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Actuators for Intelligent Electric Vehicles
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Actuators for Intelligent Electric Vehicles

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

Deadline for manuscript submissions: closed (15 January 2022) | Viewed by 64731

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Dr. Peng Hang

E-Mail Website
Guest Editor
School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: decision-making; autonomous driving; game theory; path tracking and control
Special Issues, Collections and Topics in MDPI journals
Dr. Xin Xia

E-Mail Website
Guest Editor
Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON N2L3G1, Canada
Prof. Dr. Xinbo Chen

E-Mail Website
Guest Editor
School of Automotive Studies, Tongji University, Shanghai 201804, China

Special Issue Information

Dear Colleagues,

The electrification and intelligence of automobiles have become popular in recent years. The intelligent electric vehicle (IEV) is a transformative technology that is expected to change and advance the safety, comfort, efficiency, handling stability, and maneuverability of automobiles. As the main functional components of IEVs, advanced actuators and control algorithms of steering, driving, and braking systems are of great importance. With these advanced actuators, different control frameworks and strategies are yielded for IEVs, including an antilock brake system (ABS), autonomous emergency braking (AEB), electronic stability control (ESC), differential braking, active front steering (AFS), active rear steering (ARS), and active suspension system (ASS). Thanks to these advanced control frameworks and strategies, the performances of IEVs can be remarkably improved.

This Special Issue aims to attract papers devoted to any aspect of advanced actuators for IEVs and the design of control algorithms. The topics of interest within the scope of this Special Issue include, but are not limited to, the following:

X-by-wire actuator for IEVs;
Advanced actuators for steering, braking, and driving;
Control of active suspension system;
Advanced control algorithms for IEVs;
Collaborative control of human driver and IEV;
Advanced Driving Assistance System (ADAS);
Decision making, motion planning, and control of IEVs;

Dr. Peng Hang
Dr. Xin Xia
Prof. Dr. Xinbo Chen
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.

Published Papers (18 papers)

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18 pages, 11149 KiB  
Article
Segment Drift Control with a Supervision Mechanism for Autonomous Vehicles
by Ming Liu, Bo Leng, Lu Xiong, Yize Yu and Xing Yang
Actuators 2021, 10(9), 219; https://0-doi-org.brum.beds.ac.uk/10.3390/act10090219 - 01 Sep 2021
Cited by 4 | Viewed by 2149
Abstract
Stable maneuverability is extremely important for the overall safety and robustness of autonomous vehicles under extreme conditions, and automated drift is able to ensure the widest possible range of maneuverability. However, due to the strong nonlinearity and fast vehicle dynamics occurring during the [...] Read more.
Stable maneuverability is extremely important for the overall safety and robustness of autonomous vehicles under extreme conditions, and automated drift is able to ensure the widest possible range of maneuverability. However, due to the strong nonlinearity and fast vehicle dynamics occurring during the drift process, drift control is challenging. In view of the drift parking scenario, this paper proposes a segmented drift parking method to improve the handling ability of vehicles under extreme conditions. The whole process is divided into two parts: the location approach part and the drift part. The model predictive control (MPC) method was used in the approach to achieve consistency between the actual state and the expected state. For drift, the open-loop control law was designed on the basis of drift trajectories obtained by professional drivers. The drift monitoring strategy aims to monitor the whole drift process and improve the success rate of the drift. A simulation and an actual vehicle test platform were built, and the test results show that the proposed algorithm can be used to achieve accurate vehicle drift to the parking position. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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17 pages, 3034 KiB  
Article
Research on the Identification of Tyre-Road Peak Friction Coefficient under Full Slip Rate Range Based on Normalized Tyre Model
by Yinfeng Han, Yongjie Lu, Na Chen and Hongwei Wang
Actuators 2022, 11(2), 59; https://0-doi-org.brum.beds.ac.uk/10.3390/act11020059 - 17 Feb 2022
Cited by 5 | Viewed by 2320
Abstract
The accurate estimation of the tyre-road peak friction coefficient is the key basis for the normal operation of the vehicle active safety control system. The estimation algorithm needs to be able to adapt to various conditions encountered in the actual driving process of [...] Read more.
