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Active and Passive Safety and Noise, Vibration, and Harshness (NVH)...
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Active and Passive Safety and Noise, Vibration, and Harshness (NVH) of Intelligent Vehicles

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Vehicle Engineering".

Deadline for manuscript submissions: 28 February 2026 | Viewed by 2224

Special Issue Editors

Dr. Yan Wang

E-Mail Website
Guest Editor
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Interests: vehicle active safety control; vehicle state estimation; human machine shared control
Dr. Hui Zhang

E-Mail Website
Guest Editor
School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China
Interests: collaborative detection of multi-sensor fusion; multi-modal object detection
Prof. Dr. Lanchun Zhang

E-Mail Website
Guest Editor
School of Automotive and Traffic Engineering, Jiangsu University of Technology, Changzhou 213001, China
Interests: new energy vehicle control and optimisation; new energy vehicle energy management
Dr. Liwei Xu

E-Mail Website
Guest Editor
School of Mechanical Engineering, Southeast University, Nanjing, China
Interests: vehicle dynamics and control; intelligent and connected vehicles
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid evolution of intelligent vehicles, driven by advanced technologies such as AI, sensors, and connectivity, has significantly transformed the landscape of automotive safety and comfort. In parallel with the development of autonomous and semi-autonomous systems, the importance of integrating both active and passive safety mechanisms has never been more critical. Furthermore, the focus on Noise, Vibration, and Harshness (NVH) has become a crucial aspect of enhancing the user experience in intelligent vehicles. This Special Issue aims to explore the state-of-the-art advancements in both active and passive safety systems and their integration with NVH in intelligent vehicles. Active safety systems, such as collision avoidance, adaptive cruise control, and lane-keeping assist, aim to prevent accidents by intervening in real-time to assist the driver or take over critical functions. Meanwhile, passive safety focuses on structural integrity, seatbelt technologies, and airbag systems to protect occupants in the event of a collision. Combined with NVH studies, which delve into noise reduction, vibration control, and the mitigation of harshness for a smoother ride, these elements contribute to improving the safety, comfort, and overall performance of modern vehicles. This Special Issue will provide a comprehensive platform for presenting novel research, case studies, and the latest technological advancements that address the intersection of safety and NVH challenges in intelligent vehicles. The focus will include both theoretical studies and practical applications of these concepts.

Research topics that are of interest for this Special Issue include but are not limited to the following:

Autonomous driving safety mechanisms and decision-making algorithms.

Integration of machine learning and sensor fusion in active safety.

Collision avoidance systems and advanced driver assistance systems.

Structural design improvements for crashworthiness.

Impact analysis and occupant protection in various crash scenarios.

Multi-material structures for lightweight and safety optimization.

Advancements in electric, hybrid, and internal combustion engines.

Integration of engine technologies in autonomous and electric vehicles.

NVH control methods for electric and autonomous vehicles.

Vibration reduction technologies for enhanced ride comfort.

Noise isolation techniques in cabin design.

Acoustic modeling and simulations for interior noise control.

Dr. Yan Wang
Dr. Hui Zhang
Prof. Dr. Lanchun Zhang
Dr. Liwei Xu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • intelligent vehicles
  • active safety systems
  • passive safety systems
  • autonomous driving
  • noise vibration  Harshness (NVH)
  • vehicle dynamics and control
  • electric and autonomous vehicles

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Published Papers (3 papers)

