Journal articles: 'Lightweight vehicle'

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Xie, Yong. "A Comparative Study on the Effectiveness of Lightweight Shipborne Underwater Vehicle Based on Certification Position." Applied Mechanics and Materials 148-149 (December 2011): 478–82. http://dx.doi.org/10.4028/www.scientific.net/amm.148-149.478.

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For the operational effectiveness comparison of lightweight shipborne underwater vehicle,establish and implement anti-ship underwater vehicle’s and two types of lightweight shipborne underwater vehicle’s trajectory and hit probability model,proposed the method of certification position for lightweight shipborne underwater vehicle,given the operational effectiveness calculation model.Finally,through the practical example of two types of lightweight shipborne underwater vehicle’s operational effectiveness comparison.The calculation results testify that this method is feasibility and effectiveness.The research is of great reference value for the assess different types of lightweight shipborne underwater vehicle.

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Stabile, Pietro, Federico Ballo, Gianpiero Mastinu, and Massimiliano Gobbi. "An Ultra-Efficient Lightweight Electric Vehicle—Power Demand Analysis to Enable Lightweight Construction." Energies 14, no. 3 (February 1, 2021): 766. http://dx.doi.org/10.3390/en14030766.

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A detailed analysis of the power demand of an ultraefficient lightweight-battery electric vehicle is performed. The aim is to overcome the problem of lightweight electric vehicles that may have a relatively bad environmental impact if their power demand is not extremely reduced. In particular, electric vehicles have a higher environmental impact during the production phase, which should be balanced by a lower impact during the service life by means of a lightweight design. As an example of an ultraefficient electric vehicle, a prototype for the Shell Eco-marathon competition is considered. A “tank-to-wheel” multiphysics model (thermo-electro-mechanical) of the vehicle was developed in “Matlab-Simscape”. The model includes the battery, the DC motors, the motor controller and the vehicle drag forces. A preliminary model validation was performed by considering experimental data acquisitions completed during the 2019 Shell Eco-marathon European competition at the Brooklands Circuit (UK). Numerical simulations are employed to assess the sharing of the energy consumption among the main dissipation sources. From the analysis, we found that the main sources of mechanical dissipation (i.e., rolling resistance, gravitational/inertial force and aerodynamic drag) have the same role in the defining the power consumption of such kind of vehicles. Moreover, the effect of the main vehicle parameters (i.e., mass, aerodynamic coefficient and tire rolling resistance coefficient) on the energy consumption was analyzed through a sensitivity analysis. Results showed a linear correlation between the variation of the parameters and the power demand, with mass exhibiting the highest influence. The results of this study provide fundamental information to address critical decisions for designing new and more efficient lightweight vehicles, as they allow the designer to clearly identify which are the main parameters to keep under control during the design phase and which are the most promising areas of action.

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Mei, Lin, and Li Xiaoke. "Key Technologies of Lightweight Materials for New Energy Vehicles Based on Ant Colony Algorithm." Computational Intelligence and Neuroscience 2022 (June 17, 2022): 1–8. http://dx.doi.org/10.1155/2022/1617814.

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From the perspective of the new energy vehicle, application of lightweight technology can effectively improve the endurance level of new energy vehicles and promote the steady improvement and rapid development of China’s new energy vehicle industry. By keeping in view the importance of lightweight effect of new energy vehicles, in this paper, we have carried out an in-depth analysis of key contents such as new materials, battery weight, carbon fiber technology, and structural design technology in the process of lightweight development of new energy vehicles. Furthermore, this paper introduces the pseudorandom proportional rule to improve the selection method of the seed solution, makes appropriate random disturbance to the center of the pheromone distribution, and reforms the standard deviation of the pheromone distribution. Taking the lightweight of new energy vehicle doors as an example, this paper verifies the new energy vehicle lightweight algorithm based on ant colony algorithm. It is found that the improved continuous domain basic ant colony algorithm is superior to the other two algorithms and it has the capacity to solve optimization problems and has the advantages of high reliability.

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LIN, Shih-Pin, Yuichiro TAKINO, Yoshihiro SUDA, Masahisa KAGEYAMA, Atsushi TANIMOTO, and Shinichiro KOGA. "2F23 Study on Lightweight Railway Vehicle Dynamics in Wet Condition (Vehicles-Rail/Wheel)." Proceedings of International Symposium on Seed-up and Service Technology for Railway and Maglev Systems : STECH 2015 (2015): _2F23–1_—_2F23–6_. http://dx.doi.org/10.1299/jsmestech.2015._2f23-1_.

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Hyunhee Park, Hyunhee Park. "Edge Based Lightweight Authentication Architecture Using Deep Learning for Vehicular Networks." 網際網路技術學刊 23, no. 1 (January 2022): 195–202. http://dx.doi.org/10.53106/160792642022012301020.

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When vehicles are connected to the Internet through vehicle-to-everything (V2X) systems, they are exposed to diverse attacks and threats through the network connections. Vehicle-hacking attacks in the road can significantly affect driver safety. However, it is difficult to detect hacking attacks because vehicles not only have high mobility and unreliable link conditions, but they also use broadcast-based wireless communication. To this end, V2X systems need a simple but a powerful authentication procedure on the road. Therefore, this paper proposes an edge based lightweight authentication architecture using a deep learning algorithm for road safety applications in vehicle networks. The proposed lightweight authentication architecture enables vehicles that are physically separated to form a vehicular cloud in which vehicle-to-vehicle communications can be secured. In addition, an edge-based cloud data center performs deep learning algorithms to detect car hacking attempts, and then delivers the detection results to a vehicular cloud. Extensive simulations demonstrate that the proposed authentication architecture significantly enhanced the security level. The proposed authentication architecture has 94.51 to 99.8% F1-score results depending on the number of vehicles in the intrusion detection system using control area network traffic.