The accurate estimation of the tyre-road peak friction coefficient is the key basis for the normal operation of the vehicle active safety control system. The estimation algorithm needs to be able to adapt to various conditions encountered in the actual driving process of the vehicle and obtain the estimation results timely and accurately. Therefore, a new normalized strategy is proposed in this paper. The core is the equal ratio between the peak friction coefficient and the utilization friction coefficient between adjacent typical roads. This strategy can establish the direct connection (normalization) between tyre force and tyre-road peak friction coefficient through most tyre models in the field of vehicle dynamics and accomplish estimation by combining with the filtering algorithm. In addition, most of the vehicle dynamic estimation algorithms are limited by road excitation, and it is difficult to obtain satisfactory estimation results. This strategy can greatly reduce the system error caused by insufficient road excitation (slip rate is not 0.15–0.20) and improve the applicability of the estimation algorithm to the actual driving process of the vehicle. Finally, the magic formula (MF) tyre model is selected to describe the tyre characteristics after treatment of the normalized strategy; the tyre-road peak friction coefficient is estimated by combining the extended Kalman filter and vehicle dynamics model. Satisfactory estimation results are obtained in both simulation and real vehicle tests, which verifies the effectiveness of the proposed normalized strategy. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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14 pages, 4088 KiB  
Article
Research on an Intelligent Driving Algorithm Based on the Double Super-Resolution Network
by Taoyang Hang, Bo Li, Qixian Zhao, Shaoyi Bei, Xiao Han, Dan Zhou and Xinye Zhou
Actuators 2022, 11(3), 69; https://0-doi-org.brum.beds.ac.uk/10.3390/act11030069 - 23 Feb 2022
Cited by 1 | Viewed by 2066
Abstract
Semantic segmentation plays a very important role in image processing, and has been widely used in intelligent driving, medicine, and other fields. With the development of semantic segmentation, the model has become more and more complex and the resolution of training pictures is [...] Read more.
Semantic segmentation plays a very important role in image processing, and has been widely used in intelligent driving, medicine, and other fields. With the development of semantic segmentation, the model has become more and more complex and the resolution of training pictures is higher and higher, so the requirements for required hardware facilities have become higher and higher. Many high-precision networks are difficult to apply in intelligent driving vehicles with limited hardware conditions, and will bring delay to recognition, which is not allowed in practical application. Based on the Dual Super-Resolution Learning (DSRL) network, this paper proposes a network model for training high-resolution pictures, adding a high-resolution convolution module which improves segmentation accuracy and speed while reducing computation. In a CamVid dataset, taking the road category as an example, IOU is 95.23%, which is 4% higher than DSRL, the real-time segmentation time of the same video is reduced by 46% from 120 s to 65 s, and the segmentation effect is better and faster, which greatly alleviates the recognition delay caused by high-resolution input. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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14 pages, 5748 KiB  
Article
Adaptive Cruise Control System Evaluation According to Human Driving Behavior Characteristics
by Lin Liu, Qiang Zhang, Rui Liu, Xichan Zhu and Zhixiong Ma
Actuators 2021, 10(5), 90; https://0-doi-org.brum.beds.ac.uk/10.3390/act10050090 - 27 Apr 2021
Cited by 1 | Viewed by 3451
Abstract
With the rapid and wide implementation of adaptive cruise control system (ACC), the testing and evaluation method becomes an important question. Based on the human driver behavior characteristics extracted from naturalistic driving studies (NDS), this paper proposed the testing and evaluation method for [...] Read more.
