World Electric Vehicle Journal

26 pages, 14549 KiB

Open AccessArticle

Research on Energy-Saving Control Strategy of Nonlinear Thermal Management System for Electric Tractor Power Battery Under Plowing Conditions

by Xiaoshuang Guo, Ruiliang Xu, Junjiang Zhang, Xianghai Yan, Mengnan Liu and Mingyue Shi

World Electr. Veh. J. 2025, 16(5), 249; https://doi.org/10.3390/wevj16050249 - 25 Apr 2025

Abstract

To address the issue of over-regulation of the temperature of a liquid-cooled power battery thermal management system under the plowing condition of electric tractors, which leads to high energy consumption, a nonlinear model prediction control (NMPC) algorithm for the thermal management system of [...] Read more.

To address the issue of over-regulation of the temperature of a liquid-cooled power battery thermal management system under the plowing condition of electric tractors, which leads to high energy consumption, a nonlinear model prediction control (NMPC) algorithm for the thermal management system of the power battery of electric tractors applicable to the plowing condition is proposed. Firstly, a control-oriented electric tractor power battery heat production model and a heat transfer model were established based on the tractor operating conditions and Bernardi’s theory of battery heat production. Secondly, in order to improve the accuracy of temperature prediction, a prediction method of future working condition information based on the moving average theory is proposed. Finally, a nonlinear model predictive control cooling optimization strategy is proposed, with the optimization objectives of quickly achieving battery temperature regulation and reducing compressor energy consumption. The proposed control strategy is validated by simulation and a hardware-in-the-loop (HIL) testbed. The results show that the proposed NMPC strategy can control the battery temperature better, that in the holding phase the proposed control strategy reduces the compressor speed variation range by 24.6% compared with PID, and that it reduces the compressor energy consumption by 23.1% in the whole temperature control phase. Full article

(This article belongs to the Special Issue New Energy Vehicle Thermal and Energy Management Systems Design and Collaborative Control)

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23 pages, 2616 KiB

Open AccessArticle

Investigation of Harmonic Losses to Reduce Rotor Copper Loss in Induction Motors for Traction Applications

by Muhammad Salik Siddique, Hulusi Bülent Ertan, Muhammad Shahab Alam and Muhammad Umer Khan

World Electr. Veh. J. 2025, 16(5), 248; https://doi.org/10.3390/wevj16050248 - 25 Apr 2025

Abstract

The focus of this paper is to seek means of increasing induction motor efficiency to a comparable level to a permanent magnet motor. Harmonic and high-frequency losses increase the rotor core and copper loss, often limiting IM efficiency. The research in this study [...] Read more.

The focus of this paper is to seek means of increasing induction motor efficiency to a comparable level to a permanent magnet motor. Harmonic and high-frequency losses increase the rotor core and copper loss, often limiting IM efficiency. The research in this study focuses on reducing rotor core and copper losses for this purpose. An accurate finite element model of a prototype motor is developed. The accuracy of this model in predicting the performance and losses of the prototype motor is verified with experiments over a 32 Hz–125 Hz supply frequency range. The verified model of the motor is used to identify the causes of the rotor core and copper losses of the motor. It is found that the air gap flux density of the motor contains many harmonics, and the slot harmonics are dominant. The distribution of the core loss and the copper loss is investigated on the rotor side. It is discovered that up to 35% of the rotor copper losses and 90% rotor core losses occur in the regions up to 4 mm from the airgap where the harmonics penetrate. To reduce these losses, one solution is to reduce the magnitude of the air gap flux density harmonics. For this purpose, placing a sleeve to cover the slot openings is investigated. The FEA indicates that this measure reduces the harmonic magnitudes and reduces the core and bar losses. However, its effect on efficiency is observed to be limited. This is attributed to the penetration depth of flux density harmonics inside the rotor conductors. To remedy this problem, several FEA-based modifications to the rotor slot shape are investigated to place rotor bars deeper than the harmonic penetration. It is found that placing the bars further away from the rotor surface is very effective. Using a 1 mm sleeve across the stator’s open slots combined with a rotor tapered slot lip positions the bars slightly deeper than the major harmonic penetration depth, making it the optimal solution. This reduces the bar loss by 70% and increases the motor efficiency by 1%. Similar loss reduction is observed over the tested supply frequency range. Full article

(This article belongs to the Special Issue Propulsion Systems of EVs 2.0)

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16 pages, 7117 KiB

Open AccessArticle

Performance Evaluation of Outer Rotor Permanent Magnet Direct Drive In-Wheel Motor Based on Air-Gap Field Modulation Effect

by Qin Wang

World Electr. Veh. J. 2025, 16(5), 247; https://doi.org/10.3390/wevj16050247 - 25 Apr 2025

Abstract

The different pole–slot combinations of outer rotor surface-mounted permanent magnet (ORSPM) motors are designed and analyzed to satisfy EV driving requirements. Firstly, the analytical model for various slot–pole combinations of ORSPM motors is proposed based on the air-gap field modulation effect. Then, some [...] Read more.

