Vehicle Applications Research Articles

Optimization of power loss and thermal performance in electric vehicle propulsion: a comparative analysis of Si, SiC, and GaN MOSFET power converters for EESM-based EVs

ABSTRACT This research delves into power loss and thermal dynamics in Si, SiC, and GaN inverters and two-quadrant DC-DC converters for Electric Vehicle (EV) applications with Electrically Excited Synchronous Motors (EESM). Utilizing the Cauer thermal model for dissipating junction temperature through heatsinks, the research unveils semiconductor material performance intricacies. The Si-based inverter exhibits the highest total power loss at 355.49 W, followed by SiC at 164.28 W, and GaN at 139.21 W. The efficiencies of Si, SiC, and GaN-based inverters are calculated as 94.72%, 97.49%, and 97.86%, respectively. Among them, the GaN-based inverter shows the highest efficiency, which is 3.14% higher than that of the Si-based inverter. GaN emerges as the energy-efficient choice, showcasing superior conduction and switching losses for EESM-based EV propulsion. Integration of heatsinks reduces Si average junction temperatures from 199.69 °C to 55.63 °C, SiC from 93.9 °C to 45.97 °C, and GaN from 84.13 °C to 38.78 °C. Enhanced forced cooling and advanced thermal interface materials highlights the critical role of robust thermal management in EESM-based EVs. GaN emerges as the prime candidate for EESM-based EV inverters and DC-DC converters. This research underscores meticulous semiconductor material selection and efficient cooling strategies for optimal performance and reliability.

Inhalation Exposure to Airborne Prothioconazole Caused by Unmanned Aerial Vehicles Application and Potential Lung Health Effects.

The use of unmanned aerial vehicle (UAV) has greatly improved pesticide effectiveness and control efficiency; however, the risk of inhalation exposure to pesticides caused by spray drift requires urgent attention. This study is the first to investigate residue distribution and inhalation exposure risk of airborne prothioconazole and its metabolite prothioconazole-desthio during UAV application. The maximum detected unit exposure of prothioconazole and prothioconazole-desthio in airborne particulate matter was 0.40 and 20.09 ng/m3, respectively. For exposure risk assessment, in vivo inhalation bioavailability (BAinvivo) was incorporated to adjust the inhalation exposure level, and the corresponding values measured were 37.58 and 73.99%, respectively. Moreover, we observed pesticide accumulation in rat lungs and its cause of histological damage via oxidative stress following 10-day exposure. The margin of exposure for propiconazole and prothioconazole-desthio was calculated to be within an acceptable level; however, the values might be overestimated by 40 and 70% without considering inhalation bioavailability.

Large-Area Coverage Path Planning Method Based on Vehicle–UAV Collaboration

With the widespread application of unmanned aerial vehicles (UAV) in surveying, disaster search and rescue, agricultural spraying, war reconnaissance, and other fields, coverage path planning is one of the most important problems to be explored. In this paper, a large-area coverage path planning (CCP) method based on vehicle–UAV collaboration is proposed. The core idea of the proposed method is adopting a divide-and conquer-strategy to divide a large area into small areas, and then completing efficient coverage scanning tasks through the collaborative cooperation of vehicles and UAVs. The supply points are generated and adjusted based on the construction of regular hexagons and a Voronoi diagram, and the segmentation and adjustment of sub-areas are also achieved during this procedure. The vehicle paths are constructed based on the classical ant colony optimization algorithm, providing an efficient way to traverse all supply points within the coverage area. The classic zigzag CCP method is adopted to fill the contours of each sub-area, and the UAV paths collaborate with vehicle supply points using few switching points. The simulation experiments verify the effectiveness and feasibility of the proposed vehicle–UAV collaboration CCP method, and two comparative experiments demonstrate that the proposed method excels at large-scale CCP scenarios, and achieves a significant improvement in coverage efficiency.

Review—Meeting Fuel Cell Catalyst Requirements for Heavy-Duty Vehicle Applications

Abstract Catalyst requirements for proton exchange membrane (PEM) fuel cells differ by applications. Commercial heavy-duty vehicle (HDV) applications consume more H2 fuel and demand higher durability than many others and the total cost of ownership (TCO) of the vehicle is largely related to the performance and durability of catalysts. This article is written to bridge the gap between the industrial requirements and academic activity for advanced cathode catalysts with an emphasis on durability. From a materials perspective, the underlying nature of the carbon support, Pt-alloy crystal structure, stability of the alloying element, cathode ionomer volume fraction, and catalyst-ionomer interface play a critical role in improving performance and durability. We provide our perspective on four major approaches, namely, mesoporous carbon supports, ordered PtCo intermetallic alloys, thrifting ionomer volume fraction, and shell-protection strategies that are currently being pursued. While each approach has its merits and demerits, their key developmental needs for future are highlighted.