With the rapid and wide implementation of adaptive cruise control system (ACC), the testing and evaluation method becomes an important question. Based on the human driver behavior characteristics extracted from naturalistic driving studies (NDS), this paper proposed the testing and evaluation method for ACC systems, which considers safety and human-like at the same time. Firstly, usage scenarios of ACC systems are defined and test scenarios are extracted and categorized as safety test scenarios and human-like test scenarios according to the collision likelihood. Then, the characteristic of human driving behavior is analyzed in terms of time to collision and acceleration distribution extracted from NDS. According to the dynamic parameters distribution probability, the driving behavior is divided into safe, critical, and dangerous behavior regarding safety and aggressive and normal behavior regarding human-like according to different quantiles. Then, the baselines for evaluation are designed and the weights of different scenarios are determined according to exposure frequency, resulting in a comprehensive evaluation method. Finally, an ACC system is tested in the selected test scenarios and evaluated with the proposed method. The tested vehicle finally got a safety score of 0.9496 (full score: 1) and a human-like score as fail. The results revealed the tested vehicle has a remarkably different driving pattern to human drivers, which may lead to uncomfortable ride experience and user-distrust of the system. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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17 pages, 3721 KiB  
Article
Optimization Design for the Planetary Gear Train of an Electric Vehicle under Uncertainties
by Xiang Xu, Jiawei Chen, Zhongyan Lin, Yiran Qiao, Xinbo Chen, Yong Zhang, Yanan Xu and Yan Li
Actuators 2022, 11(2), 49; https://0-doi-org.brum.beds.ac.uk/10.3390/act11020049 - 05 Feb 2022
Cited by 5 | Viewed by 3644
Abstract
The planetary gear train is often used as the main device for decelerating and increasing the torque of the drive motor of electric vehicles. Considering the lightweight requirement and existing uncertainty in structural design, a multi-objective uncertainty optimization design (MUOD) framework is developed [...] Read more.
The planetary gear train is often used as the main device for decelerating and increasing the torque of the drive motor of electric vehicles. Considering the lightweight requirement and existing uncertainty in structural design, a multi-objective uncertainty optimization design (MUOD) framework is developed for the planetary gear train of the electric vehicle in this study. The volume and transmission efficiency of the planetary gear train are taken into consideration as optimization objectives. The manufacturing size, material, and load input of the planetary gear train are considered as uncertainties. An approximate direct decoupling model, based on subinterval Taylor expansion, is applied to evaluate the propagation of uncertainties. To improve the convergence ability of the multi-objective evolutionary algorithm, the improved non-dominated sorting genetic algorithm II (NSGA-II) is designed by using chaotic and adaptive strategies. The improved NSGA-II has better convergence efficiency than classical NSGA-II and multi-objective particle swarm optimization (MOPSO). In addition, the multi-criteria decision making (MCDM) method is applied to choose the most satisfactory solution in Pareto sets from the multi-objective evolutionary algorithm. Compared with the multi-objective deterministic optimization design (MDOD), the proposed MUOD framework has better reliability than MDOD under different uncertainty cases. This MUOD method enables further guidance pertaining to the uncertainty optimization design of transportation equipment, containing gear reduction mechanisms, in order to reduce the failure risk. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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20 pages, 7546 KiB  
Article
Pressure Estimation Based on Vehicle Dynamics Considering the Evolution of the Brake Linings’ Coefficient of Friction
by Biaofei Shi, Lu Xiong and Zhuoping Yu
Actuators 2021, 10(4), 76; https://0-doi-org.brum.beds.ac.uk/10.3390/act10040076 - 08 Apr 2021
Cited by 13 | Viewed by 2991
Abstract
To mitigate the issue of low accuracy and poor robustness of the master cylinder pressure estimation (MCPE) of the electro-hydraulic brake system (EHB) by adopting EHB’s own information, a MCPE algorithm based on vehicle information considering the evolution of the brake linings’ coefficient [...] Read more.
