Article
Green & Sustainable Science & Technology
Pingshu Ge, Lie Guo, Jindun Feng, Xiaoyue Zhou
Summary: This paper studies the adaptive stability control in battery electric vehicles (BEVs) with in-wheel motors. A joint weighting control of the yaw rate and sideslip angle is carried out based on the sliding model algorithm, and a weight coefficient is designed using a fuzzy algorithm to achieve adaptive direct yaw moment control. Optimal torque distribution is designed with the minimum sum of four tire load rates as the optimization objective, considering the road adhesion coefficient and maximum motor torque constraint. The simulation results show that the proposed control methods effectively improve vehicle adaptive stability control.
Article
Computer Science, Information Systems
Lei Qiu, Shaopeng Zhu, Dong Liu, Zhiwei Xiang, Hong Fu, Huipeng Chen
Summary: In this paper, the optimal distribution of driving torque of the wheel-side motors for distributed four-wheel-drive electric buses is studied. A fuzzy yaw moment control strategy based on the golden section search algorithm is proposed to address the issues of poor economy and failure of switching control. Through simulation and experimentation, it is shown that the proposed strategy can improve torque distribution efficiency, enhance overall energy utilization, and improve stability during steering conditions.
Article
Chemistry, Analytical
Boyuan Li, Chao Huang, Yang Wu, Bangji Zhang, Haiping Du
Summary: This study proposes a comprehensive vehicle dynamics model to describe the dynamics performance of a vehicle after a tire blow-out, and presents an integrated control framework for combined yaw plane and roll-plane stability control. The control framework includes a vehicle state predictor, an upper-level control mode supervisor, and a lower-level 14-DOF model predictive controller. Simulation tests are conducted to verify the effectiveness of the proposed control strategy.
Article
Engineering, Mechanical
Qiu Xia, Long Chen, Xing Xu, Yingfeng Cai, Te Chen
Summary: This paper proposes a hierarchical control strategy for autonomous ground vehicles with within-wheel motors, achieving accurate trajectory tracking and vehicle yaw stability control. The control method combines model predictive control algorithm, high-order sliding mode control method, and double power reaching rate-based sliding mode control method.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2023)
Article
Engineering, Mechanical
Peikun Sun, Annika Stensson Trigell, Lars Drugge, Jenny Jerrelind
Summary: This study proposes a control method that combines DYC for energy-efficiency and DYC for stability to improve energy efficiency and stability of electric vehicles during turning maneuvers. By using DYC for energy efficiency during non-safety-critical cornering and combining DYC for energy efficiency with DYC for stability during cornering maneuvers containing both non-safety-critical and safety-critical parts, energy savings of 12% to 18% can be achieved.
VEHICLE SYSTEM DYNAMICS
(2022)
Article
Engineering, Mechanical
Xiaoqiang Sun, Yujun Wang, Yingfeng Cai, Pak Kin Wong, Long Chen
Summary: This research proposes a novel adaptive nonsingular fast terminal sliding mode (ANFTSM) control scheme to improve the bus curve driving stability and safety on slippery roads. By establishing a more accurate bus lateral dynamics model and adopting the robust least-squares allocation method for tire forces, the tire nonlinear mechanical properties and the effectiveness of the YSC control system are effectively addressed.
CHINESE JOURNAL OF MECHANICAL ENGINEERING
(2021)
Article
Chemistry, Multidisciplinary
Yanxin Nie, Minglu Zhang, Xiaojun Zhang
Summary: A coordinated control strategy for intelligent electric vehicle trajectory tracking and stability is proposed based on hierarchical control theory. The strategy includes an Adaptive Spiral Sliding Mode controller to reduce deviation in trajectory tracking and a tire force optimal distribution method for directional control. Simulation experiments validate the effectiveness of the control strategy in controlling vehicle trajectory deviation while ensuring lateral stability.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Mechanical
Mengjian Tian, Qiyuan Hu, Bingzhao Gao, Haitao Ding, Hong Chen
Summary: This paper proposes a new chassis structure that reduces the yaw rotational inertia of an electric vehicle by adding a oscillatable component to the battery pack, thus improving the handling performance.
VEHICLE SYSTEM DYNAMICS
(2022)
Article
Engineering, Electrical & Electronic
Huimin Zhu, Feng Zhang, Yong Zhang, Liang Su, Gang Gong
Summary: This study presents an improved adaptive nonsingular fast terminal sliding mode (ANFTSM) control method to enhance the stability of distributed drive electric buses. The method introduces an uncertainty term and adjusts the weighting factor in the sliding surface to improve control effectiveness. The algorithm is verified through co-simulation and shown to be effective.
