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

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 30084

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Special Issue Editors

Prof. Dr. Olivier Sename

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Guest Editor

GIPSA-lab/Control System department, Grenoble Institute of Technology, 38031 Grenoble, France
Interests: robust control; vehicle dynamics and control; suspension control; steering control; linear parameter varying systems; fault-tolerant control; observer design

Dr. Van Tan Vu

E-Mail Website
Guest Editor

Department of Automotive Mechanical Engineering, Faculty of Mechanical Engineering, University of Transport and Communications, 11500 Ha Noi, Viet Nam
Interests: vehicle dynamics and control; optimal control; fuzzy control; robust control; vibration control; active safety systems; electric vehicles

Dr. Thanh-Phong Pham

E-Mail Website
Guest Editor

Department of Electrical and Electronic Engineering, University of Danang-University of Technology and Education, 550000 Danang, Vietnam
Interests: robust control; adaptive control; observer design; nonlinear and linear parameter varying systems; semi-active suspension system; vehicle dynamics

Special Issue Information

Dear colleagues,

As the demands of people on the move are increasingly enhanced, the requirements on vehicle quality are also increasing. The study of vehicle modeling and control has long been an important key to achieving this goal. While the study of vehicle modeling has been carried out from the moment cars were put into service, in order to get ever-better cars, this field has never reached its limit. As the mechatronics and advanced control methods develop, vehicle control applications in general and automobiles in particular have brought about great effects in improving quality as well as creating safer and more comfortable cars. For such objectives, several actuators can be embedded on board for subsystems as braking, steering, suspension, engine, clutch, differential, powertrain, etc. Aiming at spreading the latest research in the field widely, we are pleased to announce a Special Issue on "Vehicle Modeling and Control". This Special Issue will bring together original and high-quality articles through an international standard peer-review process with the following main topics (not an exhaustive list):

- Vehicle/systems modeling and identification.

- Dynamics of commercial vehicles (light vehicles, cars, buses, trucks, and heavy vehicles) and unconventional vehicles.

- Dynamics of vehicle systems and their components including steering, braking, suspension, chassis systems, power train, noise-vibration-harshness.

- Active/semi-active safety systems including ride comfort, road holding, handling, roll stability, collision and warning devices.

- Electric vehicles, intelligent vehicles, autonomous vehicles related to vehicle dynamics.

- Control and automation systems on automobiles including optimal, adaptive, robust, linear parameter varying, model predictive control (MPC), and sliding mode control.

- Fault detection and isolation, fault-tolerant control, and observer design.

We look forward to your valuable contributions.

Prof. Dr. Olivier Sename
Dr. Van Tan Vu
Dr. Thanh-Phong Pham
Guest Editors

Manuscript Submission Information

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Keywords

Vehicle/system modeling and identification
Vehicle dynamics and control
Fault detection and fault tolerant control
Advanced control for vehicles
Active/semi-active safety systems
Electric vehicles, intelligent vehicles, autonomous vehicles

Published Papers (10 papers)

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Research

23 pages, 7150 KiB

Open AccessArticle

Fractional Order PID Control Based on Ball Screw Energy Regenerative Active Suspension

by Jingming Zhang, Jiang Liu, Bilong Liu and Min Li

Actuators 2022, 11(7), 189; https://0-doi-org.brum.beds.ac.uk/10.3390/act11070189 - 11 Jul 2022