To mitigate the issue of low accuracy and poor robustness of the master cylinder pressure estimation (MCPE) of the electro-hydraulic brake system (EHB) by adopting EHB’s own information, a MCPE algorithm based on vehicle information considering the evolution of the brake linings’ coefficient of friction (BLCF) is proposed. First, the MCPE algorithm was derived combining the vehicle longitudinal dynamics and the wheel dynamics, in which the inertial measurement unit (IMU) was adopted to adapt the MCPE algorithm to road slope change. In order to estimate the brake pressure accurately, the driving resistance of the vehicle was obtained through a vehicle test under coasting condition. After that, with the active braking function of EHB, the evolution of the BLCF was acquired through extensive real vehicle test under different initial temperatures, different initial vehicle speeds, and different brake pressures. According to the test results, a revised model of the BLCF is proposed. Finally, the performance of the MCPE based on the revised BLCF model was compared with that based on a fixed BLCF model. Vehicle test demonstrates that the former MCPE algorithm is not only more accurate at low vehicle speed than the later, but also robust to road slope change. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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17 pages, 7517 KiB  
Article
On the Lightweight Truss Structure for the Trash Can-Handling Robot
by Jiawei Chen, Yan Li, Xiang Xu and Xinbo Chen
Actuators 2021, 10(9), 214; https://0-doi-org.brum.beds.ac.uk/10.3390/act10090214 - 31 Aug 2021
Cited by 2 | Viewed by 2199
Abstract
With the rapid development of cities, the automated and intelligent garbage transportation has become an important direction for technological innovation of sanitation vehicles. In this paper, a vehicle-mounted trash can-handling robot is proposed. In order to reduce the cost of the robot and [...] Read more.
With the rapid development of cities, the automated and intelligent garbage transportation has become an important direction for technological innovation of sanitation vehicles. In this paper, a vehicle-mounted trash can-handling robot is proposed. In order to reduce the cost of the robot and increase the loading capacity of the intelligent sanitation vehicles, a lightweight design method is proposed for the truss structure of the robot. Firstly, the parameters of the robot that are related to the load are optimized by multi-objective parameter optimization based on particle swarm optimization. Then, the material distribution of the truss structure is optimized by topology optimization under multiple load cases. Finally, the thickness of the truss structure parts is optimized by discrete optimization under multiple load cases. The optimization results show that the mass of the truss structure is reduced by 8.72%, the inherent frequency is increased by 61.08%, and the maximum stress is reduced by 10.98%. The optimization results achieve the goal of performance optimization of the intelligent sanitation vehicle, and prove the feasibility of the proposed lightweight design method. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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11 pages, 3396 KiB  
Article
A Multi-Semantic Driver Behavior Recognition Model of Autonomous Vehicles Using Confidence Fusion Mechanism
by Hongze Ren, Yage Guo, Zhonghao Bai and Xiangyu Cheng
Actuators 2021, 10(9), 218; https://0-doi-org.brum.beds.ac.uk/10.3390/act10090218 - 31 Aug 2021
Cited by 3 | Viewed by 1889
Abstract
With the rise of autonomous vehicles, drivers are gradually being liberated from the traditional roles behind steering wheels. Driver behavior cognition is significant for improving safety, comfort, and human–vehicle interaction. Existing research mostly analyzes driver behaviors relying on the movements of upper-body parts, [...] Read more.
With the rise of autonomous vehicles, drivers are gradually being liberated from the traditional roles behind steering wheels. Driver behavior cognition is significant for improving safety, comfort, and human–vehicle interaction. Existing research mostly analyzes driver behaviors relying on the movements of upper-body parts, which may lead to false positives and missed detections due to the subtle changes among similar behaviors. In this paper, an end-to-end model is proposed to tackle the problem of the accurate classification of similar driver actions in real-time, known as MSRNet. The proposed architecture is made up of two major branches: the action detection network and the object detection network, which can extract spatiotemporal and key-object features, respectively. Then, the confidence fusion mechanism is introduced to aggregate the predictions from both branches based on the semantic relationships between actions and key objects. Experiments implemented on the modified version of the public dataset Drive&Act demonstrate that the MSRNet can recognize 11 different behaviors with 64.18% accuracy and a 20 fps inference time on an 8-frame input clip. Compared to the state-of-the-art action recognition model, our approach obtains higher accuracy, especially for behaviors with similar movements. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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15 pages, 2928 KiB  
Article
A New Torque Distribution Control for Four-Wheel Independent-Drive Electric Vehicles
by Dejun Yin, Junjie Wang, Jinjian Du, Gang Chen and Jia-Sheng Hu
Actuators 2021, 10(6), 122; https://0-doi-org.brum.beds.ac.uk/10.3390/act10060122 - 06 Jun 2021
Cited by 16 | Viewed by 3897
Abstract
Torque distribution control is a key technique for four-wheel independent-drive electric vehicles because it significantly affects vehicle stability and handling performance, especially under extreme driving conditions. This paper, which focuses on the global yaw moment generated by both the longitudinal and the lateral [...] Read more.
