New Journeys in Vehicle System Dynamics and Control

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

Deadline for manuscript submissions: 31 December 2025 | Viewed by 1860

Special Issue Editors


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Guest Editor
School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Interests: vibration control; acoustics and vibration; energy harvesting; computational methods; vehicle engineering; structural design and dynamic analysis; nonlinear vibrations; mechanical impedance; inerter; acoustics metamaterial

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Guest Editor
Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong
Interests: vehicle engineering; vibration control; energy harvesting; vehicle system dynamics

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Guest Editor
State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu, China
Interests: vehicle system dynamics; stability and control theory; rigid–flexible dynamics; vibration fatigue

Special Issue Information

Dear Colleagues,

As vehicles become increasingly electrified and intelligent, the dynamics and control of vehicle systems are encountering new challenges. Concurrently, the nonlinear dynamic behavior of complex systems remains at the forefront of current research. It is essential to explore and highlight the latest advancements in this field. The innovations and revolutionary possibilities merit publication and should be shared among colleagues. This Special Issue will provide a comprehensive platform for presenting novel research, case studies, and the latest technological advancements that address the challenges of vehicle dynamics and control in the science word. These include the folling: automotives, railway vehicles, motorcycles, vertical takeoff and landing (VTOL), and special vehicles. The focus will encompass both theoretical studies and practical applications of these concepts.

This topic is closely aligned with the scope of vehicle engineering in Machines, focusing on the publication of innovative technologies applicable to a diverse range of vehicles, including automobiles, trains, and vertical takeoff and landing (VTOL). Additionally, it encompasses advanced technologies that are integral to vehicle system dynamics, such as vibration and noise control, as well as active and semi-active control.

Dr. Changning Liu
Dr. Yi Yang
Dr. Lai Wei
Guest Editors

Manuscript Submission Information

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Keywords

  • grounded vehicle
  • railway vehicle
  • VTOL
  • dynamic analysis
  • vibration control
  • stability and control
  • active or semi-active control
  • energy harvesting
  • acoustics and vibration
  • nonlinear vibrations

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Published Papers (5 papers)