Cited by 2 | Viewed by 1689

Abstract

A ball screw type energy regenerative active suspension under fractional order PID control is proposed and studied in order to improve the vibration damping performance of the suspension. A mathematical model of the energy regenerative actuator is established, the energy recovery power at different frequencies is measured through experiments, and then the electromagnetic torque constant, representing the proportional relationship between the output torque and current of the motor, is calculated according to the experimental results. A mathematical model of the control circuit is established and the feasibility and the superiority of the fractional order PID control are verified by simulation and experiments. To achieve a better damping effect, the fractional order PID controller of the whole vehicle suspension system is parameterized using the Beetle Antenna Search (BAS) algorithm. The results showed that the mean energy recovery power of the actuator was about 3.5091 W at a vibration frequency of 11/6 Hz, and the electromagnetic torque constant of the motor was about 0.2885. The actuator control circuit was feasible, and the root mean square value of current deviation under fractional order PID control was 1.1158 mA, which was optimized by 9.40%, compared to the PID control. The BAS algorithm effectively realized the parameter tuning of the controller, and both the tuned PID and fractional order PID controllers, achieved optimization of suspension damping performance. The optimal value of the damping performance objective function under fractional order PID control was 0.3270, which was optimized by 62.93%, compared to the PID control. In addition, all suspension performance indices under fractional order PID control were optimized to a certain extent, compared with the PID control. Full article

(This article belongs to the Special Issue Vehicle Modeling and Control)

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17 pages, 5671 KiB

Open AccessArticle

A Basic Study on Hybrid Systems for Small Race Car to Improve Dynamic Performance Using Lap Time Simulation

by Ikkei Kobayashi, Kazuki Ogawa, Daigo Uchino, Keigo Ikeda, Taro Kato, Ayato Endo, Mohamad Heerwan Bin Peeie, Takayoshi Narita and Hideaki Kato

Actuators 2022, 11(7), 173; https://0-doi-org.brum.beds.ac.uk/10.3390/act11070173 - 22 Jun 2022

Cited by 2 | Viewed by 2390

Abstract

A hybrid vehicle is a vehicle with two or more power sources. We propose a hybrid system in which the engine torque converted by the transmission is combined with an electric motor torque. The proposed system reduces transmission because engine torque only acts during transmission. Furthermore, the proposed hybrid system’s simple structure uses lightweight chains and sprockets that can be laid out in various ways. The realization of the proposed hybrid system requires independent control algorithms for the two power systems, engine and electric motor, that take into consideration the state of the vehicle and the driver’s input; this system can be assumed to be a servo model system with multiple inputs and outputs and analyzed to obtain the optimal operation algorithm. To apply these controls to race cars, which are required to be fast, it is necessary to obtain the reference input, which is the optimal velocity and yaw angle while traveling the course of the servo system, and simulations of the competition track must be carried out. Therefore, the dynamic performance of the hybrid system was investigated by calculating the lap times on a given circuit using a quasi-steady-state method with low computational load and high prediction accuracy. In this study, the effects of changing the electric motor and final gear ratios on the driving performance of a rear-wheel-drive parallel hybrid system for optimization were investigated. The simulation results show that not only can the optimum settings be obtained by changing the final and electric motor reduction ratios on the evaluation circuit, but also that the optimum values vary across different speed ranges on different circuits. Full article

(This article belongs to the Special Issue Vehicle Modeling and Control)

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14 pages, 2879 KiB

Open AccessArticle

Distributed Drive Electric Bus Handling Stability Control Based on Lyapunov Theory and Sliding Mode Control

by Feng Zhang, Hongchao Xiao, Yong Zhang and Gang Gong

Actuators 2022, 11(3), 85; https://0-doi-org.brum.beds.ac.uk/10.3390/act11030085 - 10 Mar 2022

Cited by 5 | Viewed by 2388

Abstract

To improve the handling stability of distributed drive electric buses, a vehicle stability control system based on direct yaw moment control (DYC) with a hierarchical control structure was designed. Considering that the vehicle dynamics system is highly nonlinear, a nonlinear controller based on Lyapunov stability theory was designed to calculate the required additional yaw moment of the vehicle in the upper controller. In the lower controller, the additional yaw moment is distributed to four wheel-side motors according to the equal proportion torque distribution method, and the direction of wheel-side motor output torque is determined based on the steering state of the vehicle. A co-simulation based on Simulink and Trucksim was conducted to verify the designed controller under two extreme conditions. Simulation results indicate that the proposed method performs feasibly and effectively in the handling stability of vehicles. Compared with traditional sliding mode control (SMC), the proposed control strategy can significantly reduce the chattering of the system, which provides a theoretical basis for the application of this yaw stability control method in engineering practice. Full article

