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Actuators
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Advanced Actuation and Control Technologies for Vehicle Driving Systems—2nd Edition
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Advanced Actuation and Control Technologies for Vehicle Driving Systems—2nd Edition

A special issue of Actuators (ISSN 2076-0825). This special issue belongs to the section "Actuators for Surface Vehicles".

Deadline for manuscript submissions: closed (30 April 2025) | Viewed by 2616

Special Issue Editors

Dr. Md Abdus Samad Kamal

E-Mail Website
Guest Editor
Cluster of Electronics and Mechanical Engineering, Graduate School of Science and Technology, Gunma University, Maebashi, Japan
Interests: autonomous driving; intelligent transportation systems (ITS); model predictive control (MPC); reinforcement learning; machine learning; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Masakazu Mukai

E-Mail Website
Guest Editor
Department of Electrical and Electronic Engineering, Kogakuin University, Tokyo 163-8677, Japan
Interests: control engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Actuators are essential in any vehicle system to ultimately execute control decisions at the wheel, relaying information to the transmission and powertrain. In the case of hybrid electric vehicles, electric vehicles, and fuel cell vehicles, the role of actuators is vital in energy conversion since they assist in switching between the power sources. This requires highly efficient actuation technologies. Most importantly, the rapid development of communication technology and the need to cater to the aging population in developed countries have potentially made autonomous vehicles a necessity and a vital business paradigm. Autonomous vehicles are expected to constitute around 50% of vehicle sales, 30% of vehicles, and 40% of all vehicle travel by 2040. Advanced vehicles, including autonomous vehicles, are the most challenging areas of innovation in the automotive industry, where such actuation and control technologies are vital for developing complex vehicle subsystems to achieve better operating characteristics. Furthermore, such technologies are also vital for the motion control systems of other types of vehicles, including wheelchairs, three-wheelers, excavators, bulldozers, and so on.

This Special Issue addresses the need to develop relevant advanced technologies, considering emerging control applications in any advanced vehicle systems and specifically covering the following topics:

  • Modeling, prediction, and control of the driving behavior of autonomous vehicles;
  • Vehicle dynamics and control technologies;
  • Predictive- and learning-based control to improve autonomous vehicle safety and performance;
  • Estimation and sensing for autonomous vehicles;
  • Novel design of autonomous vehicle powertrain and chassis subsystems;
  • User-automated vehicle interaction, focusing on autonomous vehicle comfort and acceptance;
  • Vibration suppression of in-wheel motor-active suspensions against negative electromechanical coupling influences.
  • Motion control of non-traditional vehicles, integrated road transportation, and micro-mobility.

We look forward to your valuable contributions.

Dr. Md Abdus Samad Kamal
Prof. Dr. Masakazu Mukai
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. Actuators 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

  • actuation technology for vehicles
  • vehicle dynamics and control
  • intelligent vehicle
  • advanced powertrain control technology
  • advanced motion control applications