Review of Thermal Management Techniques for Prismatic Li-Ion Batteries

This review presents a comprehensive analysis of battery thermal management systems (BTMSs) for prismatic lithium-ion cells, focusing on air and liquid cooling, heat pipes, phase change materials (PCMs), and hybrid solutions. Prismatic cells are increasingly favored in electric vehicles and energy storage applications due to their high energy content, efficient space utilization, and improved thermal management capabilities. We evaluate the effectiveness, advantages, and challenges of each thermal management technique, emphasizing their impact on performance, safety, and the lifespan of prismatic Li-ion batteries. The analysis reveals that while traditional air and liquid cooling methods remain widely used, 80% of the 21 real-world BTMS samples mentioned in this review employ liquid cooling. However, emerging technologies such as PCM and hybrid systems offer superior thermal regulation, particularly in high-power applications. However, both PCM and hybrid systems come with significant challenges; PCM systems are limited by their low thermal conductivity and material melting points. While hybrid systems face complexity, cost, and potential reliability concerns due to their multiple components nature. This review underscores the need for continued research into advanced BTMSs to optimize energy efficiency, safety, and longevity for prismatic cells in electric vehicle applications and beyond.

Metalized Polymer Current Collector for High‐Energy Lithium‐Ion Batteries with Extreme Fast‐Charging Capability

Electric vehicles are pivotal in the global shift toward decarbonizing road transport, with lithium‐ion batteries at the heart of this technological evolution. However, the pursuit of batteries capable of extremely fast charging that also satisfy high energy and safety criteria, poses a significant challenge to current lithium‐ion batteries technologies. Additionally, the increasing demand for aluminum (Al) and copper (Cu) in electrification, solar energy technologies, and vehicle light‐eighting is driving these metals toward near‐critical status in the medium term. This study introduces metalized polythylene terephthalate (mPET) polymer films by depositing an Al or Cu thin layer onto two sides of a polyethylene terephthalate film—named mPET/Al and mPET/Cu, as lightweight, cost‐effective alternatives to traditional metal current collectors in lithium‐ion batteries. We have fabricated current collectors that significantly reduce weight (by 73%), thickness (by 33%), and cost (by 85%) compared with traditional metal foil counterparts. These advancements have the potential to enhance energy density to 280 Wh kg−1 at the electrode level under 10‐min charging at 6 C. Through testing, including a novel extremely fast charging protocol across various C‐rates and long‐term cycling (up to 1000 cycles) in different cell configurations, the superior performance of these metalized polymer films has been demonstrated. Notably, mPET/Cu and mPET/Al films exhibited comparable capacities to conventional cells under extremely fast charging, with the mPET cells showing a 27% improvement in energy density at 6 C and maintaining significant energy density after 1000 cycles. This study underscores the potential of mPET films to revolutionize the roll‐to‐roll battery manufacturing process and significantly advance the performance metrics of lithium‐ion batteries in electric vehicles applications.

Unraveling the Degradation Mechanism of LiNbO3‐Coated NMC Cathode at High Potential in All‐Solid‐State Batteries Using 10 K Extended X‐ray Absorption Fine Structure Analysis

All solid‐state batteries (ASSBs) utilizing sulfide‐based solid electrolytes hold promise for enhancing battery energy density while mitigating safety concerns, thus meeting the stringent requirements for electric vehicle applications. For practical application of ASSBs, it is important to stabilize the interface between the solid electrolyte and the cathode. Although cathode coated with a thin layer of LiNbO3 allows higher interface stability, which significantly improves charge‐discharge and cycle performance, degradation at high potentials has also been noted. In this study, we focused on the degradation mechanism of LiNbO3‐coated LiNi0.5Co0.2Mn0.3O2 cathode active materials at high potentials by using 3 electrode system for ASSBs which allows separating the impedance measurement of the interface between cathode and solid electrolyte. We performed X‐ray absorption spectroscopy (XAS) measurements at low temperature (10 K) to analyze the local structure around Nb and correlating these findings with impedance measurements. Our results indicate that the impedance of LiNbO3 increased rapidly due to the oxygen desorption reaction at high potentials. This study aims to elucidate the dynamic change and degradation mechanism of LiNbO3‐coated LiNi0.5Co0.2Mn0.3O2 in ASSBs and provide new ideas for the design of interfacial coating materials.

Development of an Aerial Manipulation System Using Onboard Cameras and a Multi-Fingered Robotic Hand with Proximity Sensors.