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Research

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14 pages, 2728 KB  
Article
Performance Analysis of Vehicle EM–ISD Suspension Considering Parasitic Damping
by Zhihong Jia, Yanling Liu, Yujie Shen, Chen Luo and Xiaofeng Yang
Machines 2025, 13(8), 690; https://doi.org/10.3390/machines13080690 - 6 Aug 2025
Viewed by 386
Abstract
In the practical physical structure of the electromagnetic inerter–spring–damper (EM–ISD) suspension, parasitic damping inevitably coexists with the mechanical inerter effect. To investigate the intrinsic influence of this parasitic effect on the suspension system’s performance, this study first establishes a quarter-vehicle dynamic model that [...] Read more.
In the practical physical structure of the electromagnetic inerter–spring–damper (EM–ISD) suspension, parasitic damping inevitably coexists with the mechanical inerter effect. To investigate the intrinsic influence of this parasitic effect on the suspension system’s performance, this study first establishes a quarter-vehicle dynamic model that incorporates parasitic damping, based on the actual configuration of the EM–ISD suspension. Subsequently, the particle swarm optimization (PSO) algorithm is employed to optimize the key suspension parameters, with the objective of enhancing its comprehensive performance. The optimized parameters are then utilized to systematically analyze the dynamic characteristics of the suspension under the influence of parasitic damping. The results indicate that, compared to an ideal model that neglects parasitic damping, an increase in the parasitic damping coefficient leads to a deterioration in the root mean square (RMS) value of body acceleration, while concurrently reducing the RMS values of the suspension working space and dynamic tire load. However, by incorporating parasitic damping into the design considerations during the optimization phase, its adverse impact on ride comfort can be effectively mitigated. Compared with a traditional passive suspension, the optimized EM–ISD suspension, which accounts for parasitic damping, demonstrates superior performance. Specifically, the RMS values of body acceleration and suspension working space are significantly reduced by 11.1% and 17.6%, respectively, thereby effectively improving the vehicle’s ride comfort and handling stability. Full article
(This article belongs to the Special Issue New Journeys in Vehicle System Dynamics and Control)
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28 pages, 6846 KB  
Article
Phase–Frequency Cooperative Optimization of HMDV Dynamic Inertial Suspension System with Generalized Ground-Hook Control
by Yihong Ping, Xiaofeng Yang, Yi Yang, Yujie Shen, Shaocong Zeng, Shihang Dai and Jingchen Hong
Machines 2025, 13(7), 556; https://doi.org/10.3390/machines13070556 - 26 Jun 2025
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Abstract
Hub motor-driven vehicles (HMDVs) suffer from poor handling and stability due to an increased unsprung mass and unbalanced radial electromagnetic forces. Although traditional ground-hook control reduces the dynamic tire load, it severely worsens the body acceleration. This paper presents a generalized ground-hook control [...] Read more.
Hub motor-driven vehicles (HMDVs) suffer from poor handling and stability due to an increased unsprung mass and unbalanced radial electromagnetic forces. Although traditional ground-hook control reduces the dynamic tire load, it severely worsens the body acceleration. This paper presents a generalized ground-hook control strategy based on impedance transfer functions to address the parameter redundancy in structural methods. A quarter-vehicle model with a switched reluctance motor wheel hub drive was used to study different orders of generalized ground-hook impedance transfer function control strategies for dynamic inertial suspension. An enhanced fish swarm parameter optimization method identified the optimal solutions for different structural orders. Analyses showed that the third-order control strategy optimized the body acceleration by 2%, reduced the dynamic tire load by 8%, and decreased the suspension working space by 22%. This strategy also substantially lowered the power spectral density for the body acceleration and dynamic tire load in the low-frequency band of 1.2 Hz. Additionally, it balanced computational complexity and performance, having slightly higher complexity than lower-order methods but much less than higher-order structures, meeting real-time constraints. To address time-domain deviations from generalized ground-hook control in semi-active systems, a dynamic compensation strategy was proposed: eight topological structures were created by modifying the spring–damper structure. A deviation correction mechanism was devised based on the frequency-domain coupling characteristics between the wheel speed and suspension relative velocity. For ride comfort and road-friendliness, a dual-frequency control criterion was introduced: in the low-frequency range, energy transfer suppression and phase synchronization locking were realized by constraining the ground-hook damping coefficient or inertance coefficient, while in the high-frequency range, the inertia-dominant characteristic was enhanced, and dynamic phase adaptation was permitted to mitigate road excitations. The results show that only the T0 and T5 structures met dynamic constraints across the frequency spectrum. Time-domain simulations showed that the deviation between the T5 structure and the third-order generalized ground-hook impedance model was relatively small, outperforming traditional and T0 structures, validating the model’s superior adaptability in high-order semi-active suspension. Full article
(This article belongs to the Special Issue New Journeys in Vehicle System Dynamics and Control)
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Review

