Shuwei Zhong, Yanbo Che^*, Shangyuan Zhang

Energy Engineering, Vol.121, No.3, pp. 603-618, 2024, DOI:10.32604/ee.2023.044667

Abstract Electric vehicle (EV) is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future. However, a large number of EVs will be concentrated on charging during the valley hours leading to new load peaks under the guidance of static time-of-use tariff. Therefore, this paper proposes a dynamic time-of-use tariff mechanism, which redefines the peak and valley time periods according to the predicted loads using the fuzzy C-mean (FCM) clustering algorithm, and then dynamically adjusts the peak and valley tariffs according to the actual load of each time period. Based on the proposed… More >

Yixuan Yu, Yulin Wang^*, Qingcheng Li, Bowen Jiao

Energy Engineering, Vol.121, No.3, pp. 769-788, 2024, DOI:10.32604/ee.2023.044042

Abstract The plug-in hybrid vehicles (PHEV) technology can effectively address the issues of poor dynamics and higher energy consumption commonly found in traditional mining dump trucks. Meanwhile, plug-in hybrid electric trucks can achieve excellent fuel economy through efficient energy management strategies (EMS). Therefore, a series hybrid system is constructed based on a 100-ton mining dump truck in this paper. And inspired by the dynamic programming (DP) algorithm, a predictive equivalent consumption minimization strategy (P-ECMS) based on the DP optimization result is proposed. Based on the optimal control manifold and the SOC reference trajectory obtained by the DP algorithm, the P-ECMS strategy… More >

Jian Pang^1,3, Tingting Mao², Wenyu Jia³, Xiaoli Jia^3,*, Peisong Dai², Haibo Huang^1,2,*

Sound & Vibration, Vol.58, pp. 59-80, 2024, DOI:10.32604/sv.2024.046247

Abstract Currently, the inexorable trend toward the electrification of automobiles has heightened the prominence of road noise within overall vehicle noise. Consequently, an in-depth investigation into automobile road noise holds substantial practical importance. Previous research endeavors have predominantly centered on the formulation of mechanism models and data-driven models. While mechanism models offer robust controllability, their application encounters challenges in intricate analyses of vehicle body acoustic-vibration coupling, and the effective utilization of accumulated data remains elusive. In contrast, data-driven models exhibit efficient modeling capabilities and can assimilate conceptual vehicle knowledge, but they impose stringent requirements on both data quality and quantity. In… More >

Zhiheng He¹, Hui Guo², Houguang Liu^1,*, Yu Zhao^1,3, Zipeng Zhang¹, Shanguo Yang¹

Sound & Vibration, Vol.58, pp. 47-58, 2024, DOI:10.32604/sv.2024.045470

Abstract When designing and optimizing the hull of vehicles, their sound quality needs to be considered, which greatly depends on the psychoacoustic parameters. However, the traditional psychoacoustic calculation method does not consider the influence of the real human ear anatomic structure, even the loudness which is most related to the auditory periphery. In order to introduce the real physiological structure of the human ear into the evaluation of vehicle sound quality, this paper first carried out the vehicle internal noise test to obtain the experimental samples. Then, the physiological loudness was predicted based on an established human ear physiological model, and… More >

Cheng Peng¹, Siwei Cheng², Min Sun¹, Chao Ren¹, Jun Song¹, Haibo Huang^2,*

Sound & Vibration, Vol.58, pp. 25-46, 2024, DOI:10.32604/sv.2024.046940

Abstract The Noise, Vibration, and Harshness (NVH) experience during driving is significantly influenced by the sound insulation performance of the car floor acoustic package. As such, accurate and efficient predictions of its sound insulation performance are crucial for optimizing related noise reduction designs. However, the complex acoustic transmission mechanisms and difficulties in characterizing the sound absorption and insulation properties of the floor acoustic package pose significant challenges to traditional Computer-Aided Engineering (CAE) methods, leading to low modeling efficiency and prediction accuracy. To address these limitations, a hierarchical multi-objective decomposition system for predicting the sound insulation performance of the floor acoustic package… More >