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Dittmar, Harri, and Henrik Plaggenborg. "Lightweight vehicle underbody design." Reinforced Plastics 63, no. 1 (January 2019): 29–32. http://dx.doi.org/10.1016/j.repl.2017.11.014.

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Mao, Ping Huai, Shuai Zhang, Li Bao Wang, and Yi Lin Mao. "Analysis of Lightweight Extension Support Coal Mine Car Loader." Applied Mechanics and Materials 687-691 (November 2014): 593–96. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.593.

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Horizontal support extending loader vehicle is used in coal mine, whose main role is to play a supportive role in belt transport unit. When the support car is pulled by tractor or pushed by motor vehicle, energy consumption is high with its own excessive weight. The car lightweight design is carried out through structural designing and material changing. Lightweight design has met the requirements after analysis. Lightweight design for support vehicle is not only to achieve the purpose of energy conservation, but also make the support vehicles assembling easily and get a good effect.

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Busarac, Nina, Dragan Adamovic, Nenad Grujovic, and Fatima Zivic. "Lightweight Materials for Automobiles." IOP Conference Series: Materials Science and Engineering 1271, no. 1 (December 1, 2022): 012010. http://dx.doi.org/10.1088/1757-899x/1271/1/012010.

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Abstract This paper deals with vehicle lightweighting, as a strategy to help attain sustainability in the automotive industry by facilitating improved fuel economy. We reviewed innovative materials appropriate for the manufacturing of low-carbon vehicles (LCVs), such as advanced high-strength steel (AHSS), aluminum alloys, magnesium alloys, as well as novel composite materials commonly used for lightweight construction applications. Research shows that vehicle curb weight greatly affects fuel consumption. Primary weight reduction refers to body-in-white (BIW), which can subsequently lead to secondary weight reductions in terms of engine and powertrain size. This review takes into account the environmental aspect of the car body material and the possibility of closed-loop recycling, especially for aluminum and magnesium alloys.

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Almuhaideb, Abdullah M., and Sammar S. Algothami. "ECQV-Based Lightweight Revocable Authentication Protocol for Electric Vehicle Charging." Big Data and Cognitive Computing 6, no. 4 (September 27, 2022): 102. http://dx.doi.org/10.3390/bdcc6040102.

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In the near future, using electric vehicles will almost certainly be required for the sustainability of nature and our planet. The most significant challenge that users are concerned about is the availability of electric vehicle charging stations. Therefore, to maximize the availability of electric vehicle charging stations, we suggest taking benefit from individual sellers who produce renewable energy from their homes or electric vehicle owners who have charging piles installed in their homes. However, energy services that are rapidly being offered by these businesses do not have a trust connection developed with the consumers and stakeholders in these new systems. Exchange of data related to electric vehicles and energy aggregators can be used to identify users’ behavior and compromise their privacy. Consequently, it is necessary to set up a charging system that will guarantee privacy and security. Several electric vehicle charging systems have been proposed to provide security and privacy preservation. However, ensuring anonymity alone is not enough to guarantee protection from reconstructing the victim vehicle’s route by the tracking adversary, even if the exchanged messages are completely anonymous. Furthermore, anonymity should not be absolute in order to protect the system and function as necessary by all entities. In this research, we propose an effective, secure, and privacy-preserving authentication method based on the Elliptic Curve Qu–Vanstone for an electric vehicle charging system. The proposed scheme provides all the necessary requirements and a reauthentication protocol to minimize the overhead of subsequent authentication processes. To create credentials and validate electric vehicles and energy aggregators, the scheme makes use of the Elliptic Curve Qu–Vanstone implicit certificate mechanism. The new protocols give EVs security and privacy while cutting computational time by 95% thanks to reauthentication, as demonstrated by the performance comparison with earlier works.

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Obradović, Đorđe, Živorad Mihajlović, Vladimir Milosavljević, and Miloš B. Živanov. "Graphic LCD for Lightweight Electric Vehicles." Key Engineering Materials 543 (March 2013): 163–66. http://dx.doi.org/10.4028/www.scientific.net/kem.543.163.

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In this paper, one solution of graphic LCD control board for lightweight electric vehicles is shown. The main idea was to build adoptable hardware solution that can be fast and easy applied in different electrical vehicles and easy for modifications. It was designed, built and tested graphic LCD for monitoring and seting up of main parameters and control signals for lightweight electric vehicle. Some of parameters that could be displayed on graphic LCD are charge status, actual speed, total mileage, daily mileage and indicators of direction. Also we discussed about other possibilities for some sensors that can be used to monitor vehicle speed and ways of visualizing the parameters of interest. The main principles that were used during the selection of hardware solutions implementation also are shown.

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Xu, Huibin, Mengjia Zeng, Wenjun Hu, and Juan Wang. "Authentication-Based Vehicle-to-Vehicle Secure Communication for VANETs." Mobile Information Systems 2019 (June 26, 2019): 1–9. http://dx.doi.org/10.1155/2019/7016460.

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Communication in VANETs is vulnerable to various types of security attacks since it is constructed based on an open wireless connection. Therefore, a lightweight authentication (LIAU) scheme for vehicle-to-vehicle communication is proposed in this paper. The LIAU scheme requires hash operations and uses cryptographic concepts to transfer messages between vehicles, in order to maintain the required security. Moreover, we made the LIAU scheme lightweight by introducing a small number of variable parameters in order to reduce the storage space. Performance analysis shows that the LIAU scheme is able to resist various types of security attacks and it performs well in terms of communication cost and operation time.

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Lipman, Timothy E., and Petra Maier. "Advanced materials supply considerations for electric vehicle applications." MRS Bulletin 46, no. 12 (December 2021): 1164–75. http://dx.doi.org/10.1557/s43577-022-00263-z.

