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Integrated Intelligent Vehicle Dynamics and Control

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

Deadline for manuscript submissions: 30 June 2025 | Viewed by 16406

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Special Issue Editors

Prof. Dr. Wuwei Chen

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Guest Editor

School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei, China
Interests: vehicle system dynamics and control; vehicle vibration; system modeling and simulation; intelligent vehicles and assisted driving; robot control and application; intelligent transportation

Dr. Hongbo Wang

E-Mail Website
Guest Editor

School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei, China
Interests: vehicle system dynamics and control; vehicle vibration, vehicle system analysis and control; in-wheel motor drive vehicle control

Special Issue Information

Dear Colleagues,

The development of intelligent vehicle and connected autonous vehicle has made the traffic environment changed very much. In the recent condition, the automated vehicle and human-driving vehicle coexist on the road. These new change has brung new scientific and technological challenge to the academia and industry. Intelligent vehicle dynamics and control should face the new problems to enhance vehicle function design and performance. Integrated intelligent vehicle dynamics and control is important to make clear the vehicle dynamics behavior and provide the basis for the control strategy and algorithm design. The aim of the present Special Issue is to collect original papers concerned with integrated intelligent vehicle dynamics and control. Theoretical, numerical and experimental contributions for intelligent, electric, rail and special vehicles are welcome, including but not limited in dynamics analysis, fault diagnosis and control of X-by-wire chassis with suspension, steering and brake, powertrain and energy management.

Prof. Dr. Wuwei Chen
Dr. Hongbo Wang
Guest Editors

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Keywords

intelligent vehicle
electric vehicle
rail vehicle
special vehicle
vehicle dynamics modelling and control
integrated vehicle control
dynamic modelling and control of powertrain
chassis system dynamics and integrated control
X-by-wire chassis system dynamics and control
fault diagnosis and control of intelligent vehicle
vehicle stability analysis
energy management strategy of electric vehicle
connected autonomous vehicle control
vehicle dynamics control in mixed traffic environment

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Published Papers (10 papers)

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Research

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14 pages, 2984 KiB

Open AccessArticle

Influence Analysis of Design Parameters of Elastic Valve Plate and Structural Types of Guide Flow Disc on the Performance of Relief Valve

by Junjie Chen, Peng Huang, Xinrong Xie, Changyu Guan and Hao Liu

Actuators 2025, 14(3), 143; https://doi.org/10.3390/act14030143 - 14 Mar 2025

Viewed by 287

Abstract

The elastic valve plate and guide flow disc are key components that influence parameters such as opening and pressure difference of pilot-relief valve, which are also the core components enabling continuous damping adjustment in valve-controlled continuously variable dampers. Based on deformation characteristics of elastic valve plate and various structural types of guide flow disc, this paper reveals the impact of structural types of guide flow disc and design parameters of elastic valve plate on the performance of pilot-relief valve and obtains the relationship curves between opening pressure, pressure difference and opening of relief valve versus structural types and the angle, width and the number of arc plates of elastic valve plate. It shows that the pressure difference of the relief valve reaches maximum with min angle, max width, most arc plates and irregular-shaped type, and the opening reaches maximum with max angle, min width, fewest plates and round hole type. By adjusting structural types of guide flow disc and design parameters of elastic valve plate, the pressure difference and opening of the relief valve can be precisely controlled, providing theoretical support for the precise design of pilot-relief valve and the optimization of damping characteristics. Full article

(This article belongs to the Special Issue Integrated Intelligent Vehicle Dynamics and Control)

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27 pages, 10913 KiB

Open AccessArticle

Observer-Based Sliding Mode Control for Vehicle Way-Point Tracking with Unknown Disturbances and Obstacles

by Jiacheng Song, Mingjie Shen and Yanan Zhang

Actuators 2025, 14(2), 89; https://doi.org/10.3390/act14020089 - 13 Feb 2025

Viewed by 516

Abstract

In this paper, an advanced vehicle way-point tracking control method, including kinematic control, dynamic control and an obstacle avoidance strategy, is introduced. In the kinematic part, a vehicle kinematic model is established, along with the coordinate transformation between the vehicle and its target. A way-point tracking control law is developed to optimize the vehicle’s movement along predefined way-points. In the dynamic part, a dynamic model considering the actual disturbances and losses is established. An observer compensation technique is utilized to monitor and mitigate disturbances, while sliding mode control, enhanced by a HyperSpiral algorithm, ensures accurate and stable tracking performance. Furthermore, to tackle real-world path planning challenges, an improved way-point tracking obstacle-avoidance algorithm is developed to generate effective way-points for navigating around obstacles. Finally, simulation results validate that the vehicle consistently tracks target way-points in complex scenarios, highlighting the robustness and effectiveness of the proposed method. Full article