(This article belongs to the Special Issue Vehicle Modeling and Control)

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20 pages, 8039 KiB

Open AccessArticle

Research on Trajectory Tracking of Sliding Mode Control Based on Adaptive Preview Time

by Hongzhen Hu, Shaoyi Bei, Qixian Zhao, Xiao Han, Dan Zhou, Xinye Zhou and Bo Li

Actuators 2022, 11(2), 34; https://0-doi-org.brum.beds.ac.uk/10.3390/act11020034 - 24 Jan 2022

Cited by 6 | Viewed by 2347

Abstract

The preview model is one of the common methods used in trajectory tracking. The traditional fixed preview time is not adaptable to most speeds and road conditions, which not only reduces the tracking accuracy but also reduces the vehicle stability. Therefore, a controller can be designed to determine the adaptive preview time based on an optimization function of the lateral deviation, the road boundary, and the road boundary of the whole vehicle motion response characteristics. Traditional optimal preview control theory predicts the next state of the vehicle by the assumption of constant transverse pendulum angular velocity. In this paper, an expectation-based approach is used to find the ideal steering wheel turning angle based on the adaptive preview time, and a single-point preview model is established. Based on the two-degree-of-freedom dynamics model, a sliding mode controller is designed for control, and the low-pass filters are designed to suppress jitter in the sliding mode controller. Simulation results with different preview times, different speeds and different road adhesion coefficients prove that the controller has a good control effect and has good effectiveness and adaptability to speed and adhesion coefficient. Full article

(This article belongs to the Special Issue Vehicle Modeling and Control)

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22 pages, 6672 KiB

Open AccessArticle

Evaluation of Dynamic Load Reduction for a Tractor Semi-Trailer Using the Air Suspension System at all Axles of the Semi-Trailer

by Dang Viet Ha, Vu Van Tan, Vu Thanh Niem and Olivier Sename

Actuators 2022, 11(1), 12; https://0-doi-org.brum.beds.ac.uk/10.3390/act11010012 - 05 Jan 2022

Cited by 5 | Viewed by 2676

Abstract

The air suspension system has become more and more popular in heavy vehicles and buses to improve ride comfort and road holding. This paper focuses on the evaluation of the dynamic load reduction at all axles of a semi-trailer with an air suspension system, in comparison with the one using a leaf spring suspension system on variable speed and road types. First, a full vertical dynamic model is proposed for a tractor semi-trailer (full model) with two types of suspension systems (leaf spring and air spring) for three axles at the semi-trailer, while the tractor’s axles use leaf spring suspension systems. The air suspension systems are built based on the GENSYS model; meanwhile, the remaining structural parameters are considered equally. The full model has been validated by experimental results, and closely follows the dynamical characteristics of the real tractor semi-trailer, with the percent error of the highest value being 6.23% and Pearson correlation coefficient being higher than 0.8, corresponding to different speeds. The survey results showed that the semi-trailer with the air suspension system can reduce the dynamic load of the entire field of speed from 20 to 100 km/h, given random road types from A to F according to the ISO 8608:2016 standard. The dynamic load coefficient (DLC) with the semi-trailer using the air spring suspension system can be reduced on average from 14.8% to 29.3%, in comparison with the semi-trailer using the leaf spring suspension system. Full article

(This article belongs to the Special Issue Vehicle Modeling and Control)

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23 pages, 6094 KiB

Open AccessArticle

Advanced Controller Development Based on eFMI with Applications to Automotive Vertical Dynamics Control

by Johannes Ultsch, Julian Ruggaber, Andreas Pfeiffer, Christina Schreppel, Jakub Tobolář, Jonathan Brembeck and Daniel Baumgartner