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AbstractElectric vehicles are now proliferating based on technologies and components that in turn rely on the use of strategic materials and mineral resources. This review article discusses critical materials considerations for electric drive vehicles, focusing on the underlying component technologies and materials. These mainly include materials for advanced batteries, motors and electronics, lightweight structures, and other components specific to each vehicle type. Particularly strategic and widely used minerals and elements/structures for electric vehicles include nickel, cobalt, rare-earth minerals, lightweight and high strength steel alloys and underlying metals (e.g., magnesium and aluminum), carbon fiber, graphite and graphene, copper, and steel alloying materials. Additional key considerations include those around component and vehicle supply chains, repurposing and recycling vehicle components at end of vehicle life, and environmental and humanitarian considerations around the extraction and transport of the evolving set of materials needed for modern electric vehicle production. Graphical abstract

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Dalboni, Matteo, Dario Mangoni, Davide Lusignani, and Alessandro Soldati. "Lightweight dynamic vehicle models oriented to vehicle electrification." International Journal of Vehicle Performance 5, no. 1 (2019): 40. http://dx.doi.org/10.1504/ijvp.2019.097097.

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Soldati, Alessandro, Matteo Dalboni, Dario Mangoni, and Davide Lusignani. "Lightweight dynamic vehicle models oriented to vehicle electrification." International Journal of Vehicle Performance 5, no. 1 (2019): 40. http://dx.doi.org/10.1504/ijvp.2019.10018133.

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Ye, Linsheng, Linghe Kong, Kayhan Zrar Ghafoor, Guihai Chen, and Shahid Mumtaz. "LAB: Lightweight Adaptive Broadcast Control in DSRC Vehicular Networks." Wireless Communications and Mobile Computing 2018 (August 13, 2018): 1–10. http://dx.doi.org/10.1155/2018/5713913.

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The Industrial Internet of Things (IIoT) is the use of Internet of Things (IoT) technologies in manufacturing. The vehicular ad hoc networks (VANETs) are a typical application of IIoT. Benefiting from Dedicated Short-Range Communication (DSRC) technology, vehicles can communicate with each other through wireless manner. Therefore, road safety is able to be greatly improved by the broadcast of safety messages, which contain vehicle’s real-time speed, position, direction, etc. In existing DSRC, safety messages are broadcasted at a fixed frequency by default. However, traffic conditions are dynamic. In this way, there are too many transmission collisions when vehicles are too dense and the wireless channel is underused when vehicles are too sparse. In this paper, we address broadcast congestion issue in DSRC and propose lightweight adaptive broadcast (LAB) control for DSRC safety message. The objectives of LAB are to make full use of DSRC channel and avoid congestion. LAB meets two key challenges. First, it is hard to adopt a centralized method to control the communication parameters of distributed vehicles. Furthermore, the vehicle cannot easily acquire the channel conditions of other vehicles. To overcome these challenges, channel condition is attached with safety messages in LAB and broadcast frequency is adapted according to neighboring vehicles’ channel conditions. To evaluate the performance of LAB, we conduct extensive simulations on different roads and different vehicle densities. Performance results demonstrate that LAB effectively adjusts the broadcast frequency and controls the congestion.

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Pusztai, Zoltán, Péter Kőrös, Ferenc Szauter, and Ferenc Friedler. "Vehicle Model-Based Driving Strategy Optimization for Lightweight Vehicle." Energies 15, no. 10 (May 16, 2022): 3631. http://dx.doi.org/10.3390/en15103631.

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In this paper, driving strategy optimization for a track is proposed for an energy efficient battery electric vehicle dedicated to the Shell Eco-marathon. A measurement-based mathematical vehicle model was developed to simulate the behavior of the vehicle. The model contains complicated elements such as the vehicle’s cornering resistance and the efficiency field of the entire powertrain. The validation of the model was presented by using the collected telemetry data from the 2019 Shell Eco-marathon competition in London (UK). The evaluation of applicable powertrains was carried out before the driving strategy optimization. The optimal acceleration curve for each investigated powertrain was defined. Using the proper powertrain is a crucial part of energy efficiency, as the drive has the most significant energy demand among all components. Two tracks with different characteristics were analyzed to show the efficiency of the proposed optimization method. The optimization results are compared to the reference method from the literature. The results of this study provide an applicable vehicle modelling methodology with efficient optimization framework, which demonstrates 5.5% improvement in energy consumption compared to the reference optimization theory.

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Brückmann, Simon M., Horst E. Friedrich, Michael Kriescher, Gundolf Kopp, and Roman Gätzi. "Lightweight Sandwich Structures in Innovative Vehicle Design under Crash Load Cases." Materials Science Forum 879 (November 2016): 2419–27. http://dx.doi.org/10.4028/www.scientific.net/msf.879.2419.

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On modern vehicles, the demand is made to be in every respect as efficient as possible. A technical method to increase energetic efficiency is to reduce the vehicle mass through the implementation of lightweight construction measures. The energy consumption decreases by that and the vehicle dynamics behavior of conventionally and alternatively respectively electrically powered vehicles increases. In the department Lightweight and Hybrid Design Methods of the Institute of Vehicle Concepts in Stuttgart in collaboration with 3A Composite Core Materials, a method which allows to realize sandwich structures for automotive structural applications analytically and conceptually, is developed. The development method based on material and component testing and material values would be determined at different loads, for example in pressure and in-plane tests. These values are transmitted into the analytical determination of so called failure mode maps to derive appropriate sandwich structures. With novel sandwich structures the objectives of high structural stiffness and strength are tracked, as well as a high level of energy absorption potential. By function integrating the potential of lightweight construction, depending on the energy absorption per structural weight, can be further increased. Accompanying tests on generic structures are made to validate the failure behavior. Also the influence of core material on the deformation behavior is examined. The results from the tests are transferred to a vehicle front structure of a planned lightweight vehicle of class L7E called "Safe Light Regional Vehicle" (SLRV). The behavior of the structure is examined in static and dynamic tests. The energy absorbing capacity can be further increased by geometric optimization and the use of different core materials. The research on sandwich materials is part of the research project Next Generation Car (NGC) of the DLR and represents in terms of the new vehicle concept SLRV in sandwich design a novel vehicle concept of this joint project.