The different pole–slot combinations of outer rotor surface-mounted permanent magnet (ORSPM) motors are designed and analyzed to satisfy EV driving requirements. Firstly, the analytical model for various slot–pole combinations of ORSPM motors is proposed based on the air-gap field modulation effect. Then, some of the in-wheel motor parameters and requirements are obtained for the vehicle system. In addition, some special pole–slot combination ORSPM motors are built to achieve higher flux density, and the electromagnetic performance is compared based on the finite element (FE) model, revealing that the 56-slot/48-pole (54s48p) in-wheel motor has a higher torque density and superior flux weakening capability than other cases. Finally, a 13 kW prototype with 54s48p is manufactured and tested to confirm the effectiveness of the FE analysis. Full article

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28 pages, 2961 KiB

Open AccessArticle

Impact Assessment of Integrating AVs in Optimizing Urban Traffic Operations for Sustainable Transportation Planning in Riyadh

by Nawaf Mohamed Alshabibi

World Electr. Veh. J. 2025, 16(5), 246; https://doi.org/10.3390/wevj16050246 - 24 Apr 2025

Abstract

Integrating autonomous vehicles (AVs) into urban traffic systems presents significant opportunities for optimizing traffic flow, reducing congestion, and enhancing transportation efficiency. This study proposes a comprehensive framework that combines mathematical optimization techniques, policy planning, and AV adoption modeling to improve urban mobility. Using [...] Read more.

Integrating autonomous vehicles (AVs) into urban traffic systems presents significant opportunities for optimizing traffic flow, reducing congestion, and enhancing transportation efficiency. This study proposes a comprehensive framework that combines mathematical optimization techniques, policy planning, and AV adoption modeling to improve urban mobility. Using Highway Capacity Manual (HCM) Optimization methods, the research fine-tunes traffic signal timings, dynamically allocates green time, and enhances intersection coordination to maximize throughput. The study evaluates the impact of AV penetration on traffic flow efficiency, congestion reduction, and infrastructure readiness using real-world urban data from Riyadh. The results indicate that AV integration leads to a 40% increase in traffic throughput, a 60% reduction in congestion levels, and a 45% improvement in infrastructure readiness, highlighting the effectiveness of AV-driven traffic optimization strategies. Additionally, policy interventions aimed at reducing legal constraints and increasing societal acceptance contribute to the successful implementation of AV technology. The findings provide a data-driven roadmap for city planners and policymakers, demonstrating how a well-structured AV deployment strategy can significantly enhance urban transportation efficiency. Full article

(This article belongs to the Special Issue Advancements in Autonomous Vehicles: Security, Optimization and Future Challenges)

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25 pages, 5857 KiB

Open AccessArticle

Evaluation of the Intersection Sight Distance at Stop-Controlled Intersections in a Mixed Vehicle Environment

by Jana Sarran and Sean Sarran

World Electr. Veh. J. 2025, 16(5), 245; https://doi.org/10.3390/wevj16050245 - 23 Apr 2025

Abstract

The introduction of autonomous vehicles (AVs) on roadways will result in a mixed vehicle environment consisting of these vehicles and manual vehicles (MVs). This vehicular environment will impact intersection sight distances (ISDs) due to differences in the driving behaviors of AVs and MVs. [...] Read more.

The introduction of autonomous vehicles (AVs) on roadways will result in a mixed vehicle environment consisting of these vehicles and manual vehicles (MVs). This vehicular environment will impact intersection sight distances (ISDs) due to differences in the driving behaviors of AVs and MVs. Currently, ISD design values for stop-controlled intersections are based on AASHTO’s guidelines, which account only for human driver behaviors. However, with AVs in the traffic stream, it is important to assess whether the existing MV-based ISDs are compliant when an AV is present at an intersecting roadway. Hence, this study utilizes the Monte Carlo Simulation method to compute the PNC of various object locations on the major and minor roadways for possible vehicle interaction types in a mixed vehicle environment at a stop-controlled intersection. Scenarios generated considered these variables and the major roadway speed limits and sight distance triangles (SDTs). ISD non-compliance was determined by examining the PNC metric, which occurred when the demand exceeded the supply. The results indicated that when AV–MV interaction was present at the intersection, the MV-based ISD design was non-compliant. However, it is possible to correct this non-compliance issue by reducing the AV speed limit. Full article

(This article belongs to the Special Issue Recent Advances in Autonomous Vehicles)

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21 pages, 13843 KiB

Open AccessArticle

Improved Quintic Polynomial Autonomous Vehicle Lane-Change Trajectory Planning Based on Hybrid Algorithm Optimization

by Yuelou Zhang, Lingshan Chen and Ning Li

World Electr. Veh. J. 2025, 16(5), 244; https://doi.org/10.3390/wevj16050244 - 23 Apr 2025

Abstract

A trajectory planning method is proposed to address the lane-changing problem in intelligent vehicles. The method is based on quintic polynomial improvement. The transit position is determined according to the position and state of motion of the vehicle and the obstacle vehicle; the [...] Read more.