Article
Automation & Control Systems
Pengxu Li, Panshuo Li, Bin Zhang, Jing Zhao, Baozhu Du
Summary: This paper introduces a control strategy for enhancing the lateral dynamics stability and handling performance of FWIA electric vehicles through a double layers control scheme, including an upper layer controller and a lower layer force distribution method. Simulation results confirm the effectiveness of the proposed strategy.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2021)
Article
Automation & Control Systems
Rahul Moghe, Maruthi R. Akella
Summary: This paper introduces a projection scheme to handle eigenvalue bounds for adaptive control with uncertain symmetric matrix parameters. Conventional parameter projection techniques are generally unable to handle explicit eigenvalue bounds. The continuous projection scheme presented here maintains the closed-loop stability properties for adaptive controllers while simultaneously satisfying a priori available eigenvalue bounds of the uncertain symmetric matrix valued parameters. The new projection shows improved performance in numerical simulations of rigid body attitude tracking control and trajectory tracking of robotic manipulators with unknown inertia parameters.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Chemistry, Multidisciplinary
Hyeon-Woo Kim, Hyun-Rok Cha
Summary: The study tackled the issue of vehicle stability by mathematically formulating a variable mass understeer gradient (VMUG) for electric vehicle trucks, introducing a slip control method that outperformed conventional approaches in simulated scenarios for both normal loading and overloading conditions.
APPLIED SCIENCES-BASEL
(2021)
Article
Automation & Control Systems
Zichen Zheng, Xuan Zhao, Shu Wang, Qiang Yu, Haichuan Zhang, Zhaoke Li, Hua Chai, Qi Han
Summary: This paper proposes a hierarchical extension coordinated controller that considers the bounded rationality of the control system to address traditional stability control interference on driving speed and driver operation. The controller divides the operating state of vehicles using the extension phase plane at the supervisory layer. At the coordinated decision-making layer, an evolutionary game model is used to determine coordination weights for active front-wheel steering (AFS) and direct yaw moment control (DYC). Results show that the bounded rationality coordinated controller achieves better stability control with less intervention on driving speed, as compared to a completely rational independent control system, as confirmed by vehicle testing.
CONTROL ENGINEERING PRACTICE
(2023)
Article
Computer Science, Information Systems
Huipeng Chen, Weiyang Wang, Shaopeng Zhu, Sen Chen, Jian Gao, Rougang Zhou, Wei Wei
Summary: By introducing a wheel motor, the chassis structure of the electric bus is simplified, and its response speed and controllability are greatly improved. This study proposes an adaptive distributed drive control strategy, using an adaptive fuzzy controller and a rule distribution method to adjust the steering characteristics and achieve optimal driving torque distribution. Experimental results verify that adaptive fuzzy control can significantly reduce the deviations of yaw rate and vehicle sideslip angle, improving the lateral stability of electric buses under complex driving conditions.
Article
Engineering, Civil
Zheng Chen, Byungkyu Brian Park
Summary: In this paper, a CACC algorithm with unconnected vehicles (CACCu) is proposed to improve the usability of CACC in mixed traffic. By utilizing the information from a connected preceding vehicle, CACCu can closely follow an unconnected preceding vehicle. The algorithm maintains string stability and outperforms existing ACC and CCC in terms of string stability, ride comfort, safety maintenance, and fuel consumption.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Automation & Control Systems
Xingyu Zhou, Zejiang Wang, Heran Shen, Junmin Wang
Summary: This paper introduces a mixed L-1/H-2 observer for accurately estimating the driver's steering torque in automated and assistance driving systems. Experimental results demonstrate that the proposed method outperforms the traditional method.
JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME
(2022)
Article
Computer Science, Theory & Methods
Yunhao Bai, Li Li, Zejiang Wang, Xiaorui Wang, Junmin Wang
Summary: The rapid growth of autonomous driving presents new challenges to traditional vehicle control systems, leading to the proposal of a two-tier real-time scheduling framework AutoE2E that reduces deadline miss ratio and maximizes computing precision for driving control.