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Wang, Li Xia, Tian Feng Zhao, Jian Bo Cao, Ji Feng Shen, Yan Bin Xiao, and Ze Xin Zhou. "Design of Body Structure for New Type Lightweight Electric Vehicle." Key Engineering Materials 620 (August 2014): 335–40. http://dx.doi.org/10.4028/www.scientific.net/kem.620.335.

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Considering the efficient use of energy and environmental pollution, people's lives tend to energy saving and environmental protection, and energy saving electric vehicles has gradually been widely used. Through combining theoretical analysis, numerical simulation, system design and experimental validation, based on studying electric vehicle body design principles, the experiment optimized electric vehicle body design, and reduced the weight of the vehicle effectively. Its performance becomes more advanced, and the application becomes more economical and safe. By using Solidworks software, lightweight electric vehicle body structure of two-dimensional design and three-dimensional modeling was built to reach practical requirements. The body structure design is original and simple, which has good practical value.

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Das, R. K., A. Upadhyay, and R. K. Garg. "An Unmanned Tracked Vehicle for Snow Research Applications." Defence Science Journal 67, no. 1 (December 23, 2016): 74. http://dx.doi.org/10.14429/dsj.1.8952.

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Lightweight robotic vehicles can be designed for over-snow mobility to carry out a variety of snow and glacier related studies like carrying out GPR survey of cracks & crevasses over ice crusts that cannot support foot travel, for collecting snow samples and carrying out sub-surface experiments with penetrometers on terrain that are dangerous for human, GPS mapping of avalanche debris etc. Sinkage, resistance to snow compaction, loss of traction and ingestion of snow into the driving system are some of the challenges that an unmanned lightweight tracked vehicle faces in snowbound terrain. In present work, a lightweight and unmanned remotely operated vehicle (ROV) is conceptualized and developed as a technological solution. In this paper design and features of this vehicle, named HimBot, are presented along with the results obtained from tests carried over snow at Solang Nullah field observatory of SASE in February 2013. The outcome of this work will help in developing an optimized design of an ROV for over snow mobility for a variety of applications.

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Pettersson, Stefan. "Lightweight infrastructure for electric vehicle charging." World Electric Vehicle Journal 7, no. 4 (December 28, 2015): 631–42. http://dx.doi.org/10.3390/wevj7040631.

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Suzuki, Katsutoshi, Takamasa Yamamoto, Katsuya Nagata, and Kengo Hurukawa. "442 Development of Ultra Lightweight Vehicle." Proceedings of the Symposium on Environmental Engineering 2012.22 (2012): 377–80. http://dx.doi.org/10.1299/jsmeenv.2012.22.377.

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Pusztai, Zoltán, Péter Kőrös, and Ferenc Friedler. "Modelling Steering Resistance to Save Energy." IOP Conference Series: Materials Science and Engineering 1237, no. 1 (May 1, 2022): 012016. http://dx.doi.org/10.1088/1757-899x/1237/1/012016.

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Abstract In this paper, the design and vehicle model implementation of a spiral path steering system for a lightweight vehicle is presented. The lateral sliding caused by imperfect rolling in corners means considerable loss, for lightweight vehicles. A spiral path steering mechanism provides an alternative solution for steering generated loss reduction. Theoretically, with the application of a spiral path steering system, ideal Ackerman steering geometry is feasible in all corners. The system is able to replace the common rack and pinion solution in purpose-made vehicles. The main design concepts of spiral path steering are introduced in this article. The described system was realized and installed in an experimental vehicle, where field tests were carried out, to measure the cornering losses during operation. The process of cornering loss measurement is also presented in this paper. The resistance model of cornering is elaborated in a Matlab Simulink environment, based on the measurement results. Vehicle losses are characterized by an extended resistance force model, which can be used by simulations for energy saving purposes. The optimization of vehicle operation can be achieved by simulations, where the corresponding velocity profiles of the vehicle is determined. An accurate steering model is essential for proper vehicle modelling and for the following optimization process.

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Jia, Lei, Jianzhu Wang, Tianyuan Wang, Xiaobao Li, Haomin Yu, and Qingyong Li. "HMD-Net: A Vehicle Hazmat Marker Detection Benchmark." Entropy 24, no. 4 (March 28, 2022): 466. http://dx.doi.org/10.3390/e24040466.

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Vehicles carrying hazardous material (hazmat) are severe threats to the safety of highway transportation, and a model that can automatically recognize hazmat markers installed or attached on vehicles is essential for intelligent management systems. However, there is still no public dataset for benchmarking the task of hazmat marker detection. To this end, this paper releases a large-scale vehicle hazmat marker dataset named VisInt-VHM, which includes 10,000 images with a total of 20,023 hazmat markers captured under different environmental conditions from a real-world highway. Meanwhile, we provide an compact hazmat marker detection network named HMD-Net, which utilizes a revised lightweight backbone and is further compressed by channel pruning. As a consequence, the trained-model can be efficiently deployed on a resource-restricted edge device. Experimental results demonstrate that compared with some established methods such as YOLOv3, YOLOv4, their lightweight versions and popular lightweight models, HMD-Net can achieve a better trade-off between the detection accuracy and the inference speed.