(This article belongs to the Special Issue Integrated Intelligent Vehicle Dynamics and Control)

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19 pages, 11246 KiB

Open AccessArticle

A New Dual Steering System in a Compact Tractor

by Giorgio Paolo Massarotti, German Filippini, Gustavo Raush Alviach, Pedro Javier Gamez-Montero and Esteban Codina Macia

Actuators 2025, 14(1), 35; https://doi.org/10.3390/act14010035 - 17 Jan 2025

Viewed by 993

Abstract

To achieve optimal controllability in a dual steering tractor (a four-wheel, iso-diametric tractor equipped with a dual-hydraulic steering system), this study proposes a coordinated approach that combines experimental testing (using a special agricultural tractor) with numerical analysis of the entire vehicle, developed in Bond Graph-3D. For certain crops, a dual steering vehicle is used to meet the needs of professionals who require easy maneuverability in narrow spaces and/or reduced steering time. This study aims to explore the reasons behind the need for dual steering tractors, highlighting the advantages and disadvantages of these two different configurations and ultimately focusing on the combined benefits of both. Based on an extensive review of the literature and drawing from previous studies, this paper analyzes aspects such as the variation in noise levels (or comfort level) experienced at the steering wheel when switching from Ackermann steering to a dual steering system. After outlining the theoretical methodology used to describe the model, both experimental and numerical analyses of a vineyard tractor in operation are presented. The goal of this work is to provide guidance on design methods and, through the Bond Graph-3D model, suggest the best control algorithms to minimize steering noise and enhance driving comfort. This research aims to pave the way for future control strategies in electrohydraulic steering systems. Full article

(This article belongs to the Special Issue Integrated Intelligent Vehicle Dynamics and Control)

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18 pages, 11052 KiB

Open AccessArticle

A Robust Path Tracking Controller for Autonomous Mobility with Control Delay Compensation Using Backstepping Control

by Munjung Jang, Sehwan Kim, Byeonghun Yoo and Kwangseok Oh

Actuators 2024, 13(12), 508; https://doi.org/10.3390/act13120508 - 9 Dec 2024

Cited by 1 | Viewed by 895

Abstract

Control delay phenomena, such as time delays and actuator lags, can compromise the control performance of autonomous mobility systems, leading to increased control errors. Therefore, it is essential to develop a control delay compensation algorithm. This paper proposes a Lyapunov-based backstepping steering control algorithm to compensate for control delays in autonomous mobility systems. To estimate the control delay in the steering system, the Recursive Least Squares (RLS) algorithm was employed to calculate the time constant in real time. The control delay was estimated using an RLS designed based on a first-order differential equation. A backstepping steering controller was developed to calculate the desired steering angle using simplified error dynamics for reference path tracking. The control errors, specifically the lateral preview and yaw angle errors, were derived by calculating the path error between the current position and the waypoint. The performance of the proposed control algorithm was evaluated using the DC motor and CarMaker software 8.1.1(IPG Automotive, Karlsruhe, Germany) under scenarios involving sinusoidal input and four-curved loop and S-curved paths respectively. Full article

(This article belongs to the Special Issue Integrated Intelligent Vehicle Dynamics and Control)

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29 pages, 7167 KiB

Open AccessArticle

A Tube-Based Model Predictive Control for Path Tracking of Autonomous Articulated Vehicle

by Taeyeon Lee and Yonghwan Jeong

Actuators 2024, 13(5), 164; https://doi.org/10.3390/act13050164 - 1 May 2024

Cited by 4 | Viewed by 2236

Abstract

This paper presents tube-based Model Predictive Control (MPC) for the path and velocity tracking of an autonomous articulated vehicle. The target platform of this study is an autonomous articulated vehicle with a non-steerable axle. Consequently, the articulation angle and wheel torque input are determined by the tube-based MPC. The proposed MPC aims to achieve two objectives: minimizing path tracking error and enhancing robustness to disturbances. Furthermore, the lateral stability of the autonomous articulated vehicle is considered to reflect its dynamic characteristics. The vehicle model for the MPC is formulated using local linearization to minimize modeling errors. The reference state is determined using a virtual controller based on the linear quadratic regulator to provide the optimal reference for the MPC solver. The proposed algorithm was evaluated through a simulation study with base algorithms under noise injection into the sensor signal. Simulation results demonstrate that the proposed algorithm achieved the smallest path tracking error, compared to the base algorithms. Additionally, the proposed algorithm demonstrated robustness to external noise for multiple signals. Full article