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35 pages, 1234 KB  
Review
A Survey of Autonomous Driving Trajectory Prediction: Methodologies, Challenges, and Future Prospects
by Miao Xu, Zhi Liu, Bingyi Wang and Shengyan Li
Machines 2025, 13(9), 818; https://doi.org/10.3390/machines13090818 (registering DOI) - 6 Sep 2025
Abstract
Trajectory prediction is a critical component of autonomous driving decision-making systems, directly impacting driving safety and traffic efficiency. Despite advancements, existing reviews exhibit limitations in timeliness, classification frameworks, and challenge analysis. This paper systematically reviews multi-agent trajectory prediction technologies, focusing on generating future [...] Read more.
Trajectory prediction is a critical component of autonomous driving decision-making systems, directly impacting driving safety and traffic efficiency. Despite advancements, existing reviews exhibit limitations in timeliness, classification frameworks, and challenge analysis. This paper systematically reviews multi-agent trajectory prediction technologies, focusing on generating future position sequences from historical trajectories, high-precision maps, and scene context. We propose a multi-dimensional classification framework integrating input representation, output forms, method paradigms, and interaction modeling. The review comprehensively compares conventional methods and deep learning architectures, including diffusion models and large language models. We further analyze five core challenges: complex interactions, rule and map dependence, long-term prediction errors, extreme-scene generalization, and real-time constraints. Finally, interdisciplinary solutions are prospectively explored. Full article
(This article belongs to the Special Issue New Journeys in Vehicle System Dynamics and Control)
40 pages, 3903 KB  
Review
A Review on the Application of Inerters in Vehicle Suspension Systems
by Xiaofeng Yang, Tianyi Zhang, Yongchao Li, Yujie Shen, Yanling Liu and Changzhuang Chen
Machines 2025, 13(9), 779; https://doi.org/10.3390/machines13090779 - 30 Aug 2025
Viewed by 206
Abstract
The inerter is a device that produces a force proportional to the relative acceleration of both inerter terminals. When combined with springs and dampers in a vehicle suspension system, it forms an inerter–spring–damper (ISD) suspension. This structure shows significant advantages in improving vehicle [...] Read more.
The inerter is a device that produces a force proportional to the relative acceleration of both inerter terminals. When combined with springs and dampers in a vehicle suspension system, it forms an inerter–spring–damper (ISD) suspension. This structure shows significant advantages in improving vehicle ride comfort and road friendliness. This paper systematically reviews research progress on ISD suspension. First, the working principle and structural types of the inerter are introduced. Then, an overview of the breakdown phenomena and nonlinear characteristics of ISD suspension is provided, followed by a systematic analysis of ISD suspension structure designs. Next, the control strategies for ISD suspension are discussed, along with their applications in the automotive field. Finally, the paper outlines the main challenges in current inerter research and explores its potential applications in vehicle suspensions. This work can provide a reference for the development of inerter and ISD suspension technologies. Full article
(This article belongs to the Special Issue New Journeys in Vehicle System Dynamics and Control)
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37 pages, 3983 KB  
Review
Fault Diagnosis of In-Wheel Motors Used in Electric Vehicles: State of the Art, Challenges, and Future Directions
by Yukun Tao, Xuan Wang, Liang Zhang, Xiaoyi Bao, Hongtao Xue, Huiyu Yue, Huayuan Feng and Dongpo Yang
Machines 2025, 13(8), 711; https://doi.org/10.3390/machines13080711 - 11 Aug 2025
Viewed by 470
Abstract
In-wheel motors (IWMs) have become a promising solution for electric vehicles due to their compact design, high integration, and flexible torque control. However, their exposure to harsh operating conditions increases the risk of mechanical, electrical, and magnetic faults, making reliable fault diagnosis essential [...] Read more.
In-wheel motors (IWMs) have become a promising solution for electric vehicles due to their compact design, high integration, and flexible torque control. However, their exposure to harsh operating conditions increases the risk of mechanical, electrical, and magnetic faults, making reliable fault diagnosis essential for ensuring driving safety and system reliability. Although considerable progress has been made in fault diagnosis techniques related to IWMs, a systematic review in this area is still lacking. To address this gap, this paper provides a comprehensive review of fault diagnosis techniques for IWMs. First, typical faults in IWMs are analyzed with a focus on their unique structural and failure characteristics. Then, the applications and recent research progress of three major categories of fault diagnosis approaches—model-based, signal-based, and knowledge-based methods—in the context of IWMs are critically reviewed. Finally, key challenges and pain points in IWM diagnosis are discussed, along with promising future research directions. Full article
(This article belongs to the Special Issue New Journeys in Vehicle System Dynamics and Control)
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