten Berg, Pia Sundbergh, Sara Berntsson and Björn Tano

World Electr. Veh. J. 2026, 17(6), 307; https://doi.org/10.3390/wevj17060307 - 12 Jun 2026

The market for electric single-person vehicles in Sweden has undergone significant changes, shifting from a rental-dominated model to increasing private ownership. This transformation has resulted in both benefits and challenges, including improved accessibility, evolving consumer behaviour, and increased accident rates, particularly among young [...] Read more.

The market for electric single-person vehicles in Sweden has undergone significant changes, shifting from a rental-dominated model to increasing private ownership. This transformation has resulted in both benefits and challenges, including improved accessibility, evolving consumer behaviour, and increased accident rates, particularly among young users. This study, commissioned by the Swedish government, presents a comprehensive mapping of the availability, usage, and consequences of private electric scooters. Through market surveys, user studies, and accident data analysis, we provide insights into regulatory gaps, consumer awareness, and safety concerns. Our findings highlight the need for clearer communication of existing regulations and improved consumer education to ensure the safe and responsible use of electric single-person vehicles. Full article

(This article belongs to the Special Issue EVS38—International Electric Vehicle Symposium and Exhibition (Gothenburg, Sweden))

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19 pages, 4738 KB

Open AccessArticle

A Hybrid Valley Filling and NSGA-III Metaheuristic for Day-Ahead City-Scale Electric Vehicle Charging Scheduling

by Guilherme G. Souza, Emerson G. R. Nobre, Ricardo Santos and Ruben B. Godoy

World Electr. Veh. J. 2026, 17(6), 306; https://doi.org/10.3390/wevj17060306 (registering DOI) - 11 Jun 2026

Electric vehicle (EV) fleets are expanding rapidly and will place substantial demand on distribution grids. Day-ahead scheduling of city-scale EV charging constitutes a constrained multi-objective optimization problem that must balance peak load, load variation, and valley utilization simultaneously. This paper proposes a structured [...] Read more.

Electric vehicle (EV) fleets are expanding rapidly and will place substantial demand on distribution grids. Day-ahead scheduling of city-scale EV charging constitutes a constrained multi-objective optimization problem that must balance peak load, load variation, and valley utilization simultaneously. This paper proposes a structured warm-start strategy that embeds a load-conservation valley-filling (LCVF) heuristic into the NSGA-III metaheuristic, seeding the entire initial population with grid-compliant, valley-filling schedules before the first generation runs. This search-space shaping approach restricts the evolutionary search to a feasible subspace defined by LCVF, enabling convergence that random initialization cannot achieve within the same computational budget. On four seasonal city-level instances derived from real electricity consumption data from Campo Grande, MS, Brazil (

N = 50,336

vehicles), VF–NSGA-III reduces peak load by

0.54

–

2.52 %

(mean

1.31 %

) relative to standalone LCVF while requiring only

\approx 1.5 %

of its runtime. The warm-start provides a structural advantage that population scaling alone cannot overcome: LCVF-initialized NSGA-III with

N_{pop} = 10

achieves a hypervolume

35 %

above the randomly initialized variant with

N_{pop} = 100

. A 32-day generalization study (June 2022–May 2023) confirms a mean peak-load reduction of

4.91 %

over standalone LCVF and

4.93 %

over randomly initialized NSGA-III across all seasons, demonstrating consistent performance over a full annual demand cycle. Full article

(This article belongs to the Section Charging Infrastructure and Grid Integration)

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11 pages, 1486 KB

Open AccessArticle

Swedish EV Users’ Routines and Behaviors Without Home Charging Availability

by Érika Martins Silva Ramos and Jens Hagman

World Electr. Veh. J. 2026, 17(6), 305; https://doi.org/10.3390/wevj17060305 - 11 Jun 2026

This study investigates the charging behaviors, routines, and perceptions of Swedish electric vehicle (EV) users who lack access to home charging, a group that remains underrepresented in the EV adoption literature. Based on an online survey of 250 EV users—primarily located in Gothenburg—respondents [...] Read more.

This study investigates the charging behaviors, routines, and perceptions of Swedish electric vehicle (EV) users who lack access to home charging, a group that remains underrepresented in the EV adoption literature. Based on an online survey of 250 EV users—primarily located in Gothenburg—respondents were divided into two groups: those with and those without home charging availability. Nearly half of the sample (47.6%) reported not having access to charging at home. Comparative analyses, including linear regression models, were conducted to examine differences in sociodemographic characteristics, charging patterns, and perceptions of public charging. While the two groups were similar in terms of age, gender, vehicle type, charging frequency, and minimum state of charge preferences, significant differences emerged in perceived convenience, distance, and freedom to charge. Users without home charging availability reported lower access to workplace charging and evaluated public charging as less convenient and less accessible. Charging behavior in both groups was primarily goal-oriented and triggered by minimum state of charge rather than spontaneous opportunities. The findings highlight the structural disadvantages faced by users without home charging and underline the importance of adapting public charging infrastructure and policy strategies to support a broader and more equitable transition to electric mobility. Full article

(This article belongs to the Special Issue EVS38—International Electric Vehicle Symposium and Exhibition (Gothenburg, Sweden))

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19 pages, 5454 KB

Open AccessArticle

Electric Vehicle User Behavior Forecasting via Data-Driven Techniques

by Yonghua Xu, Xiangyi Tang and Wei Liu

World Electr. Veh. J. 2026, 17(6), 304; https://doi.org/10.3390/wevj17060304 - 9 Jun 2026

Electric vehicle (EV) charging behaviors exhibit significant heterogeneity in terms of price sensitivity, time-of-day preference, and weekend charging habits, creating challenges for charging demand prediction and service management. To address this issue, this paper proposes a three-variable charging response framework that jointly considers [...] Read more.

Electric vehicle (EV) charging behaviors exhibit significant heterogeneity in terms of price sensitivity, time-of-day preference, and weekend charging habits, creating challenges for charging demand prediction and service management. To address this issue, this paper proposes a three-variable charging response framework that jointly considers electricity price, time-of-day preference, and weekend preference. Using real charging-order data from a public charging platform, four behavioral parameters, namely baseline charging demand (Q₀), price sensitivity (α), time preference (β), and weekend preference (γ), are estimated through nonlinear least squares (NLS). Based on the extracted parameter vectors, K-means clustering is employed to identify five representative user groups: Commuting-Dominant, elastic energy-saving, Weekend-Switching, Night-Preferential, and discount-sensitive users. The results reveal substantial behavioral heterogeneity among users. To validate the proposed framework, both parameter interpretability analysis and benchmark comparisons are conducted. Compared with the best baseline model, the proposed method reduces the test RMSE from 11.5 kWh to 8.3 kWh (27.8%), decreases the test MAPE from 25.3% to 18.7% (26.1%), and improves the test R² from 0.70 to 0.80. The proposed framework provides an interpretable approach for EV charging behavior modeling and user segmentation, offering practical support for differentiated pricing, charging demand management, and intelligent charging service operation. Full article

(This article belongs to the Section Marketing, Promotion and Socio Economics)

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