A trajectory planning method is proposed to address the lane-changing problem in intelligent vehicles. The method is based on quintic polynomial improvement. The transit position is determined according to the position and state of motion of the vehicle and the obstacle vehicle; the lane-changing process is divided into two segments. The quintic polynomials are commonly applied in trajectory planning, respectively, in the two segments. According to the different characteristics of the lane-changing paths in the front and rear segments, a multi-objective optimization function with different weight coefficients is established. A safe and comfortable lane-changing trajectory is achieved through the improved particle swarm optimization algorithm. Real-time simulation tests of lane-changing method are conducted on the hardware-in-the-loop platform. The method can be used in different scenarios to plan safe and comfortable trajectories. Full article

(This article belongs to the Special Issue Motion Planning and Control of Autonomous Vehicles)

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24 pages, 5964 KiB

Open AccessArticle

A Privacy-Preserving Scheme for Charging Reservations and Subsequent Deviation Settlements for Electric Vehicles Based on a Consortium Blockchain

by Beibei Wang, Yikun Yang, Wenjie Liu and Lun Xu

World Electr. Veh. J. 2025, 16(5), 243; https://doi.org/10.3390/wevj16050243 - 22 Apr 2025

Abstract

Electric vehicles have garnered substantial attention as an environmentally sustainable transportation alternative amid escalating global concerns regarding ecological preservation and energy resource management. While the proliferation of electric vehicles necessitates the development of efficient and secure charging infrastructure, the inherent communication-intensive nature of [...] Read more.

Electric vehicles have garnered substantial attention as an environmentally sustainable transportation alternative amid escalating global concerns regarding ecological preservation and energy resource management. While the proliferation of electric vehicles necessitates the development of efficient and secure charging infrastructure, the inherent communication-intensive nature of the charging processes has raised concerns regarding potential privacy vulnerabilities. Our paper introduces a privacy protection scheme specifically designed for electric vehicle charging reservations to address this issue. The primary goal of this scheme is to protect user privacy while maintaining operational efficiency and economic viability for charging providers. Our proposed solution ensures a secure and private environment for charging reservation transactions and subsequent deviation settlements by incorporating advanced technologies, including zero-knowledge proof, a consortium blockchain, and homomorphic encryption. The scheme encrypts charging reservation information and securely transmits it via a consortium blockchain, effectively shielding the sensitive data of all participating parties. Notably, the experimental findings establish the robustness of our scheme in terms of its security and privacy protection, aligning with the stringent demands of electric vehicle charging operations. Full article

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15 pages, 242 KiB

Open AccessCommunication

Enhancing Sustainable Last-Mile Delivery: The Impact of Electric Vehicles and AI Optimization on Urban Logistics

by Joao C. Ferreira and Marco Esperança

World Electr. Veh. J. 2025, 16(5), 242; https://doi.org/10.3390/wevj16050242 - 22 Apr 2025

Abstract

The rapid growth of e-commerce has intensified the need for efficient and sustainable last-mile delivery solutions in urban environments. This paper explores the integration of electric vehicles (EVs) and artificial intelligence (AI) into a combined framework to enhance the environmental, operational, and economic [...] Read more.

The rapid growth of e-commerce has intensified the need for efficient and sustainable last-mile delivery solutions in urban environments. This paper explores the integration of electric vehicles (EVs) and artificial intelligence (AI) into a combined framework to enhance the environmental, operational, and economic performance of urban logistics. Through a comprehensive literature review, we examine current trends, technological developments, and implementation challenges at the intersection of smart mobility, green logistics, and digital transformation. We propose an operational framework that leverages AI for route optimization, fleet coordination, and energy management in EV-based delivery networks. This framework is validated through a real-world case study conducted in Lisbon, Portugal, where a logistics provider implemented a city consolidation center model supported by AI-driven optimization tools. Using key performance indicators—including delivery time, energy consumption, fleet utilization, customer satisfaction, and CO₂ emissions—we measure the pre- and post-AI deployment impacts. The results demonstrate significant improvements across all metrics, including a 15–20% reduction in delivery time, a 10–25% gain in energy efficiency, and up to a 40% decrease in emissions. The findings confirm that the synergy between EVs and AI provides a robust and scalable model for achieving sustainable last-mile logistics, supporting broader urban mobility and climate objectives. Full article

(This article belongs to the Special Issue Theory, Method and Application of New Energy and Intelligent Transportation)

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World Electr. Veh. J., Volume 16, Issue 5 (May 2025) – 8 articles

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