Torque distribution control is a key technique for four-wheel independent-drive electric vehicles because it significantly affects vehicle stability and handling performance, especially under extreme driving conditions. This paper, which focuses on the global yaw moment generated by both the longitudinal and the lateral tire forces, proposes a new distribution control to allocate driving torques to four-wheel motors. The proposed objective function not only minimizes the longitudinal tire usage, but also make increased use of each tire to generate yaw moment and achieve a quicker yaw response. By analysis and a comparison with prior torque distribution control, the proposed control approach is shown to have better control performance in hardware-in-the-loop simulations. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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22 pages, 5805 KiB  
Article
Automatic Lane-Changing Decision Based on Single-Step Dynamic Game with Incomplete Information and Collision-Free Path Planning
by Hongbo Wang, Shihan Xu and Longze Deng
Actuators 2021, 10(8), 173; https://0-doi-org.brum.beds.ac.uk/10.3390/act10080173 - 24 Jul 2021
Cited by 4 | Viewed by 3354
Abstract
Traffic accidents are often caused by improper lane changes. Although the safety of lane-changing has attracted extensive attention in the vehicle and traffic fields, there are few studies considering the lateral comfort of vehicle users in lane-changing decision-making. Lane-changing decision-making by single-step dynamic [...] Read more.
Traffic accidents are often caused by improper lane changes. Although the safety of lane-changing has attracted extensive attention in the vehicle and traffic fields, there are few studies considering the lateral comfort of vehicle users in lane-changing decision-making. Lane-changing decision-making by single-step dynamic game with incomplete information and path planning based on Bézier curve are proposed in this paper to coordinate vehicle lane-changing performance from safety payoff, velocity payoff, and comfort payoff. First, the lane-changing safety distance which is improved by collecting lane-changing data through simulated driving, and lane-changing time obtained by Bézier curve path planning are introduced into the game payoff, so that the selection of the lane-changing start time considers the vehicle safety, power performance and passenger comfort of the lane-changing process. Second, the lane-changing path without collision to the forward vehicle is obtained through the constrained Bézier curve, and the Bézier curve is further constrained to obtain a smoother lane-changing path. The path tracking sliding mode controller of front wheel angle compensation by radical basis function neural network is designed. Finally, the model in the loop simulation and the hardware in the loop experiment are carried out to verify the advantages of the proposed method. The results of three lane-changing conditions designed in the hardware in the loop experiment show that the vehicle safety, power performance, and passenger comfort of the vehicle controlled by the proposed method are better than that of human drivers in discretionary lane change and mandatory lane change scenarios. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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20 pages, 5070 KiB  
Article
Pressure Estimation of the Electro-Hydraulic Brake System Based on Signal Fusion
by Biaofei Shi, Lu Xiong and Zhuoping Yu
Actuators 2021, 10(9), 240; https://0-doi-org.brum.beds.ac.uk/10.3390/act10090240 - 16 Sep 2021
Cited by 6 | Viewed by 2683
Abstract
At present, the master cylinder pressure estimation algorithm (MCPE) of electro-hydraulic brake systems (EHB) based on vehicle dynamics has the disadvantages of poor condition adaptability, and there are delays and noise in the estimated pressure; however, the MCPE based on the characteristics of [...] Read more.