Article
Engineering, Civil
Zejiang Wang, Xingyu Zhou, Junmin Wang
Summary: This paper proposes an algebraic framework for evaluating a class of car-following models with linearly identified parameters, providing a new method for evaluating and comparing different car-following models.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Chuan Hu, Junmin Wang
Summary: This paper introduces a quantitative dynamic model of driver trust in ACC, applied to a trust-based ACC system. By improving the control barrier functions and introducing a new performance function, stable system operation with specific performance requirements is achieved. High-fidelity CarSim simulations validate the effectiveness of the proposed trust model and control approach.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Yan Ma, Jian Chen, Junmin Wang, Yanchuan Xu, Yuexuan Wang
Summary: In this paper, a new passivity-based control approach is designed to improve the robustness and stability of autonomous vehicles in performing path-tracking tasks using a port-Hamiltonian model. The energy-shaping method is utilized to ensure stability, and an optimization-based tire load distribution method is designed to minimize the sum of tire loads.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Zejiang Wang, Adrian Cosio, Junmin Wang
Summary: The study proposes a method to allocate implementation resources based on driver maneuver capabilities instead of adding extra electronic computing units. By adjusting control horizons, resources can be allocated to different types of collision-avoidance assistance systems, improving driving safety without increasing the overall usage of implementation resources.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Yao Ma, Junmin Wang
Summary: This study proposes an integrated model to assess and predict vehicle fuel economy based on drivers' behaviors, using naturalistic traffic data. The results reveal significant correlation between driving behaviors and fuel consumption, showing that even in the same traffic conditions, different driving behaviors can lead to significant differences in fuel consumption.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Civil
Xingyu Zhou, Zejiang Wang, Junmin Wang
Summary: This paper proposes a novel methodology for synthesis of ground vehicle path-following controller based on the energy-to-peak robust control theory, and its robustness and disturbance attenuation ability are experimentally verified on a scaled car.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Yujing Zhou, Zejiang Wang, Junmin Wang
Summary: This article presents a novel and computationally efficient algorithm for illumination-resilient lane detection and path-following tasks in autonomous driving. The algorithm performs lane detection in the hue-saturation-value color space by distinguishing colored lane marks from the background.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Heran Shen, Zejiang Wang, Xingyu Zhou, Maxavier Lamantia, Kuo Yang, Pingen Chen, Junmin Wang
Summary: This article proposes a novel hybrid deterministic-stochastic methodology to accurately predict the future velocity and energy consumption of electric vehicles using various inputs, and experimental results demonstrate its superior performance compared to two popular baseline algorithms in velocity and energy consumption estimation.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Article
Engineering, Electrical & Electronic
Heran Shen, Xingyu Zhou, Hyunjin Ahn, Maxavier Lamantia, Pingen Chen, Junmin Wang
Summary: This article proposes a data-driven approach to predict the speed and energy consumption of electric vehicles, taking into account road features and individual driving characteristics. Improved neural networks are used to extract information and a novel energy consumption model is suggested. Experimental results show that the proposed method provides accurate predictions.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2023)
Article
Automation & Control Systems
Zejiang Wang, Xingyu Zhou, Adrian Cosio, Junmin Wang
Summary: This paper proposes a novel nonlinear driver-vehicle-road (DVR) model that explicitly considers road curvature. A flatness-based lane-keeping assistance (LKA) system is designed based on this model. Model-Free Control is introduced to compensate for system modeling errors, and the proposed control framework is validated through simulations and experiments.
CONTROL ENGINEERING PRACTICE
(2023)
Article
Automation & Control Systems
Xingyu Zhou, Heran Shen, Zejiang Wang, Hyunjin Ahn, Junmin Wang
Summary: This article proposes a novel driver-centric and neuro-adaptive-control-based lane-keeping assistance system (LKAS) to address the issue of vehicle roadway departure accidents. The system utilizes a noncertainty-equivalent adaptive control design scheme and an adaptive neural network that captures the human driver's steering behavior. A pilot study using a high-fidelity driving simulator validates the effectiveness of the proposed LKAS.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Computer Science, Artificial Intelligence
Xingyu Zhou, Zejiang Wang, Heran Shen, Junmin Wang
Summary: This paper proposes a novel control architecture to tackle the backlash issue in ground vehicle path-tracking. The dynamics of the steering system's backlash are compensated using an adaptive inverse controller and robustified with sigma modification. Hardware experiments demonstrate the superiority of the proposed solution.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2022)
Article
Automation & Control Systems
Zejiang Wang, Xingyu Zhou, Junmin Wang
Summary: Traditional automated vehicle path-tracking algorithms require accurate plant models, while data-driven controllers have become popular for not relying on predefined plant models. Model-free control (MFC) offers a straightforward solution for ground vehicle path tracking, but its control gain tuning remains a challenge.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)