(This article belongs to the Special Issue Integrated Intelligent Vehicle Dynamics and Control)

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21 pages, 849 KiB

Open AccessArticle

Yaw Stability Control of Unmanned Emergency Supplies Transportation Vehicle Considering Two-Layer Model Predictive Control

by Minan Tang, Yaqi Zhang, Wenjuan Wang, Bo An and Yaguang Yan

Actuators 2024, 13(3), 103; https://doi.org/10.3390/act13030103 - 6 Mar 2024

Viewed by 1958

Abstract

The transportation of emergency supplies is characterized by real-time, urgent, and non-contact, which constitute the basic guarantee for emergency rescue and disposal. To improve the yaw stability of the four-wheel-drive unmanned emergency supplies transportation vehicle (ESTV) during operation, a two-layer model predictive controller (MPC) method based on a Kalman filter is proposed in this paper. Firstly, the dynamics model of the ESTV is established. Secondly, the improved Sage–Husa adaptive extended Kalman filter (SHAEKF) is used to decrease the impact of noise on the ESTV system. Thirdly, a two-layer MPC is designed for the yaw stability control of the ESTV. The upper-layer controller solves the yaw moment and the front wheel steering angle of the ESTV. The lower-layer controller optimizes the torque distribution of the four tires of the ESTV to ensure the self-stabilization of the ESTV operation. Finally, analysis and verification are carried out. The simulation results have verified that the improved SHAEKF can decrease the state estimation error by more than 78% and achieve the noise reduction of the ESTV state. Under extreme conditions of high velocity and low adhesion, the average relative error is within 6.77%. The proposed control method can effectively prevent the instability of the ESTV and maintain good yaw stability. Full article

(This article belongs to the Special Issue Integrated Intelligent Vehicle Dynamics and Control)

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33 pages, 12225 KiB

Open AccessArticle

Coordinated Control for the Trajectory Tracking of Four-Wheel Independent Drive–Four-Wheel Independent Steering Electric Vehicles Based on the Extension Dynamic Stability Domain

by Yiran Qiao, Xinbo Chen and Dongxiao Yin

Actuators 2024, 13(2), 77; https://doi.org/10.3390/act13020077 - 16 Feb 2024

Cited by 3 | Viewed by 2416

Abstract

In order to achieve multi-objective chassis coordination control for 4WID-4WIS (four-wheel independent drive–four-wheel independent steering) electric vehicles, this paper proposes a coordinated control strategy based on the extension dynamic stability domain. The strategy aims to improve trajectory tracking performance, handling stability, and economy. Firstly, expert PID and model predictive control (MPC) are used to achieve longitudinal speed tracking and lateral path tracking, respectively. Then, a sliding mode controller is designed to calculate the expected yaw moment based on the desired vehicle states. The extension theory is applied to construct the extension dynamic stability domain, taking into account the linear response characteristics of the vehicle. Different coordinated allocation strategies are devised within various extension domains, providing control targets for direct yaw moment control (DYC) and active rear steering (ARS). Additionally, a compound torque distribution strategy is formulated to optimize driving efficiency and tire adhesion rate, considering the vehicle’s economy and stability requirements. The optimal wheel torque is calculated based on this strategy. Simulation tests using the CarSim/Simulink co-simulation platform are conducted under slalom test and double-lane change to validate the control strategy. The test results demonstrate that the proposed control strategy not only achieves good trajectory tracking performance but also enhances handling stability and economy during driving. Full article

(This article belongs to the Special Issue Integrated Intelligent Vehicle Dynamics and Control)

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22 pages, 8667 KiB

Open AccessArticle

Adaptive Fuzzy Power Management Strategy for Extended-Range Electric Logistics Vehicles Based on Driving Pattern Recognition