At present, the master cylinder pressure estimation algorithm (MCPE) of electro-hydraulic brake systems (EHB) based on vehicle dynamics has the disadvantages of poor condition adaptability, and there are delays and noise in the estimated pressure; however, the MCPE based on the characteristics of an EHB (i.e., the pressure–position relationship) is not robust enough to prevent brake pad wear. For the above reasons, neither method be applied to engineering. In this regard, this article proposes a MCPE that is based on signal fusion. First, a five-degree-of-freedom (5-DOF) vehicle model that includes longitudinal motion, lateral motion, yaw motion, and front and rear wheel rotation is established. Based on this, an algebraic expression for MCPE is derived, which extends the MCPE from a straight condition to a steering condition. Real vehicle tests show that the MCPE based on the 5-DOF vehicle model can effectively estimate the brake pressure in both straight and steering conditions. Second, the relationship between the hydraulic pressure and the rack position in the EHB is tested under different brake pad wear levels, and the results show that the pressure–position relationship will change as the brake pad is worn down, so the pressure estimated by the pressure–position model based on fixed parameters is not robust. Third, a MCPE based on the fusion the above two MCPEs through the recursive least squares algorithm (RLS) is proposed, in which the pressure-position model can be updated online by vehicle dynamics and the final estimated pressure is calculated based on the updated pressure–position model. Finally, several simulations based on vehicle test data demonstrate that the fusion-based MCPE can estimate the brake pressure accurately and smoothly with little delay and is robust enough to prevent brake pad wear. In addition, by setting the enabling conditions of RLS, the fusion-based MCPE can switch between driving and parking smoothly; thus, the fusion-based MCPE can be applied to all working conditions. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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17 pages, 6267 KiB  
Article
Performance Assessment of an Electric Power Steering System for Driverless Formula Student Vehicles
by Raffaele Manca, Salvatore Circosta, Irfan Khan, Stefano Feraco, Sara Luciani, Nicola Amati, Angelo Bonfitto and Renato Galluzzi
Actuators 2021, 10(7), 165; https://0-doi-org.brum.beds.ac.uk/10.3390/act10070165 - 18 Jul 2021
Cited by 8 | Viewed by 7568
Abstract
In the context of automated driving, Electric Power Steering (EPS) systems represent an enabling technology. They introduce the ergonomic function of reducing the physical effort required by the driver during the steering maneuver. Furthermore, EPS gives the possibility of high precision control of [...] Read more.
In the context of automated driving, Electric Power Steering (EPS) systems represent an enabling technology. They introduce the ergonomic function of reducing the physical effort required by the driver during the steering maneuver. Furthermore, EPS gives the possibility of high precision control of the steering system, thus paving the way to autonomous driving capability. In this context, the present work presents a performance assessment of an EPS system designed for a full-electric all-wheel-drive electric prototype racing in Formula Student Driverless (FSD) competitions. Specifically, the system is based on the linear actuation of the steering rack by using a ball screw. The screw nut is rotated through a belt transmission driven by a brushless DC motor. Modeling and motion control techniques for this system are presented. Moreover, the numerical model is tuned through a grey-box identification approach. Finally, the performance of the proposed EPS system is tested experimentally on the vehicle through both sine-sweep profiles and co-simulated driverless sessions. The system performance is assessed in terms of reference tracking capability, thus showing favorable results for the proposed actuation solution. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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13 pages, 33337 KiB  
Article
Mono-Vision Based Lateral Localization System of Low-Cost Autonomous Vehicles Using Deep Learning Curb Detection
by Junwei Yu and Zhuoping Yu
Actuators 2021, 10(3), 57; https://0-doi-org.brum.beds.ac.uk/10.3390/act10030057 - 11 Mar 2021
Cited by 5 | Viewed by 2914
Abstract
The localization system of low-cost autonomous vehicles such as autonomous sweeper requires a highly lateral localization accuracy as the vehicle needs to keep a near lateral-distance between the side brush system and the road curb. Existing methods usually rely on a global navigation [...] Read more.
