WEVJ MDPI

04/12/2025

Editor’s Choice – World Electric Vehicle Journal

Neural Sliding Mode Control (NSMC) takes regenerative braking in EVs to the next level! ⚡🚗
A new study shows how an RHONN-based controller with Kalman filter training (EKF & UKF) outperforms traditional PI controllers, boosting battery SOC and efficiency in EVs. Robust even under noise and parameter changes.

Read more: https://brnw.ch/21wY3WN

This paper presents the design and simulation of a neural sliding mode controller (NSMC) for a regenerative braking system in an electric vehicle (EV). The NSMC regulates the required current and voltage of the bidirectional DC-DC buck–boost converter, an element of the auxiliary energy system (AE...

03/12/2025

Hybrid vehicle adoption in Guayaquil is still limited—but technical features matter more than price! 🚗⚡
A new study finds technology, performance, and maintenance drive purchase intentions, while financing and info gaps influence decisions.
Focus on long-term savings & reliability rather than generic sustainability messages. 🌱

Read more: https://brnw.ch/21wY3cK

01/12/2025

👉This study develops a multi-dimensional psychological model to explain driver takeover safety in conditionally automated vehicles. Based on survey data from 385 ADS users in Shaoguan, China, the model integrates the Theory of Planned Behavior with real-world driving experience. Results show that driver attitudes, perceived behavioral control, and subjective norms significantly influence takeover intention, explaining 48.7% of its variance. Both intention and perceived control have strong direct effects on actual takeover behavior, with the full model explaining 58.3% of behavior variance. Importantly, user characteristics such as driving experience and ADS usage frequency moderate these relationships: experienced or frequent users rely more on perceived control and attitudes, while less experienced drivers are more influenced by social norms. These findings provide actionable insights for designing adaptive human–machine interfaces, developing targeted driver training programs, and enhancing safety interventions for automated driving systems. The proposed psychological approach complements traditional engineering models, offering a deeper understanding of human factors in automated driving.

🔊Check for more :

With the rapid adoption of automated driving systems, ensuring safe and efficient driver takeover has become a crucial challenge for road safety. This study introduces a novel psychological framework for understanding and predicting takeover behavior in conditionally automated vehicles, leveraging a...

01/12/2025

🚀 New publication alert!

📄 “The Speed of Shared Autonomous Vehicles Is Critical to Their Demand Potential”

We analyzed real-world data from the AV KEXI – Germany’s first autonomous Mobility-on-Demand (AMoD) service operated on public roads – to understand how demand reacts to key system parameters.
🔍 Key findings include:
• 🚗 Increasing vehicle speed leads to 📈 superlinear demand growth, especially with small fleets
• 🧑‍🤝‍🧑 Demand saturates at large fleet sizes
• 🗺️ Expanding the service area and 🕐 moving to full-day operations boosts ridership
• 🚙💤 Idle vehicle positioning significantly affects usage

📘 Full study: https://brnw.ch/21wXYwp

🚀 New publication alert! I am happy to announce the publication of my latest study in the WEVJ MDPI: 📄 “The Speed of Shared Autonomous Vehicles Is Critical to Their Demand Potential” We analyzed real-world data from the AV KEXI – Germany’s first autonomous Mobility-on-Demand (AMoD) ser...

28/11/2025

Holistic security Framework for connected EVs: AI-enabled detection, lightweight crypto, privacy tech, and SIEM/EDR oversight stop spoofing, replay & jamming across V2V/V2X and EV charging/BMS.

🧷

This study conducts a detailed analysis of cybersecurity threats, including artificial intelligence (AI)-driven cyber-attacks targeting vehicle-to-vehicle (V2V) and electric vehicle (EV) communications within the rapidly evolving field of connected and autonomous vehicles (CAVs). As autonomous and e...

28/11/2025

The article introduces a novel aircraft charging problem optimizing speed, energy use, and costs for hybrid electric flights using advanced heuristics and genetic algorithms.

🧷

The shift toward sustainable aviation has accelerated research into hybrid electric aircraft, particularly in the context of regional air mobility. To support this transition, we introduce the Soft Fixed Route Hybrid Electric Aircraft Charging Problem with Variable Speed (S-FRHACP-VS), a novel optim...

27/11/2025

YOLOv5s-F enables real-time small target detection on highways via lightweight FasterNet backbone, dedicated 160×160 layer, and Focal EIoU loss. Achieves 32 FPS on embedded devices with higher accuracy.

