Jichao Li, Xuexin Zhu, Cong Zhang, Shiwang Dang, Guang Chen^*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.9, pp. 2305-2329, 2025, DOI:10.32604/fdmp.2025.067087 - 30 September 2025

Abstract The rapid advancement of technology and the increasing speed of vehicles have led to a substantial rise in energy consumption and growing concern over environmental pollution. Beyond the promotion of new energy vehicles, reducing aerodynamic drag remains a critical strategy for improving energy efficiency and lowering emissions. This study investigates the influence of key geometric parameters on the aerodynamic drag of vehicles. A parametric vehicle model was developed, and computational fluid dynamics (CFD) simulations were conducted to analyse variations in the drag coefficient () and pressure distribution across different design configurations. The results reveal that More >

Shih-Lin Lin^*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1365-1382, 2025, DOI:10.32604/cmc.2025.067764 - 29 August 2025

Abstract This paper proposes an integrated multi-stage framework to enhance frequency modulated continuous wave (FMCW) automotive radar performance under high noise and interference. The four-stage pipeline is applied consecutively: (i) an improved independent component analysis (ICA) blindly separates the two-channel echoes, isolating target and interference components; (ii) a recursive least-squares (RLS) filter compensates amplitude- and phase-mismatches, restoring signal fidelity; (iii) variational mode decomposition (VMD) followed by the Hilbert-Huang Transform (HHT) extracts noise-free intrinsic mode functions (IMFs) and sharpens their time-frequency signatures; and (iv) HHT-based beat-frequency estimation reconstructs a clean echo and delivers accurate range information. Finally, More >

Pallabi Biswas^1,#, Samarendra Nath Sur^2,#,*, Rabindranath Bera³, Agbotiname Lucky Imoize⁴, Chun-Ta Li^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 83-146, 2025, DOI:10.32604/cmes.2025.067724 - 31 July 2025

Abstract Automotive radar has emerged as a critical component in Advanced Driver Assistance Systems (ADAS) and autonomous driving, enabling robust environmental perception through precise range-Doppler and angular measurements. It plays a pivotal role in enhancing road safety by supporting accurate detection and localization of surrounding objects. However, real-world deployment of automotive radar faces significant challenges, including mutual interference among radar units and dense clutter due to multiple dynamic targets, which demand advanced signal processing solutions beyond conventional methodologies. This paper presents a comprehensive review of traditional signal processing techniques and recent advancements specifically designed to address… More > Graphic Abstract

Jian Ge¹, Qin Qin^1,*, Jinhua Jiang¹, Zhiwei Shen², Zimei Tu¹, Yahui Zhang¹

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3211-3226, 2025, DOI:10.32604/cmc.2025.059389 - 16 April 2025

Abstract Manufacturers must identify and classify various defects in automotive sealing rings to ensure product quality. Deep learning algorithms show promise in this field, but challenges remain, especially in detecting small-scale defects under harsh industrial conditions with multimodal data. This paper proposes an enhanced version of You Only Look Once (YOLO)v8 for improved defect detection in automotive sealing rings. We introduce the Multi-scale Adaptive Feature Extraction (MAFE) module, which integrates Deformable Convolutional Network (DCN) and Space-to-Depth (SPD) operations. This module effectively captures long-range dependencies, enhances spatial aggregation, and minimizes information loss of small objects during feature More >

Md Naeem Hossain¹, Md. Abdur Rahim², Md Mustafizur Rahman^1,3,*, Devarajan Ramasamy¹

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 3643-3692, 2025, DOI:10.32604/cmc.2025.061749 - 06 March 2025

Abstract The automotive sector is crucial in modern society, facilitating essential transportation needs across personal, commercial, and logistical domains while significantly contributing to national economic development and employment generation. The transformative impact of Artificial Intelligence (AI) has revolutionised multiple facets of the automotive industry, encompassing intelligent manufacturing processes, diagnostic systems, control mechanisms, supply chain operations, customer service platforms, and traffic management solutions. While extensive research exists on the above aspects of AI applications in automotive contexts, there is a compelling need to synthesise this knowledge comprehensively to guide and inspire future research. This review introduces a… More >