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

20 pages, 2602 KiB  
Article
Performance Improvement in a Vehicle Suspension System with FLQG and LQG Control Methods
by Tayfun Abut, Enver Salkım and Andreas Demosthenous
Actuators 2025, 14(3), 137; https://doi.org/10.3390/act14030137 - 10 Mar 2025
Viewed by 474
Abstract
This study investigates the effect of active control on a quarter-vehicle suspension system. The car suspension system was modeled using the Lagrange–Euler method. The linear quadratic Gaussian (LQG) and fuzzy linear quadratic Gaussian (FLQG) control methods were designed and used for active control [...] Read more.
This study investigates the effect of active control on a quarter-vehicle suspension system. The car suspension system was modeled using the Lagrange–Euler method. The linear quadratic Gaussian (LQG) and fuzzy linear quadratic Gaussian (FLQG) control methods were designed and used for active control to increase vehicle handling and passenger comfort, with the aim of reducing or eliminating vibrations by performing active control of passive suspension systems using these methods. The optimum values of the coefficients of the points where the membership functions of the LQG and Fuzzy LQG methods touch were obtained using the grey wolf optimization (GWO) algorithm. The success of the control performance rate of the applied methods was compared based on the passive suspension system. In addition, the obtained results were compared with each other and with other studies using the integral time-weighted absolute error (ITAE) performance criterion. The proposed control method yielded significant improvements in vehicle parameters compared with the passive suspension system. Vehicle body movement, vehicle acceleration, suspension deflection, and tire deflection improved by approximately 88.2%, 91.5%, 88%, and 89.4%, respectively. Thus, vehicle driving comfort was significantly enhanced based on the proposed system. Full article
(This article belongs to the Special Issue Advanced Actuation and Control Technologies for Vehicle Driving Systems—2nd Edition)
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21 pages, 2616 KiB  
Article
Autonomous Tracked Vehicle Trajectory Tracking Control Based on Disturbance Observation and Sliding Mode Control
by Xihao Yan, Shuo Wang, Yuxin He, Aixiang Ma and Sihai Zhao
Actuators 2025, 14(2), 51; https://doi.org/10.3390/act14020051 - 24 Jan 2025
Viewed by 988
Abstract
This paper examines the path-tracking control issue for tracked mobile robots (TMRs) operating in complex terrains, focusing on improving their autonomous operation capabilities. Considering the system’s complex dynamic model, environmental uncertainties, and non-linear characteristics, especially the phenomenon of track slippage, a dynamic model [...] Read more.
This paper examines the path-tracking control issue for tracked mobile robots (TMRs) operating in complex terrains, focusing on improving their autonomous operation capabilities. Considering the system’s complex dynamic model, environmental uncertainties, and non-linear characteristics, especially the phenomenon of track slippage, a dynamic model that incorporates track slippage is proposed. A sliding factor observer is then designed to estimate slippage parameters, ensuring the control system remains stable and accurate despite uncertainties. A hierarchical control architecture is introduced, with the upper-level controller using a kinematic model to generate desired rotational speed commands for the left and right drive wheels. The lower-level controller, operating on a dynamic model, adjusts motor torque to achieve these desired speeds. Utilizing sliding mode control strategies, combined with adaptive laws and nonlinear control methods, the controller effectively addresses the issue of high-frequency chattering arising from the use of signum functions, thereby enhancing the lifespan of actuators and overall system control performance. A comprehensive simulation and experimental setup for real TMR systems is established to validate the proposed control strategy. Results demonstrate that the control scheme effectively achieves trajectory tracking across various unstructured terrains, exhibiting strong robustness and stability. Full article
(This article belongs to the Special Issue Advanced Actuation and Control Technologies for Vehicle Driving Systems—2nd Edition)
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17 pages, 5084 KiB  
Article
Optimization Study of Pneumatic–Electric Combined Braking Strategy for 30,000-ton Heavy-Haul Trains
by Mingtao Zhang, Congjin Shi, Kun Wang, Pengfei Liu, Guoyun Liu, Zhiwei Wang and Weihua Zhang
Actuators 2025, 14(1), 40; https://doi.org/10.3390/act14010040 - 20 Jan 2025
Cited by 1 | Viewed by 760
Abstract
The normalized operation of 30,000-ton heavy-haul trains is of significant importance for enhancing the transportation capacity of heavy-haul railways. However, with the increase in train formation size, traditional braking strategies result in excessive longitudinal impulse when combined pneumatic and electric braking is applied [...] Read more.
The normalized operation of 30,000-ton heavy-haul trains is of significant importance for enhancing the transportation capacity of heavy-haul railways. However, with the increase in train formation size, traditional braking strategies result in excessive longitudinal impulse when combined pneumatic and electric braking is applied on long, steep gradients. This presents a serious challenge to the braking safety of the train. To this end, this paper establishes a longitudinal dynamic model of a 30,000-ton heavy-haul train based on vehicle system dynamics theory, and validates the model’s effectiveness through line test data. On this basis, the influence of two braking parameters, namely, the distribution of the magnitude of the electric braking force and the matching time of pneumatic braking and electric braking, on the longitudinal dynamic behavior of heavy-haul trains is studied. Thereby, an optimized combined pneumatic and electric braking strategy is formulated to reduce the longitudinal impulse of the trains. The results show that setting reasonable braking parameters can effectively reduce the longitudinal impulse, with the braking matching time having a significant impact on the longitudinal impulse. Specifically, when using a strategy where the electric braking forces of three locomotives are set to 90 kN, 300 kN, and 300 kN, with a 30 s delay in applying the electric braking force, a better optimization effect is achieved. The two proposed braking strategies reduce the maximum longitudinal forces by 20.27% and 47.83%, respectively, compared to conventional approaches. The research results provide effective methods and theoretical guidance for optimizing the braking strategy and ensuring the operational safety of 30,000-ton heavy-haul trains. Full article
(This article belongs to the Special Issue Advanced Actuation and Control Technologies for Vehicle Driving Systems—2nd Edition)
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