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Limbasiya, Trupil, and Debasis Das. "Lightweight Secure Message Broadcasting Protocol for Vehicle-to-Vehicle Communication." IEEE Systems Journal 14, no. 1 (March 2020): 520–29. http://dx.doi.org/10.1109/jsyst.2019.2932807.

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Kim, Wansoo, Jungho Lee, Yousik Lee, Yoenjin Kim, Jingyun Chung, and Samuel Woo. "Vehicular Multilevel Data Arrangement-Based Intrusion Detection System for In-Vehicle CAN." Security and Communication Networks 2022 (January 20, 2022): 1–11. http://dx.doi.org/10.1155/2022/4322148.

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Modern vehicles are equipped with various types of electrical/electronic (E/E) systems. Electronic control units (ECUs) are used to control various E/E systems in the vehicle. For efficient information exchange between ECUs, most vehicle manufacturers use the Controller Area Network (CAN) protocol. However, CAN has security vulnerabilities because it does not have an authentication or encryption method. Since attacks on in-vehicle networks affect the safety of drivers, it is essential to develop a technology to prevent attacks. The intrusion detection system (IDS) is one of the best ways to enhance network security. Unlike the traditional IDS for network security, IDS for the in-vehicle network requires a lightweight algorithm because of the limitation of the computing power of in-vehicle ECUs. In this paper, we propose a lightweight IDS algorithm for in-vehicle CAN based on the degree of change between successive data frames. In particular, the proposed method minimizes the load on the ECU by using the CAN data frame compression algorithm based on exclusive-OR operations as a tool for calculating the degree of change.

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Nicoletti, Lorenzo, Andrea Romano, Adrian König, Peter Köhler, Maximilian Heinrich, and Markus Lienkamp. "An Estimation of the Lightweight Potential of Battery Electric Vehicles." Energies 14, no. 15 (July 31, 2021): 4655. http://dx.doi.org/10.3390/en14154655.

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Although battery electric vehicles (BEVs) are locally emission-free and assist automakers in reducing their carbon footprint, two major disadvantages are their shorter range and higher production costs compared to combustion engines. These drawbacks are primarily due to the battery, which is generally the heaviest and most expensive component of a BEV. Lightweight measures (strategies to decrease vehicle mass, e.g., by changing materials or downsizing components) lower energy consumption and reduce the amount of battery energy required (and in turn battery costs). Careful selection of lightweight measures can result in their costs being balanced out by a commensurate reduction in battery costs. This leads to a higher efficiency vehicle, but without affecting its production and development costs. In this paper, we estimate the lightweight potential of BEVs, i.e., the cost limit below which a lightweight measure is fully compensated by the cost savings it generates. We implement a parametric energy consumption and mass model and apply it to a set of BEVs. Subsequently, we apply the model to quantify the lightweight potential range (in €/kg) of BEVs. The findings of this paper can be used as a reference for the development of cheaper, lighter, and more energy-efficient BEVs.

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Verbrugge, Mark, Theresa Lee, Paul E. Krajewski, Anil K. Sachdev, Catarina Bjelkengren, Richard Roth, and Randy Kirchain. "Mass Decompounding and Vehicle Lightweighting." Materials Science Forum 618-619 (April 2009): 411–18. http://dx.doi.org/10.4028/www.scientific.net/msf.618-619.411.

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Although mass reduction can be associated with additional costs, a decision to lightweight a structural subsystem may, depending on when in the vehicle development process the decision is taken, result in secondary (additional) mass savings such that the value of lightweighting is substantially increased. This paper overviews a method to estimate the potential for secondary mass savings in different vehicle subsystems. We close by describing current research efforts aimed at developing new lightweight product solutions for both body and powertrain applications along with commensurate manufacturing processes.

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Qin, Yuting, and Junying Fang. "The Application of New Energy Materials in New-energy Vehicle." Academic Journal of Science and Technology 2, no. 3 (September 8, 2022): 111–13. http://dx.doi.org/10.54097/ajst.v2i3.1537.

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Climate change is becoming one of the biggest environmental challenges in the 21st century. New-energy vehicle produce less greenhouse gases as compared to the traditional vehicles with internal combustion engines. New energy vehicles have great potential to successfully address the issue of climate change. Additionally, new energy materials can also be used in automotive lightweight technology. This paper discussed the currently lightweight materials including high-strength low-alloy steel (HSLA), carbon fiber composite material, and modified plastics. According to the discussion in this paper, high-strength low-alloy steel can be used in automotive safety parts, chassis, and body. Carbon fiber composite materials can be used in car bodies, chassis, roofs, doors, head covers, hoods, rear wings, center consoles, trim strips, drive shafts, leaf springs, frames, brake pads, interior and exterior accessories. Modified plastics can be mainly used in exterior decorative parts, interior decorative parts, functional parts, and structural parts. However, three are still many drawbacks of application of new energy materials in new-energy vehicle. The current new energy materials used in automotive lightweight technology are usually costly and time-consuming. Moreover, the characteristics of the new energy materials are still not clear. It could have a negative impact on the environment. Before this technology can be widely used in new-energy vehicles, more research is needed regarding the new energy materials.

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Jandura, Pavel, and Martin Bukvic. "Lightweight Battery Electric Vehicle for Educational Purposes." Applied Mechanics and Materials 390 (August 2013): 281–85. http://dx.doi.org/10.4028/www.scientific.net/amm.390.281.

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Introducing the concept of Battery Electric Vehicle developed at the Technical University of Liberec, intended for test and educational purposes. It is a lightweight four wheeled vehicle with an open frame primarily designed for ease of access to all major vehicle components. For the main structural elements of the vehicle frame was chosen modular system of extruded aluminum profiles. The vehicle power unit consists of BLDC motor paired with multi-speed manual transmission. Traction battery with regard for the electrical safety consists of 17s LFP cells only, resulting in a nominal voltage of 55 VDC (63 VDC fully charged). Total amount of energy stored in the traction battery is 10.8 kWh.