🧷

To address the challenges of real-time monitoring via highway vehicle-mounted cameras—specifically, the difficulty in detecting distant pedestrians and vehicles in real time—this study proposes an enhanced object detection algorithm, YOLOv5s-F. Firstly, the FasterNet network structure is adopted...

27/11/2025

⚡ Editor’s Choice: Comparison of EV Fast Charging Protocols

Fast charging is crucial for EV adoption, but it can strain the grid and affect battery life. This study explores innovative sinusoidal half-wave DC and pulsed charging methods for lithium-ion batteries, showing how these protocols can improve efficiency and reduce battery degradation over 250 cycles. A promising step toward smarter, longer-lasting fast charging!

Read more: https://brnw.ch/21wXShw

In electric vehicle fast charging systems, it is important to minimize the effect of fast charging on the grid and it is also important to operate the charging system at high efficiencies. In order to achieve these objectives, in this paper, a sinusoidal half-wave DC current charging protocol and a ...

26/11/2025

⚡ Editor’s Choice: Flexibility Potential of Smart Charging Electric Trucks and Buses

Did you know that electric trucks and buses could provide up to 23 GW of flexibility to the energy system in Germany by 2040? This study explores how smart charging of heavy-duty electric vehicles can help balance the grid, reduce electricity costs for depots, and support a cleaner energy transition.

Read more: https://brnw.ch/21wXQb9

In addition to passenger vehicles, battery-electric trucks and buses could offer substantial flexibility to the energy system. Using a Bass diffusion model, we extrapolated the unidirectional charging needs and availability of trucks in five of eleven typical applications, as well as city buses, for...

26/11/2025

This study develops a bilevel optimization model for planning EV battery swapping and charging stations, jointly minimizing system cost and user service time.

The rapid growth of electric vehicles (EVs) has significantly increased the demand for charging infrastructure, posing a challenge in balancing charging demand and infrastructure supply. The development of battery swapping and charging stations (BSCSs) is crucial for addressing these challenges and ...

25/11/2025

In this study, we present a sensitivity-stratified multi-objective optimization method to enhance the electromagnetic performance of IPM synchronous motors. By stratifying multiple rotor structure parameters based on sensitivity and applying tailored analysis and optimization methods to each stratum, we achieved dual optimization goals: boosting the fundamental amplitude of air gap magnetic flux density and reducing total harmonic distortion. Additionally, our analysis of demagnetization conditions improved the demagnetization resistance of permanent magnets.
This approach effectively tackled the challenges of complex parameter interdependencies and magnetic field complexity in IPM motor design, leading to significant electromagnetic performance improvements. The optimized motor demonstrates increased fundamental amplitude of air gap magnetic flux density, reduced harmonic distortion, enhanced demagnetization resistance, and improved average output torque with decreased torque ripple under rated conditions. These advancements provide new insights and methods for high-performance IPM synchronous motor design and optimization, offering great significance for enhancing motor performance in applications such as electric vehicles.

Read for more:

In addressing the challenges posed by the numerous rotor structure parameters and the difficulty in analyzing the air gap magnetic field distribution in interior permanent magnet (IPM) motors, and to enhance the performance of automotive IPM synchronous motors, this paper proposes a multi-objective ...

25/11/2025

🚙This paper addresses the adoption of electric vehicles in the transportation sector by proposing the use of electric heavy-duty trucks for logistics and distribution of large prefabricated building components. Our approach seeks to tackle the high total costs and significant energy waste associated with traditional transportation methods. We focus on a multi-to-multi distribution mode and construct a two-level optimization model. The upper-level model allocates demand points effectively, while the lower-level model optimizes the selection of road network nodes and charging stations along delivery routes. It also dynamically adjusts charging timing and volume based on real-time power conditions. To enhance performance, we design a two-level multi-objective evolutionary algorithm grounded in Pareto theory, which simultaneously optimizes distribution costs and coordinates path planning and charging strategies. Comparative experiments indicate that our algorithm improves both accuracy and quality over traditional single-level and multi-stage models. Additionally, the dynamic charging strategy proposed reduces total distribution costs by approximately 15.83% when compared to a full-charge capacity strategy. These findings demonstrate the effectiveness of our model and algorithm in optimizing logistics and provide feasible solutions for implementing electric vehicles in engineering logistics.

Read for more:

To align with the adoption of electric vehicles in the transportation sector, this paper proposes the use of electric heavy-duty trucks for the logistics and distribution of large prefabricated building components. This approach aims to address the problems of high total costs and significant energy...