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Research

31 pages, 5103 KiB  
Article
Multi-Objective Optimization of Battery Pack Mounting System for Construction Machinery
by Dunhuang Lin, Run Sun, Hai Wei and Yujiang Wang
Machines 2025, 13(8), 705; https://doi.org/10.3390/machines13080705 - 9 Aug 2025
Viewed by 170
Abstract
With the accelerated electrification of engineering machinery, the battery pack mounting system plays a critical role in enhancing the vehicle’s structural safety and vibration-damping performance. This paper proposes an optimization framework for the multi-layer battery pack mounting systems used in such machinery. The [...] Read more.
With the accelerated electrification of engineering machinery, the battery pack mounting system plays a critical role in enhancing the vehicle’s structural safety and vibration-damping performance. This paper proposes an optimization framework for the multi-layer battery pack mounting systems used in such machinery. The framework integrates a multi-degree-of-freedom (MDOF) dynamic model, uncertainty analysis, and a multi-objective evolutionary algorithm (MOEA) to resolve the vibration suppression challenges associated with large-mass battery packs under harsh operating conditions. A parameter optimization method is introduced with the objectives of increasing natural frequencies, enhancing modal decoupling, and avoiding resonance. By identifying key influencing parameters and performing a comprehensive optimization of mount locations and stiffness, this approach achieves a highly efficient improvement in dynamic performance. Simulation and analysis results demonstrate that, compared to the initial design, the proposed method significantly elevates the system’s first six natural frequencies (by 13.6%, 7.8%, 3.3%, 2.5%, 11.7%, and 9.4%, respectively). Furthermore, it enhances the energy decoupling between modes, with the decoupling rates for Y-direction translation and Z-axis rotation both increasing by 11.3%. This achieves a synergistic improvement in the system’s vibration avoidance and decoupling performance. The methodology offers an effective means to optimize the safety and operational stability of battery systems in electric engineering machinery. Full article
(This article belongs to the Special Issue Active and Passive Safety and Noise, Vibration, and Harshness (NVH) of Intelligent Vehicles)
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17 pages, 5504 KiB  
Article
Multi-Objective Optimization of Acoustic Black Hole Plate Attached to Electric Automotive Steering Machine for Maximizing Vibration Attenuation Performance
by Xiaofei Du, Weilong Li, Fei Hao and Qidi Fu
Machines 2025, 13(8), 647; https://doi.org/10.3390/machines13080647 - 24 Jul 2025
Viewed by 357
Abstract
This research introduces an innovative passive vibration control methodology employing acoustic black hole (ABH) structures to mitigate vibration transmission in electric automotive steering machines—a prevalent issue adversely affecting driving comfort and vehicle safety. Leveraging the inherent bending wave manipulation properties of ABH configurations, [...] Read more.
This research introduces an innovative passive vibration control methodology employing acoustic black hole (ABH) structures to mitigate vibration transmission in electric automotive steering machines—a prevalent issue adversely affecting driving comfort and vehicle safety. Leveraging the inherent bending wave manipulation properties of ABH configurations, we conceive an integrated vibration suppression framework synergizing advanced computational modeling with intelligent optimization algorithms. A high-fidelity finite element (FEM) model integrating ABH-attached steering machine system was developed and subjected to experimental validation via rigorous modal testing. To address computational challenges in design optimization, a hybrid modeling strategy integrating parametric design (using Latin Hypercube Sampling, LHS) with Kriging surrogate modeling is proposed. Systematic parameterization of ABH geometry and damping layer dimensions generated 40 training datasets and 12 validation datasets. Surrogate model verification confirms the model’s precise mapping of vibration characteristics across the design space. Subsequent multi-objective genetic algorithm optimization targeting RMS velocity suppression achieved substantial vibration attenuation (29.2%) compared to baseline parameters. The developed methodology provides automotive researchers and engineers with an efficient suitable design tool for vibration-sensitive automotive component design. Full article
(This article belongs to the Special Issue Active and Passive Safety and Noise, Vibration, and Harshness (NVH) of Intelligent Vehicles)
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27 pages, 4076 KiB  
Article
Horizontal and Vertical Coordinated Control of Three-Axis Heavy Vehicles
by Lanchun Zhang, Fei Huang, Hao Cui, Yaqi Wang and Lin Yang
Machines 2025, 13(2), 123; https://doi.org/10.3390/machines13020123 - 7 Feb 2025
Viewed by 844
Abstract
In order to coordinate the transverse motion control and longitudinal motion control in the tracking control process and ensure the yaw stability and roll stability in the tracking process, a transverse and longitudinal coordinated control method of three-axis heavy vehicles is designed based [...] Read more.
In order to coordinate the transverse motion control and longitudinal motion control in the tracking control process and ensure the yaw stability and roll stability in the tracking process, a transverse and longitudinal coordinated control method of three-axis heavy vehicles is designed based on model predictive control. The lateral motion controller is designed based on the phase plane method. The upper controller calculates the front wheel angle and additional yaw moment, which ensures the yaw stability while tracking the vehicle. The lower controller calculates the driving force and braking force of the three-axis heavy vehicle. The velocity planning method is designed with the coupling point of longitudinal velocity to coordinate the lateral and longitudinal motion controllers and prevent vehicle rollover. By building the vehicle model in Trucksim (2016.1) and establishing the horizontal and vertical coordination control in Matlab (R2016b), the designed horizontal and vertical coordination control method is simulated and verified. The simulation results show that the designed method can accurately track the reference trajectory while ensuring the yaw stability and roll stability of the three-axis heavy vehicle. Full article
(This article belongs to the Special Issue Active and Passive Safety and Noise, Vibration, and Harshness (NVH) of Intelligent Vehicles)
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