Binyong Li^1,2,3, Liangming Deng^1,*, Jie Zhang¹, Xianhui Deng¹

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 407-426, 2025, DOI:10.32604/cmc.2024.056730 - 03 January 2025

Abstract To solve the challenges of connecting and coordinating multiple platforms in the automotive industry and to enhance collaboration among different participants, this research focuses on addressing the complex supply relationships in the automotive market, improving data sharing and interactions across various platforms, and achieving more detailed integration of data and operations. We propose a trust evaluation permission delegation method based on the automotive industry chain. The proposed method combines smart contracts with trust evaluation mechanisms, dynamically calculating the trust value of users based on the historical behavior of the delegated entity, network environment, and other More >

Khadija El Fellah^1,*, Ikram El Azami^2,*, Adil El Makrani², Habiba Bouijij³, Oussama El Azzouzy⁴

Computer Systems Science and Engineering, Vol.49, pp. 99-122, 2025, DOI:10.32604/csse.2024.057754 - 03 January 2025

Abstract The rapid growth of the automotive industry has raised significant concerns about the security of connected vehicles and their integrated supply chains, which are increasingly vulnerable to advanced cyber threats. Traditional authentication methods have proven insufficient, exposing systems to risks such as Sybil, Denial of Service (DoS), and Eclipse attacks. This study critically examines the limitations of current security protocols, focusing on authentication and data exchange vulnerabilities, and explores blockchain technology as a potential solution. Blockchain’s decentralized and cryptographically secure framework can significantly enhance Vehicle-to-Vehicle (V2V) communication, ensure data integrity, and enable transparent, immutable transactions More >

Yongbing Li^1,*, Yunwu Ma¹, Yujun Xia¹, Ming Lou¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012602

Abstract The implementation of lightweight materials and structures in automotive body manufacturing is a strategic approach to improve fuel efficiency of energy-efficient vehicles and driving range of new energy vehicles. However, high specific strength low-ductility light metals (like 7xxx aluminum, magnesium and cast aluminum), ultra-high strength steels, high-stiffness profile structures and their mixed use poses a big challenge to existing commercial spot joining processes, such as resistance spot welding and self-piercing riveting. In this talk, the challenges which new lightweight materials and structures pose to spot joining process will be presented, the bottleneck of the existing More >

Muhammad Azhar Ali Khan¹, Syed Sohail Akhtar^2,3,*, Abba A. Abubakar^2,4, Muhammad Asad¹, Khaled S. Al-Athel^2,5

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2325-2350, 2024, DOI:10.32604/cmes.2024.054741 - 31 October 2024

Abstract The fatigue life and reliability of wrought carbon steel castings produced with an optimized mold design are predicted using a finite element method integrated with reliability calculations. The optimization of the mold is carried out using MAGMASoft mainly based on porosity reduction as a response. After validating the initial mold design with experimental data, a spring flap, a common component of an automotive suspension system is designed and optimized followed by fatigue life prediction based on simulation using Fe-safe. By taking into consideration the variation in both stress and strength, the stress-strength model is used… More >

Carmen Gheorghe^*, Mihai Duguleana, Razvan Gabriel Boboc, Cristian Cezar Postelnicu

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 1939-1981, 2024, DOI:10.32604/cmes.2024.054735 - 31 October 2024

Abstract Identifying objects in real-time is a technology that is developing rapidly and has a huge potential for expansion in many technical fields. Currently, systems that use image processing to detect objects are based on the information from a single frame. A video camera positioned in the analyzed area captures the image, monitoring in detail the changes that occur between frames. The You Only Look Once (YOLO) algorithm is a model for detecting objects in images, that is currently known for the accuracy of the data obtained and the fast-working speed. This study proposes a comprehensive More >