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Jia, Junbo, and Jonas W. Ringsberg. "Numerical and Experimental Investigation of Dynamics of Vehicle/Ship-Deck Interactions." Marine Technology and SNAME News 45, no. 01 (January 1, 2008): 28–41. http://dx.doi.org/10.5957/mt1.2008.45.1.28.

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The paper presents numerical modeling and analysis of vehicle/ship-deck interactions and a review of similar models and approaches in the literature. The physical modeling of vehicles is discussed together with the modeling of supporting structures/ship decks, and the interactions between vehicles and supporting structures. Some engineering applications are studied, for example, the dynamic structural behavior of vehicle/ship-deck systems, vehicle vibrations, damping effects of vehicles on structural systems, dynamic interactions between tires and deck surfaces, and vehicle securing on decks during ship motions. In addition, results from modal testing of unloaded and vehicle-loaded lightweight deck systems in a ship and the tire-deck friction under dynamic loading are reported. The results are used for validation and verification of models. Finally, vehicle transportation using RO/RO ships and lashing-free vehicle concept ideas are studied and discussed.

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Zhi-Yong Yang, Zhi-Yong Yang, Zhen-Ping Mou Zhi-Yong Yang, Long Wang Zhen-Ping Mou, and Yu Zhou Long Wang. "Application of Lightweight Neural Network in Speed Bump Recognition of Autonomous Vehicle." 電腦學刊 33, no. 5 (October 2022): 029–38. http://dx.doi.org/10.53106/199115992022103305003.

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Vibration occurs when a vehicle passes through a speed bump, which has different intensities at different sizes and speeds. The recognition of speed bump type is an important step for vehicle to adjust speed automatically in time in automatic driving, which helps to improve the safety and comfort of passengers. In this paper, we put forward the technical requirements of speed bump image acquisition in automatic driving scene, and establish the speed bump image dataset. Based on improved EfficientNet basic block, we construct a lightweight convolutional neural network integrating edge detection, which is named Edge-Efficientnet. The experimental results show that its accuracy is improved by 3.3% and the model size is reduced by 53% compared with EfficientNetB0 model. In terms of computing speed, the model meets the real-time performance requirements. The Edge-Efficientnet model can be applied to the comfortable speed adjustment of autonomous vehicles passing through speed bump.

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Targosz, Mirosław, Wojciech Skarka, and Piotr Przystałka. "Model-Based Optimization of Velocity Strategy for Lightweight Electric Racing Cars." Journal of Advanced Transportation 2018 (June 7, 2018): 1–20. http://dx.doi.org/10.1155/2018/3614025.

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The article presents a method for optimizing driving strategies aimed at minimizing energy consumption while driving. The method was developed for the needs of an electric powered racing vehicle built for the purposes of the Shell Eco-marathon (SEM), the most famous and largest race of energy efficient vehicles. Model-based optimization was used to determine the driving strategy. The numerical model was elaborated in Simulink environment, which includes both the electric vehicle model and the environment, i.e., the race track as well as the vehicle environment and the atmospheric conditions. The vehicle model itself includes vehicle dynamic model, numerical model describing issues concerning resistance of rolling tire, resistance of the propulsion system, aerodynamic phenomena, model of the electric motor, and control system. For the purpose of identifying design and functional features of individual subassemblies and components, numerical and stand tests were carried out. The model itself was tested on the research tracks to tune the model and determine the calculation parameters. The evolutionary algorithms, which are available in the MATLAB Global Optimization Toolbox, were used for optimization. In the race conditions, the model was verified during SEM races in Rotterdam where the race vehicle scored the result consistent with the results of simulation calculations. In the following years, the experience gathered by the team gave us the vice Championship in the SEM 2016 in London.

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Carruthers, J. J., M. Calomfirescu, P. Ghys, and J. Prockat. "The application of a systematic approach to material selection for the lightweighting of metro vehicles." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 223, no. 5 (June 17, 2009): 427–37. http://dx.doi.org/10.1243/09544097jrrt279.

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With reduced operational energy consumption as the primary driver, a cross-industry consortium of vehicle manufacturers has explored some of the issues surrounding the introduction of lightweight materials into metro vehicles. Taking today's vehicles as the starting point, the aim of the study was to examine the current barriers that need to be removed or overcome in order to realize the economic and environmental benefits of lightweight materials. From a technical perspective, the use of a systematic approach to material selection is described that matches the design requirements and constraints of a given application to potentially suitable candidate materials within a large database. The approach is illustrated by a case study in which a 57 per cent mass saving is achieved for a metro vehicle interior grab rail. Estimates are also provided for the magnitude of the operational energy and cost savings that can be achieved through metro vehicle lightweighting. For the particular scenario considered in this article, a 10 per cent reduction in vehicle mass was estimated to equate to a 7 per cent saving in energy consumption and a corresponding 100 000 € annual operational cost saving per vehicle. Such data can now be used to support decision making with respect to the benefits of lightweighting.

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Carvalho Barbosa, Rodrigo, Muhammad Shoaib Ayub, Renata Lopes Rosa, Demóstenes Zegarra Rodríguez, and Lunchakorn Wuttisittikulkij. "Lightweight PVIDNet: A Priority Vehicles Detection Network Model Based on Deep Learning for Intelligent Traffic Lights." Sensors 20, no. 21 (October 31, 2020): 6218. http://dx.doi.org/10.3390/s20216218.