Recently, aerial manipulations are becoming more and more important for the practical applications of unmanned aerial vehicles (UAV) to choose, transport, and place objects in global space. In this paper, an aerial manipulation system consisting of a UAV, two onboard cameras, and a multi-fingered robotic hand with proximity sensors is developed. To achieve self-contained autonomous navigation to a targeted object, onboard tracking and depth cameras are used to detect the targeted object and to control the UAV to reach the target object, even in a Global Positioning System-denied environment. The robotic hand can perform proximity sensor-based grasping stably for an object that is within a position error tolerance (a circle with a radius of 50 mm) from the center of the hand. Therefore, to successfully grasp the object, a requirement for the position error of the hand (=UAV) during hovering after reaching the targeted object should be less than the tolerance. To meet this requirement, an object detection algorithm to support accurate target localization by combining information from both cameras was developed. In addition, camera mount orientation and UAV attitude sampling rate were determined by experiments, and it is confirmed that these implementations improved the UAV position error to within the grasping tolerance of the robot hand. Finally, the experiments on aerial manipulations using the developed system demonstrated the successful grasping of the targeted object.

Gain scheduling of backstepping sliding mode controller using optimized type-1 Sugeno fuzzy logic approach for quadcopter

PurposeThis paper aims to propose an optimized type-1 Sugeno fuzzy logic backstepping sliding mode controller (T1-SFL-BSMC) to control the altitude and rotational behaviour of a quadcopter. The proposed controller improves the performance of the system by overcoming the limitations of conventional trial-and-error techniques for BSMC gain design.Design/methodology/approachIn this study, the type-1 Sugeno fuzzy logic controller (T1-SFLC) technique is proposed which dynamically modifies the BSMC gains. In addition, the parameters of T1-SFLC are further tuned by five different optimization techniques, namely, genetic algorithm, particle swarm optimization (PSO), pattern search (PS), simulated annealing (SA) and adaptive neural network (ANN).FindingsThe effectiveness of these optimization techniques in tuning the T1-SFLCs for the gain scheduled BSMC is evaluated in terms of time response metrics; rising time, settling time and root mean square error (RMSE) for altitude and rotational behaviour. The results demonstrated that PSO-optimized T1-SFL-BSMC provides better responses in terms of time response metrices with reduced rise and settling times and minimized RMSE when compared to other optimized T1-SFL-BSMC.Originality/valueThis paper proposes a novel approach for controlling quadcopters by combining fuzzy logic with a BSMC. It is then improved by using many optimization strategies. A more dependable and effective approach to controller design is provided by the suggested method, which is essential for unmanned aerial vehicle applications.

Vehicle-mounted Millimeter-wave Radar Target Recognition Technology

Vehicle-mounted millimeter-wave radar target tracking technology is a technology that uses millimeter-wave radar equipment to detect and track targets around the vehicle. This technology relies on specific characteristics of radar signals, such as frequency and amplitude, and analyzes the reflected signals from targets to gather information. Through algorithm processing and analysis, it can track the target's position, speed and trajectory. The basic principle of vehicle-mounted millimeter-wave radar target tracking is to use radar equipment to transmit radio frequency signals. When the signal encounters an object, it is reflected back to the radar device, providing information about the target. This article explains this new technology in three parts: the working principle of millimeter-wave radar, various cutting-edge algorithms in the technology, and its application in vehicles. The integration of millimeter-wave radar technology represents a significant advancement in vehicle safety and autonomous driving capabilities. Furthermore, understanding these technological components is crucial for developing more efficient and reliable vehicle detection systems.

Small‐Signal Modelling of Bidirectional CLLC Converters for Onboard Charging Application in Electric Vehicles

ABSTRACTA two‐stage onboard battery charger with an CLLC resonant converter is a widely adopted configuration in the automotive industry. The ZVS and ZCS capability of the switching devices with high operating frequency of the CLLC converters encourages its application in various EV platforms to improve efficiency. In the literature, various authors proposed many methods to control the CLLC converters efficiently, but up to now, no simple and accurate small‐signal equivalent circuit modelling is available. As dynamic networks are load‐dependent, closed‐loop voltage and current controllers provide more stable operations in these converters. In this paper, a detailed mathematical modelling of the CLLC converters with time domain analysis has been presented. The proposed mathematical model accurately predicts the small‐signal behaviors seen in pulse‐frequency‐modulated (PFM) CLLC resonant converters whether the switching frequency is below, near to, or above the resonant frequency. Stable closed‐loop controllers for both current and voltage loops in battery charging applications are designed and detailed. A prototype hardware is been built and the experimental results with the load variations with the designed controllers are tested and the results are been discussed in the paper.