The localization system of low-cost autonomous vehicles such as autonomous sweeper requires a highly lateral localization accuracy as the vehicle needs to keep a near lateral-distance between the side brush system and the road curb. Existing methods usually rely on a global navigation satellite system that often loses signal in a cluttered environment such as sweeping streets between high buildings and trees. In a GPS-denied environment, map-based methods are often used such as visual and LiDAR odometry systems. Apart from heavy computation costs from feature extractions, they are too expensive to meet the low-price market of the low-cost autonomous vehicles. To address these issues, we propose a mono-vision based lateral localization system of an autonomous sweeper. Our system relies on a fish-eye camera and precisely detects road curbs with a deep curb detection network. Curbs locations are then referred to as straightforward marks to control the lateral motion of the vehicle. With our self-recorded dataset, our curb detection network achieves 93% pixel-level precision. In addition, experiments are performed with an intelligent sweeper to prove the accuracy and robustness of our proposed approach. Results demonstrate that the average lateral distance error and the maximum invalid rate are within 0.035 m and 9.2%, respectively. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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24 pages, 9857 KiB  
Article
UWB Based Relative Planar Localization with Enhanced Precision for Intelligent Vehicles
by Mingyang Wang, Xinbo Chen, Pengyuan Lv, Baobao Jin, Wei Wang and Yong Shen
Actuators 2021, 10(7), 144; https://0-doi-org.brum.beds.ac.uk/10.3390/act10070144 - 26 Jun 2021
Cited by 4 | Viewed by 2135
Abstract
Along with the rapid development of advanced driving assistance systems for intelligent vehicles, essential functions such as forward collision warning and collaborative cruise control need to detect the relative positions of surrounding vehicles. This paper proposes a relative planar localization system based on [...] Read more.
Along with the rapid development of advanced driving assistance systems for intelligent vehicles, essential functions such as forward collision warning and collaborative cruise control need to detect the relative positions of surrounding vehicles. This paper proposes a relative planar localization system based on the ultra-wideband (UWB) ranging technology. Three UWB modules are installed on the top of each vehicle. Because of the limited space on the vehicle roof compared with the ranging error, the traditional triangulation method leads to significant positioning errors. Therefore, an optimal localization algorithm combining homotopy and the Levenberg–Marquardt method is first proposed to enhance the precision. The triangular side lengths and directed area are introduced as constraints. Secondly, a UWB sensor error self-correction method is presented to further improve the ranging accuracy. Finally, we carry out simulations and experiments to show that the presented algorithm in this paper significantly improves the relative position and orientation precision of both the pure UWB localization system and the fusion system integrated with dead reckoning. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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21 pages, 3599 KiB  
Review
Towards Autonomous Driving: Review and Perspectives on Configuration and Control of Four-Wheel Independent Drive/Steering Electric Vehicles
by Peng Hang and Xinbo Chen
Actuators 2021, 10(8), 184; https://0-doi-org.brum.beds.ac.uk/10.3390/act10080184 - 05 Aug 2021
Cited by 42 | Viewed by 8418
Abstract
In this paper, the related studies of chassis configurations and control systems for four-wheel independent drive/steering electric vehicles (4WID-4WIS EV) are reviewed and discussed. Firstly, some prototypes and integrated X-by-wire modules of 4WID-4WIS EV are introduced, and the chassis configuration of 4WID-4WIS EV [...] Read more.
In this paper, the related studies of chassis configurations and control systems for four-wheel independent drive/steering electric vehicles (4WID-4WIS EV) are reviewed and discussed. Firstly, some prototypes and integrated X-by-wire modules of 4WID-4WIS EV are introduced, and the chassis configuration of 4WID-4WIS EV is analyzed. Then, common control models of 4WID-4WIS EV, i.e., the dynamic model, kinematic model, and path tracking model, are summarized. Furthermore, the control frameworks, strategies, and algorithms of 4WID-4WIS EV are introduced and discussed, including the handling of stability control, rollover prevention control, path tracking control and active fault-tolerate control. Finally, with a view towards autonomous driving, some challenges, and perspectives for 4WID-4WIS EV are discussed. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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21 pages, 5977 KiB  
Article
Extension Coordinated Multi-Objective Adaptive Cruise Control Integrated with Direct Yaw Moment Control
by Hongbo Wang, Youding Sun, Zhengang Gao and Li Chen
Actuators 2021, 10(11), 295; https://0-doi-org.brum.beds.ac.uk/10.3390/act10110295 - 06 Nov 2021
Cited by 5 | Viewed by 2325
Abstract
An adaptive cruise control (ACC) system can reduce driver workload and improve safety by taking over the longitudinal control of vehicles. Nowadays, with the development of range sensors and V2X technology, the ACC system has been applied to curved conditions. Therefore, in the [...] Read more.