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Minimizing human intervention in engines, such as traffic lights, through automatic applications and sensors has been the focus of many studies. Thus, Deep Learning (DL) algorithms have been studied for traffic signs and vehicle identification in an urban traffic context. However, there is a lack of priority vehicle classification algorithms with high accuracy, fast processing, and a lightweight solution. For filling those gaps, a vehicle detection system is proposed, which is integrated with an intelligent traffic light. Thus, this work proposes (1) a novel vehicle detection model named Priority Vehicle Image Detection Network (PVIDNet), based on YOLOV3, (2) a lightweight design strategy for the PVIDNet model using an activation function to decrease the execution time of the proposed model, (3) a traffic control algorithm based on the Brazilian Traffic Code, and (4) a database containing Brazilian vehicle images. The effectiveness of the proposed solutions were evaluated using the Simulation of Urban MObility (SUMO) tool. Results show that PVIDNet reached an accuracy higher than 0.95, and the waiting time of priority vehicles was reduced by up to 50%, demonstrating the effectiveness of the proposed solution.

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Jung, Yoon-Sik, Heon-Seop Shin, Sungsoo Rhim, and Jin-Hwan Choi. "Lightweight Suspension Module Development for Electric Vehicle." Transactions of the Korean Society of Mechanical Engineers A 37, no. 8 (August 1, 2013): 1015–19. http://dx.doi.org/10.3795/ksme-a.2013.37.8.1015.

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Kim, Yong, Ki-Young Park, and Kyoung-Don Lee. "Development of Welding Technologies for Lightweight Vehicle." Journal of the Korean Welding and Joining Society 29, no. 6 (December 31, 2011): 1–3. http://dx.doi.org/10.5781/kwjs.2011.29.6.621.

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Brown, M. D. "Book Review: Lightweight electric/hybrid vehicle design." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 215, no. 10 (October 2001): 1143. http://dx.doi.org/10.1243/0954407011528680.

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Ten Broek, Cees, Harry Singh, and Martin Hillebrecht. "Lightweight Design for the Future Steel Vehicle." Auto Tech Review 1, no. 11 (November 2012): 24–30. http://dx.doi.org/10.1365/s40112-012-0171-0.

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Milan, Benko, Kučera Ľuboš, and Smetánka Lukáš. "Front suspension design of the lightweight vehicle." Transportation Research Procedia 40 (2019): 623–30. http://dx.doi.org/10.1016/j.trpro.2019.07.089.

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HWANG, J., D. WANG, and N. SHIH. "Development of a lightweight fuel cell vehicle." Journal of Power Sources 141, no. 1 (February 16, 2005): 108–15. http://dx.doi.org/10.1016/j.jpowsour.2004.08.056.

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Ten Broek, Cees, Harry Singh, and Martin Hillebrecht. "Lightweight design for the future steel vehicle." ATZ worldwide 114, no. 5 (May 2012): 4–11. http://dx.doi.org/10.1007/s38311-012-0203-z.

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Hagebeuker, Leif, Kristian Seidel, and Lutz Eckstein. "Composite-intensive Lightweight Design in Vehicle Modules." ATZ worldwide 118, no. 11 (October 28, 2016): 30–35. http://dx.doi.org/10.1007/s38311-016-0116-3.

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Zhang, Yifan, Chiu C. Tan, Fengyuan Xu, Hao Han, and Qun Li. "VProof: Lightweight Privacy-Preserving Vehicle Location Proofs." IEEE Transactions on Vehicular Technology 64, no. 1 (January 2015): 378–85. http://dx.doi.org/10.1109/tvt.2014.2321666.

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Kurihara, Yuki. "Vehicle Weight Reduction Obtained with Lightweight Materials." JSME international journal. Ser. A, Mechanics and material engineering 38, no. 4 (October 15, 1995): 487–93. http://dx.doi.org/10.1299/jsmea1993.38.4_487.

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Li, Zhen, Qingkai Miao, Shehzad Ashraf Chaudhry, and Chien-Ming Chen. "A provably secure and lightweight mutual authentication protocol in fog-enabled social Internet of vehicles." International Journal of Distributed Sensor Networks 18, no. 6 (June 2022): 155013292211043. http://dx.doi.org/10.1177/15501329221104332.

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The Internet of vehicles technology has developed rapidly in recent years and has become increasingly important. The social Internet of vehicles provides better resources and services for the development of the Internet of vehicles and provides better experience for users. However, there are still many security problems in social vehicle networking environments. Once the vehicle is networked, the biggest problem is data security according to the three levels of data collection, intelligent analysis, and decision control of the Internet of vehicles. Recently, Wu et al. proposed a lightweight vehicle social network security authentication protocol based on fog nodes. They claimed that their security authentication protocol could resist various attacks. However, we found that their authentication protocols are vulnerable to internal attacks, smart card theft attacks, and lack perfect forward security. In this study, we propose a new protocol to overcome these limitations. Finally, security and performance analyses show that our protocol perfectly overcomes these limitations and exhibits excellent performance and efficiency.

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Ulianov, Cristian, Ramy Shaltout, and Adrian Ciprian Balan. "Lightweight Vehicle Structural Design with Advanced Steel Grades and Profiles." Applied Mechanics and Materials 809-810 (November 2015): 1199–204. http://dx.doi.org/10.4028/www.scientific.net/amm.809-810.1199.

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In the recent decades, the vehicle lighweighting problem has been addressed through various methodologies by different researchers and industries. Significant effort has been made recently to develop lightweight structural solutions by employing state-of-the-art and emerging materials, manufacturing processes and technologies. The presented research aimed to investigate the possibility of designing vehicle lightweight structures using advanced steel grades and novel structural profiles developed by industry by integrating smart design and manufacturing solutions. A case study was developed in the presented paper on a freight wagon structure. The structural stress analysis of the new lightweight design has been carried out through Finite Element Analysis (FEA) for validating the proposed solutions. The FEA considered the standard loading scenarios, taking into account both the static and dynamic operational loads, and the results were evaluated against the traditional design of a similar benchmark homologated vehicle. The results demonstrate that novel steel products can be successfully employed for designing sustainable and feasible lightweight vehicle structures.