by Changyin Wei, Xiaodong Wang, Yunxing Chen, Huawei Wu and Yong Chen

Actuators 2023, 12(11), 410; https://doi.org/10.3390/act12110410 - 3 Nov 2023

Cited by 7 | Viewed by 1836

Abstract

The primary objective of an energy management strategy is to achieve optimal fuel economy through proper energy distribution. The adoption of a fuzzy energy management strategy is hindered due to different reasons, such as uncertainties surrounding its adaptability and sustainability compared to conventional energy control methods. To address this issue, a fuzzy energy management strategy based on long short-term memory neural network driving pattern recognition is proposed. The time-frequency characteristics of vehicle speed are obtained using the Hilbert–Huang transform method. The multi-dimensional features are composed of the time-frequency features of vehicle speed and the time-domain signals of the accelerator pedal and brake pedal. A novel driving pattern recognition approach is designed using a long short-term memory neural network. A dual-input and single-output fuzzy controller is proposed, which takes the required power of the vehicle and the state of charge of the battery as the input, and the comprehensive power of the range extender as the output. The parameters of the fuzzy controller are selected according to the category of driving pattern. The results show that the fuel consumption of the method proposed in this paper is 5.8% lower than that of the traditional fuzzy strategy, and 4.2% lower than the fuzzy strategy of the two-dimensional feature recognition model. In general, the proposed EMS can effectively improve the fuel consumption of extended-range electric vehicles. Full article

(This article belongs to the Special Issue Integrated Intelligent Vehicle Dynamics and Control)

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17 pages, 4101 KiB

Open AccessArticle

Vehicle Sideslip Angle Estimation Based on Radial Basis Neural Network and Unscented Kalman Filter Algorithm

by Chuanwei Zhang, Yansong Feng, Jianlong Wang, Peng Gao and Peilin Qin

Actuators 2023, 12(10), 371; https://doi.org/10.3390/act12100371 - 26 Sep 2023

Cited by 7 | Viewed by 2236

Abstract

Most existing ESC (electronic stability control) and ADS (auto drive system) stability controls rely on the measurement of yaw rate and sideslip angle. However, the existing sensors are too expensive, which is one of the factors that makes it difficult to measure the side slip angle of vehicles directly. Therefore, the estimation of sideslip angle has been extensively discussed in the relevant literature. Accurate modeling is complicated by the fact that vehicles are highly nonlinear. This article combines a radial basis function neural network with an unscented Kalman filter to propose a new sideslip angle estimation method for controlling the dynamic behavior of vehicles. Considering the influence of input data type and sensor ease of measurement factors on the results, a two-degrees-of-freedom vehicle nonlinear dynamic model was established, and a radial basis function neural network estimation algorithm was designed. In order to reduce the impact of noise and improve the reliability of the algorithm, the neural network algorithm was combined with the Kalman filter. The information collected from low-cost sensors for actual vehicle operation (longitudinal vehicle speed, steering wheel angle, yaw rate, lateral acceleration) was trained using a radial basis function neural network to obtain a “pseudo slip angle”. The “pseudo slip angle”, yaw rate, and lateral acceleration are input as observations of the Kalman filter. The sideslip angle obtained from different observation methods was compared with the values provided by the Carsim 2020. The experiment shows that the sideslip angle estimator based on the radial basis function neural network and unscented Kalman filter achieves the optimal effect. Full article

(This article belongs to the Special Issue Integrated Intelligent Vehicle Dynamics and Control)

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Review

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30 pages, 1112 KiB

Open AccessReview

A Survey of Vehicle System and Energy Models

by Lingyun Hua, Jian Tang and Guoming Zhu

Actuators 2025, 14(1), 10; https://doi.org/10.3390/act14010010 - 1 Jan 2025

Viewed by 1302

Abstract

Vehicle system models can be roughly divided into two categories, dynamic and steady-state (or quasi-steady-state) models, and can be applied to evaluate vehicle transient performance such as vehicle longitudinal and lateral dynamics, as well as energy economies like fuel or electricity consumption. This paper reviews various energy consumption models for automotive systems, focusing on component- and vehicle-level models. As the foundation to calculate the energy consumption, powertrain component models of three main vehicle types (internal combustion engine (ICE) vehicles, electric vehicles (EVs), and hybrid vehicles) are reviewed with their key components, including internal combustion engines, electric motors, and batteries. Three types of vehicle energy consumption models are explored according to their interpretability: white-box, black-box, and grey-box models. Optimizing vehicle energy usage based upon a vehicle energy consumption model is reviewed from the aspects of eco-driving and eco-routing problems at the end of the paper. Eco-driving research primarily selects models focusing on transient performance; whereas eco-routing focuses on steady-state or quasi-steady-state conditions to balance the needs of model accuracy and calculation efficiency for real-time applications. This review aims to guide model selection and inspire future applications of energy consumption models for advancing sustainable automotive technologies. Full article

(This article belongs to the Special Issue Integrated Intelligent Vehicle Dynamics and Control)

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