Actuators 2021, 10(11), 301; https://0-doi-org.brum.beds.ac.uk/10.3390/act10110301 - 12 Nov 2021

Cited by 4 | Viewed by 2812

Abstract

High-level modeling languages facilitate system modeling and the development of control systems. This is mainly achieved by the automated handling of differential algebraic equations which describe the dynamics of the modeled systems across different physical domains. A wide selection of model libraries provides additional support to the modeling process. Nevertheless, deployment on embedded targets poses a challenge and usually requires manual modification and reimplementation of the control system. The novel proposed eFMI Standard (Functional Mock-up Interface for embedded systems) introduces a workflow and an automated toolchain to simplify the deployment of model-based control systems on embedded targets. This contribution describes the application and verification of the eFMI workflow using a vertical dynamics control problem with an automotive application as an example. The workflow is exemplified by a control system design process which is supported by the a-causal, multi-physical, high-level modeling language Modelica. In this process, the eFMI toolchain is applied to a model-based controller for semi-active dampers and demonstrated using an eFMI-based nonlinear prediction model within a nonlinear Kalman filter. The generated code was successfully tested in different validation steps on the dedicated embedded system. Additionally, tests with a low-volume production electronic control unit (ECU) in a series-produced car demonstrated the correct execution of the controller code under real-world conditions. The novelty of our approach is that it automatically derives an embedded software solution from a high-level multi-physical model with standardized eFMI methodology and tooling. We present one of the first full application scenarios (covering all aspects ranging from multi-physical modeling up to embedded target deployment) of the new eFMI tooling. Full article

(This article belongs to the Special Issue Vehicle Modeling and Control)

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22 pages, 4151 KiB

Open AccessArticle

Learning-Based Cooperative Adaptive Cruise Control

by Jonas Mirwald, Johannes Ultsch, Ricardo de Castro and Jonathan Brembeck

Actuators 2021, 10(11), 286; https://0-doi-org.brum.beds.ac.uk/10.3390/act10110286 - 26 Oct 2021

Cited by 3 | Viewed by 3248

Abstract

Traffic congestion and the occurrence of traffic accidents are problems that can be mitigated by applying cooperative adaptive cruise control (CACC). In this work, we used deep reinforcement learning for CACC and assessed its potential to outperform model-based methods. The trade-off between distance-error minimization and energy consumption minimization whilst still ensuring operational safety was investigated. Alongside a string stability condition, robustness against burst errors in communication also was incorporated, and the effect of preview information was assessed. The controllers were trained using the proximal policy optimization algorithm. A validation by comparison with a model-based controller was performed. The performance of the trained controllers was verified with respect to the mean energy consumption and the root mean squared distance error. In our evaluation scenarios, the learning-based controllers reduced energy consumption in comparison to the model-based controller by 17.9% on average. Full article

(This article belongs to the Special Issue Vehicle Modeling and Control)

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20 pages, 5324 KiB

Open AccessArticle

Observer-Based Coordinated Control for Blended Braking System with Actuator Delay

by Wenfei Li, Huiyun Li, Chao Huang, Kun Xu, Tianfu Sun and Haiping Du

Actuators 2021, 10(8), 193; https://0-doi-org.brum.beds.ac.uk/10.3390/act10080193 - 11 Aug 2021

Cited by 5 | Viewed by 2041

Abstract

The coordinated control of a blended braking system is always a difficult task. In particular, blended braking control becomes more challenging when the braking actuator has an input time-delay and some states of the braking system cannot be measured. In order to improve the tracking performance, a coordinated control system was designed based on the input time-delay and state observation for a blended braking system comprising a motor braking system and friction braking system. The coordinated control consists of three parts: Sliding mode control, a multi-input single-output observer, and time-delay estimation-based Smith Predictor control. The sliding mode control is used to calculate the total command braking torque according to the desired braking performance and vehicle states. The multi-input single-output observer is used to simultaneously estimate the input time-delay and output braking torque of the friction braking system. With time-delay estimation-based Smith Predictor control, the friction braking system is able to effectively track the command braking torque of the friction braking system. The tracking of command braking torque is realized through the coordinated control of the motor braking system and friction braking system. In order to validate the effectiveness of the proposed approach, numerical simulations on a quarter-vehicle braking model were performed. Full article