Jiarui Deng^1,2, Wuqiang Shen^1,3, Yihua Feng⁴, Guosheng Lu⁵, Guiquan Shen^1,3, Lei Cui^1,3, Shanxiang Lyu^1,2,*

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1345-1361, 2024, DOI:10.32604/cmc.2023.047079

Abstract The blockchain-empowered Internet of Vehicles (IoV) enables various services and achieves data security and privacy, significantly advancing modern vehicle systems. However, the increased frequency of data transmission and complex network connections among nodes also make them more susceptible to adversarial attacks. As a result, an efficient intrusion detection system (IDS) becomes crucial for securing the IoV environment. Existing IDSs based on convolutional neural networks (CNN) often suffer from high training time and storage requirements. In this paper, we propose a lightweight IDS solution to protect IoV against both intra-vehicle and external threats. Our approach achieves superior performance, as demonstrated by… More >

Yaoyao Du, Xiangkui Jiang^*

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 303-327, 2024, DOI:10.32604/cmc.2023.046068

Abstract To address the challenges of high complexity, poor real-time performance, and low detection rates for small target vehicles in existing vehicle object detection algorithms, this paper proposes a real-time lightweight architecture based on You Only Look Once (YOLO) v5m. Firstly, a lightweight upsampling operator called Content-Aware Reassembly of Features (CARAFE) is introduced in the feature fusion layer of the network to maximize the extraction of deep-level features for small target vehicles, reducing the missed detection rate and false detection rate. Secondly, a new prediction layer for tiny targets is added, and the feature fusion network is redesigned to enhance the… More >

Tianmin Deng^*, Xiyue Zhang, Xinxin Cheng

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 533-549, 2024, DOI:10.32604/cmc.2023.044639

Abstract Vehicle detection plays a crucial role in the field of autonomous driving technology. However, directly applying deep learning-based object detection algorithms to complex road scene images often leads to subpar performance and slow inference speeds in vehicle detection. Achieving a balance between accuracy and detection speed is crucial for real-time object detection in real-world road scenes. This paper proposes a high-precision and fast vehicle detector called the feature-guided bidirectional pyramid network (FBPN). Firstly, to tackle challenges like vehicle occlusion and significant background interference, the efficient feature filtering module (EFFM) is introduced into the deep network, which amplifies the disparities between… More >

Deyong Shang^1,2, Xi Zhang¹, Fengqi Liang¹, Chunde Zhai¹, Hang Yang¹, Yanqi Niu^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2027-2041, 2024, DOI:10.32604/cmes.2023.045750

Abstract When the amphibious vehicle navigates in water, the angle of the anti-wave plate and the position of the center of gravity greatly influence the navigation characteristics. In the relevant research on reducing the navigation resistance of amphibious vehicles by adjusting the angle of the anti-wave plate, there is a lack of scientific selection of parameters and reasonable research of simulation results by using mathematical methods, and the influence of the center of gravity position on navigation characteristics is not considered at the same time. To study the influence of the combinations of the angle of the anti-wave plate and the… More >

Xingwang Li^1,2, Hua Pang¹, Geng Li^1,*, Junjie Jiang¹, Hui Zhang³, Changfei Gu⁴, Dong Yuan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1135-1166, 2024, DOI:10.32604/cmes.2023.031534

Abstract The development of the fifth-generation (5G) mobile communication systems has entered the commercialization stage. 5G has a high data rate, low latency, and high reliability that can meet the basic demands of most industries and daily life, such as the Internet of Things (IoT), intelligent transportation systems, positioning, and navigation. The continuous progress and development of society have aroused wide concern. Positioning accuracy is the core demand for the applications, especially in complex environments such as airports, warehouses, supermarkets, and basements. However, many factors also affect the accuracy of positioning in those environments, for example, multipath effects, non-line-of-sight, and clock… More >