Comparative Study on Environmental Impact of Electric Vehicle Batteries from a Regional and Energy Perspective

Against the backdrop of the global goal of “carbon neutrality”, the advancement of electric vehicles (EVs) holds substantial importance for diminishing the reliance on fossil fuels, mitigating vehicular emissions, and fostering the transition of the automotive sector towards a sustainable, low-carbon paradigm. The wide application of electric vehicles not only reduces the dependence on non-renewable resources such as oil, but also concurrently effectuates a substantial reduction in carbon emissions within the transportation sector. In the realm of electric vehicles, ternary lithium batteries (NCM) and lithium iron phosphate batteries (LFP) are two widely used batteries. This study examines the resource utilization and environmental repercussions associated with the production of 1 kW ternary lithium batteries and lithium iron phosphate batteries, employing a life cycle assessment (LCA) framework. The importance of clean energy in reducing environmental pollution and global warming potential is revealed by introducing five different power generation types and the regional power generation structure in China into the power battery production process. The findings of the investigation indicate that lithium iron phosphate batteries exhibit pronounced superiority in terms of environmental sustainability, while ternary lithium batteries are more advantageous in terms of performance. The mitigation of environmental pollution associated with battery production can be significantly achieved by the holistic integration of clean energy sources and the systematic optimization of manufacturing processes. Specific interventions encompass enhancing the energy efficiency of the production process, incorporating renewable energy sources for power generation, and minimizing the utilization of hazardous materials. By implementing these strategies, the battery sector can advance towards a more environmentally benign and sustainable trajectory.

Ego-Motion Estimation for Autonomous Vehicles Based on Genetic Algorithms and CUDA Parallel Processing

Estimating ego-motion in autonomous vehicles is critical for tasks such as localization, navigation, obstacle avoidance, and so on. While traditional methods often rely on direct pose estimation or AI-based approaches, these can be computationally intensive, especially for small, incremental movements typically observed between consecutive frames. In this work, we propose a brute-force-based ego-motion estimation algorithm that takes advantage of the constraints of autonomous vehicles, which are assumed to have only three degrees of freedom (x, y, and yaw). Our approach is based on a genetic algorithm to efficiently explore potential vehicle movements. By generating an initial seed of random motion candidates and iteratively mutating and selecting the best-performing individuals, we minimize the cost function that measures image similarity between frames. Furthermore, we implement the algorithm using CUDA to exploit parallel processing, significantly improving computational speed. Experimental results demonstrate that our approach achieves accurate ego-motion estimation with high efficiency, making it suitable for real-time autonomous vehicle applications.

Based on the form of new energy, the development prospect of supercapacitors in electric vehicles is discussed

With the increasing global emphasis on environmental protection and sustainable development, new forms of energy have gradually become a key development direction in the energy sector. Electric vehicles, as an important application area of new energy technology, have their performance improvement and technological innovation as the focal points of industry attention. Supercapacitors, as an emerging energy storage device, have shown great potential in the field of electric vehicles due to their fast charging and discharging, high power density, and long cycle life. This article analyzes the development trend of electric vehicle technology under new energy forms and deeply explores the basic principles of supercapacitors and their specific applications in electric vehicles. Furthermore, this article looks forward to the development prospects of supercapacitors in electric vehicles, pointing out their enormous potential in improving electric vehicle performance and promoting efficient energy utilization. However, the development of supercapacitors also faces challenges such as high costs, limited energy density, and insufficient technological maturity. Addressing these issues, this paper puts forward suggestions such as strengthening technological research and development and optimizing joint usage strategies. The aim is to achieve positive interaction and collaborative development between supercapacitors and electric vehicles.

Does the promotion and application of new energy vehicles contribute to the reduction of carbon intensity? A quasi-natural experiment analysis

Does the promotion and application of new energy vehicles contribute to the reduction of carbon intensity? A quasi-natural experiment analysis

Integrated location and routing optimization for the application of electric vehicles in on-demand delivery

Integrated location and routing optimization for the application of electric vehicles in on-demand delivery

Advanced Online State-of-Health Prediction and Monitoring of Na-Ion Battery for Electric Vehicles Application

Advanced Online State-of-Health Prediction and Monitoring of Na-Ion Battery for Electric Vehicles Application

Optimal Design for Six-Phase Asymmetrical Surface Mount Permanent Magnet Synchronous Motor: An Innovative Approach Considering Fault Tolerance and Load Variations for Electric Vehicle Applications

Optimal Design for Six-Phase Asymmetrical Surface Mount Permanent Magnet Synchronous Motor: An Innovative Approach Considering Fault Tolerance and Load Variations for Electric Vehicle Applications

ET-Net: A novel framework for fine-grained traffic classification in intelligent vehicle applications

ET-Net: A novel framework for fine-grained traffic classification in intelligent vehicle applications

An Enhanced Vehicle-to-Vehicle Wireless Power Transfer System for Electric Vehicle Applications Using a Reconfigurable Coil Approach

An Enhanced Vehicle-to-Vehicle Wireless Power Transfer System for Electric Vehicle Applications Using a Reconfigurable Coil Approach