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Ding, Ju Yue, and Jian Wang Shao. "Automotive Floor Sound Package Design Using Statistical Energy Analysis." Applied Mechanics and Materials 670-671 (October 2014): 1102–5. http://dx.doi.org/10.4028/www.scientific.net/amm.670-671.1102.

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An increasing demand for vehicle noise control has been proposed and at the same time, vehicle weight and fuel economy have become critical for the automotive industry. The methodology of statistical energy analysis (SEA) is used to balance both light weight and high noise insulation performance. In this paper, the floor system which is one of the major paths for vehicle interior noise is studied with two sound package systems, the original floor insulation system and the lightweight one. The vehicle floor system is modeled by SEA and its transmission loss (TL) is analyzed. The results show that under certain sound package coverage, the TL of the floor system with the lightweight sound package is a little larger than the TL with the lightweight one. However, the lightweight sound package system has better absorption property and the advantage of weight reduction. Finally, in order to get the better TL, the sound package design is performed.

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Basavaraj, Dheeraj, and Shahab Tayeb. "Towards a Lightweight Intrusion Detection Framework for In-Vehicle Networks." Journal of Sensor and Actuator Networks 11, no. 1 (January 10, 2022): 6. http://dx.doi.org/10.3390/jsan11010006.

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With the emergence of networked devices, from the Internet of Things (IoT) nodes and cellular phones to vehicles connected to the Internet, there has been an ever-growing expansion of attack surfaces in the Internet of Vehicles (IoV). In the past decade, there has been a rapid growth in the automotive industry as network-enabled and electronic devices are now integral parts of vehicular ecosystems. These include the development of automobile technologies, namely, Connected and Autonomous Vehicles (CAV) and electric vehicles. Attacks on IoV may lead to malfunctioning of Electronic Control Unit (ECU), brakes, control steering issues, and door lock issues that can be fatal in CAV. To mitigate these risks, there is need for a lightweight model to identify attacks on vehicular systems. In this article, an efficient model of an Intrusion Detection System (IDS) is developed to detect anomalies in the vehicular system. The dataset used in this study is an In-Vehicle Network (IVN) communication protocol, i.e., Control Area Network (CAN) dataset generated in a real-time environment. The model classifies different types of attacks on vehicles into reconnaissance, Denial of Service (DoS), and fuzzing attacks. Experimentation with performance metrics of accuracy, precision, recall, and F-1 score are compared across a variety of classification models. The results demonstrate that the proposed model outperforms other classification models.

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Hong, Sunghoon, and Daejin Park. "Runtime ML-DL Hybrid Inference Platform Based on Multiplexing Adaptive Space-Time Resolution for Fast Car Incident Prevention in Low-Power Embedded Systems." Sensors 22, no. 8 (April 14, 2022): 2998. http://dx.doi.org/10.3390/s22082998.

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Forward vehicle detection is the key technique to preventing car incidents in front. Artificial intelligence (AI) techniques are used to more accurately detect vehicles, but AI-based vehicle detection takes a lot of processing time due to its high computational complexity. When there is a risk of collision with a vehicle in front, the slow detection speed of the vehicle may lead to an accident. To quickly detect a vehicle in real-time, a high-speed and lightweight vehicle detection technique with similar detection performance to that of an existing AI-based vehicle detection is required. In addition, to apply forward collision warning system (FCWS) technology to vehicles, it is important to provide high performance based on low-power embedded systems because the vehicle’s battery consumption must remain low. The vehicle detection algorithm occupies the most resources in FCWS. To reduce power consumption, it is important to reduce the computational complexity of an algorithm, that is, the amount of resources required to run it. This paper describes a method for fast, accurate forward vehicle detection using machine learning and deep learning. To detect a vehicle in consecutive images consistently, a Kalman filter is used to predict the bounding box based on the tracking algorithm and correct it based on the detection algorithm. As a result, its vehicle detection speed is about 25.85 times faster than deep-learning-based object detection is, and its detection accuracy is better than machine-learning-based object detection is.

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Yu, Li Li, Zhen Hua Su, Jing Zhan Lin, Yu Sen Yuan, Chun Xiang Cui, and Ling Yu. "Effect of Multi-Material Substitutions on Static and Dynamic Properties of Electric Vehicles." Advanced Materials Research 535-537 (June 2012): 1402–7. http://dx.doi.org/10.4028/www.scientific.net/amr.535-537.1402.

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Automotive weight reduction is a challenging task due to many performance targets that must be satisfied simultaneously, in particular in terms of static and dynamic properties direct relating to strength, stiffness and NVH characteristics of vehicles. Compared to all-steel vehicle frame, multi-material substitutions are adopted in each structural component for higher product performance and a lightweight electric vehicle frame in this paper. The SHELL63 element is selected to construct finite element (FE) model of vehicle frame based on the FEA software ANSYS. Under full bending loading and torsional loading respectively, static analysis of frame is performed, and the strength and stiffness are evaluated as well. The Block Lanczos is adopted for dynamic analysis of vehicle frame. Their first eight modal properties are obtained and far away exciting frequency range of rough road. The multi-material vehicle frame has been designed to be made of mild steel, aluminum and magnesium alloys. Its static and dynamic properties show that the strength, stiffness and NVH characteristics are better than ones from all-steel vehicle frame with weight reduction of 31.7%. These procedures will help to design a lightweight and thus to provide technical support for reducing fuel consumption and greenhouse gas emissions.

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Journal articles on the topic 'Lightweight vehicle'

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