(This article belongs to the Special Issue Vehicle Modeling and Control)

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35 pages, 11519 KiB

Open AccessArticle

Reconfigurable Slip Vectoring Control in Four In-Wheel Drive Electric Vehicles

by Gerardo Amato and Riccardo Marino

Actuators 2021, 10(7), 157; https://0-doi-org.brum.beds.ac.uk/10.3390/act10070157 - 10 Jul 2021

Cited by 6 | Viewed by 2856

Abstract

Controllability, maneuverability, fault-tolerance/isolation and safety are significantly enhanced in electric vehicles (EV) equipped with the redundant actuator configuration of four-in-wheel electric motors (4IWM). A highly reconfigurable architecture is proposed and illustrated for the adaptive, nonmodel-based control of 4IWM-EVs. Given the longitudinal force, yaw-moment requests and the reconfiguration matrix, each IWM is given a slip reference according to a Slip Vectoring (SV) allocation strategy, which minimizes the overall slip vector norm. The distributed electric propulsion and the slip vector reference allow for a decentralized online estimation of the four-wheel torque-loads, which are uncertain depending on loading and road conditions. This allows for the allocation of four different torques depending on individual wheel conditions and to determine in which region (linear/nonsaturated or nonlinear/saturated) of the torque/slip characteristics each wheel is operating. Consequently, the 4IWMs can be equalized or reconfigured, including actuator fault-isolation as a special case, so that they are enforced to operate within the linear tire region. The initial driving-mode selection can be automatically adjusted and restored among eighteen configurations to meet the safety requirements of linear torque/slip behavior. Three CarSim realistic simulations illustrate the equalization algorithm, the quick fault-isolation capabilities and the importance of a continuous differential action in a critical double-lane-change maneuver. Full article

(This article belongs to the Special Issue Vehicle Modeling and Control)

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18 pages, 3080 KiB

Open AccessArticle

An Optimization Design of Adaptive Cruise Control System Based on MPC and ADRC

by Zengfu Yang, Zengcai Wang and Ming Yan

Actuators 2021, 10(6), 110; https://0-doi-org.brum.beds.ac.uk/10.3390/act10060110 - 24 May 2021

Cited by 26 | Viewed by 4769

Abstract

In this paper, a novel adaptive cruise control (ACC) algorithm based on model predictive control (MPC) and active disturbance rejection control (ADRC) is proposed. This paper uses an MPC algorithm for the upper controller of the ACC system. Through comprehensive considerations, the upper controller will output desired acceleration to the lower controller. In addition, to increase the accuracy of the predictive model in the MPC controller and to address fluctuations in the vehicle’s acceleration, an MPC aided by predictive estimation of acceleration is proposed. Due to the uncertainties of vehicle parameters and the road environment, it is difficult to establish an accurate vehicle dynamic model for the lower-level controller to control the throttle and brake actuators. Therefore, feed-forward control based on a vehicle dynamic model (VDM) and compensatory control based on ADRC is used to enhance the control precision and to suppress the influence of internal or external disturbance. Finally, the proposed optimal design of the ACC system was validated in road tests. The results show that ACC with APE can accurately control the tracking of the host vehicle with less acceleration fluctuation than that of the traditional ACC controller. Moreover, when the mass of the vehicle and the slope of the road is changed, the ACC–APE–ADRC controller is still able to control the vehicle to quickly and accurately track the desired acceleration. Full article

(This article belongs to the Special Issue Vehicle Modeling and Control)

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