An adaptive cruise control (ACC) system can reduce driver workload and improve safety by taking over the longitudinal control of vehicles. Nowadays, with the development of range sensors and V2X technology, the ACC system has been applied to curved conditions. Therefore, in the curving car-following process, it is necessary to simultaneously consider the car-following performance, longitudinal ride comfort, fuel economy and lateral stability of ACC vehicle. The direct yaw moment control (DYC) system can effectively improve the vehicle lateral stability by applying different longitudinal forces to different wheels. However, the various control objectives above will conflict with each other in some cases. To improve the overall performance of ACC vehicle and realize the coordination between these control objectives, the extension control is introduced to design the real-time weight matrix under a multi-objective model predictive control (MPC) framework. The driver-in-the-loop (DIL) tests on a driving simulator are conducted and the results show that the proposed method can effectively improve the overall performance of vehicle control system and realize the coordination of various control objectives. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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14 pages, 3958 KiB  
Article
In-Wheel Two-Speed AMT with Selectable One-Way Clutch for Electric Vehicles
by Dele Meng, Fei Wang, Yuhai Wang and Bingzhao Gao
Actuators 2021, 10(9), 220; https://0-doi-org.brum.beds.ac.uk/10.3390/act10090220 - 02 Sep 2021
Cited by 5 | Viewed by 3073
Abstract
To improve the efficiency of the electric vehicle (EV) drive systems and EV performance, the use of multi-speed transmissions and distributed drives has been studied extensively. In addition, to develop efficient and compact drive systems, new clutch solutions are needed. In this paper, [...] Read more.
To improve the efficiency of the electric vehicle (EV) drive systems and EV performance, the use of multi-speed transmissions and distributed drives has been studied extensively. In addition, to develop efficient and compact drive systems, new clutch solutions are needed. In this paper, we propose an in-wheel two-speed automatic mechanical transmission (IW-AMT) with a selectable one-way clutch (SOWC). The IW-AMT consists of a high-speed motor and a mechanical shift actuator, and it can realize shifting without power interruption, thus effectively reducing the unsprung mass and the technical specifications of the motor. We established a virtual prototype model of the IW-AMT to show the shifting process and evaluate the quality of shifting. The simulation results of the upshifting process indicated that the vehicle torque and velocity changed smoothly, and the maximum jerk is less than 10 m/s3. Furthermore, to improve the jerk induced by the downshifting process, we analyzed the momentary state of the SOWC struts that are dropped and attempted to improve the jerk from two aspects: improving the wet multi-plate clutch (WMPC) combination curve and improving the SOWC structure. The results indicated that the downshift-induced jerk can be reduced to 13 m/s3. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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16 pages, 6930 KiB  
Communication
Optimal Control Method of Path Tracking for Four-Wheel Steering Vehicles
by Xiaojun Tan, Deliang Liu and Huiyuan Xiong
Actuators 2022, 11(2), 61; https://0-doi-org.brum.beds.ac.uk/10.3390/act11020061 - 18 Feb 2022
Cited by 11 | Viewed by 4824
Abstract
Path tracking is a key technique for intelligent electric vehicles, while four-wheel steering (4WS) technology is of great significance to improve its accuracy and flexibility. However, the control methods commonly used in path tracking for a 4WS vehicle cannot take full advantage of [...] Read more.
Path tracking is a key technique for intelligent electric vehicles, while four-wheel steering (4WS) technology is of great significance to improve its accuracy and flexibility. However, the control methods commonly used in path tracking for a 4WS vehicle cannot take full advantage of the additional steering freedom of the 4WS vehicle, because of restricting the relationship between the front and rear wheels steering angle. To address this issue, we derive a kinematic model without the restriction based on the small-angle assumption. Then, the objective function and constraints of system control quantity optimization are designed based on the tracking error model. After the optimization problem is solved in the form of quadratic programming with constraints, the control sequence with the smallest performance index is obtained through rolling optimization. The proposed method is tested on a high-fidelity Carsim/Simulink co-simulation platform and an experimental vehicle. The results show that the standard deviation of the lateral error and the yaw angle error of the algorithm is less than 0.1 m and 3.0°, respectively. Compared with the other two algorithms, the control of the front and rear wheels angle of this method is more flexible and the tracking accuracy is higher. Full article
(This article belongs to the Special Issue Actuators for Intelligent Electric Vehicles)
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