Yaw and Lateral Stability Control for Four-Wheel Steer-by-Wire System

Zhao, Wanzhong; Qin, XiaoXi; Wang, Chunyan

doi:10.1109/tmech.2018.2812220

Cited by 115 publications

(52 citation statements)

References 17 publications

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“…Highly automated vehicles are likely to be on public roads within a few years. Before transitioning to fully autonomous driving, driver behavior should be better understood and integrated to enhance vehicle performance and traffic efficiency [6]- [9]. To address these challenges, researchers have explored advanced driver assistance systems (ADAS), and humanmachine interface (HMI) from a variety of points of view [10], [11].…”

Section: A Driver-vehicle Interactionsmentioning

confidence: 99%

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Driving-Style-Based Codesign Optimization of an Automated Electric Vehicle: A Cyber-Physical System Approach

Sangiovanni‐Vincentelli

et al. 2019

IEEE Trans. Ind. Electron.

235

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This paper studies the co-design optimization approach to determine how to optimally adapt automatic control of an intelligent electric vehicle to driving styles. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the plant and controller parameters for an automated electric vehicle, in view of vehicle's dynamic performance, drivability, and energy along with different driving styles. System description, requirements, constraints, optimization objectives and methodology are investigated. Driving style recognition algorithm is developed using unsupervised machine learning and validated via vehicle experiments. Adaptive control algorithms are designed for three driving styles with different protocol selections. Performance exploration method is presented. Parameter optimizations are implemented based on the defined objective functions. Test results show that an automated vehicle with optimized plant and controller can perform its tasks well under aggressive, moderate, and conservative driving styles, further improving the overall performance. The results validate the feasibility and effectiveness of the proposed CPS-based co-design optimization approach.

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Section: A Driver-vehicle Interactionsmentioning

confidence: 99%

“…The motor torque is modelled as a first-order reaction, as shown in equation (8). The models for the drivetrain dynamics and halfshaft torque can be given by equation (9) and 10…”

Section: A Electric Powertrain Systemmentioning

confidence: 99%

Driving-Style-Based Codesign Optimization of an Automated Electric Vehicle: A Cyber-Physical System Approach

Sangiovanni‐Vincentelli

et al. 2019

IEEE Trans. Ind. Electron.

235

View full text Add to dashboard Cite

show abstract

“…From the perspective of system configuration, EVs can be categorized into two distinct types: centrally driven type and distributed-drive type. Compared with the centrally driven layout, the latter case incorporates an electric motor in the hub of a wheel for direct drive, and it provides numerous advantages, including more available chassis space, prompt system response and high energy efficiency [5][6][7][8][9]. In this context, distributed-drive EVs are attracting more attention from both academia and automobile industry and are also considered as the direction of current and future EVs.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Analysis and Optimization of Dynamic Vibration-Absorbing Structures for Electric Vehicles Driven by In-Wheel Motors

et al. 2019

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Distributed-drive electric vehicles (EVs) replace internal combustion engine with multiple motors, and the novel configuration results in new dynamic-related issues. This paper studies the coupling effects between the parameters and responses of dynamic vibration-absorbing structures (DVAS) for EVs driven by in-wheel motors (IWM). Firstly, a DVAS-based quarter suspension model is developed for distributed-drive EVs, from which nine parameters and five responses are selected for the coupling effect analysis. A two-stage global sensitivity analysis is then utilized to investigate the effect of each parameter on the responses. The control of the system is then converted into a multiobjective optimization problem with the defined system parameters being the optimization variables, and three dynamic limitations regarding both motor and suspension subsystems are taken as the constraints. A particle swarm optimization approach is then used to either improve ride comfort or mitigate IWM vibration, and two optimized parameter sets for these two objects are provided at last. Simulation results provide in-depth conclusions for the coupling effects between parameters and responses, as well as a guideline on how to design system parameters for contradictory objectives. It can be concluded that either passenger comfort or motor lifespan can be reduced up to 36% and 15% by properly changing the IWM suspension system parameters.This section introduces the two-step GSA and analyzes the effects each parameter has on the system response characteristics.

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“…Deviation of these sensors' signals may lead to spurious triggering or misoperation of the control system. Once a fault occurs, it causes serious consequences [1][2][3], so the possibility to diagnose and reconstruct potential faults of these sensors is the key issue of safety and stability of a forklift. To detect an incipient fault as early as possible to avoid serious damage to the controlled system, a fuzzy relational sliding mode observer (FRSMO) is proposed [4].…”

Section: Introductionmentioning

confidence: 99%

Sensor Fault Reconstruction based on Adaptive Sliding Mode Observer for Forklift Fault-Tolerant Control System

Zhang

Xiao

2020

Applied Sciences

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For the problem of multiple sensor fault detection and reconstruction in the forklift fault-tolerant control system, a sliding mode observer (SMO) with adaptive regulation law is proposed. Based on the three-degree-of-freedom (3-DOF) model of forklift, a linear state equation with output disturbance is designed as its equivalent sensor fault model. The sensor fault is converted into an actuator fault by defining an auxiliary state variable as an output signal filter. Then the SMO-based method of sensor fault detection and reconstruction is given. Without knowing the upper bound of an unknown fault, an adaptive sliding mode observer (ASMO) can also be effective through the adaptive algorithm. Finally, experimental results further verify the effectiveness of the method, and provide a foundation for forklift fault-tolerant control.

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Yaw and Lateral Stability Control for Four-Wheel Steer-by-Wire System

Cited by 115 publications

References 17 publications

Driving-Style-Based Codesign Optimization of an Automated Electric Vehicle: A Cyber-Physical System Approach

Driving-Style-Based Codesign Optimization of an Automated Electric Vehicle: A Cyber-Physical System Approach

Comprehensive Analysis and Optimization of Dynamic Vibration-Absorbing Structures for Electric Vehicles Driven by In-Wheel Motors

Sensor Fault Reconstruction based on Adaptive Sliding Mode Observer for Forklift Fault-Tolerant Control System

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