Lateral Stability Control of Four-Wheel Independent Drive Electric Vehicles Based on Model Predictive Control

Huang, Bin; Wu, Sen; Huang, Song; Fu, Xiang

doi:10.1155/2018/6080763

Cited by 17 publications

(8 citation statements)

References 19 publications

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“…The forces and moments output in the following control layer are distributed to four wheels for specific optimization purposes. LQP and pseudo-inverse are used to solve the math calculation in the most studies of the tire force distribution [11,12]. In this paper, LQP is introduced to distribute the tire force, as it is easier to solve optimization problems and add constraints.…”

Section: Tire Force Allocator Layermentioning

confidence: 99%

“…As an actuator redundancy system, the primary challenge is dealing with the physical constraints and the actuator redundancy. Most of the solutions are considering it as an optimization problem; therefore, model predictive control theory (MPC) and linear quadratic programming (LQP) are used in tire force allocation [11]. Other studies focus on the pseudo inverse algorithm and design it for dynamically allocating the desired external yaw moment into the redundant tire actuators because of its faster calculation [12].…”

Section: Introductionmentioning

confidence: 99%

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Approach of Coordinated Control Method for Over-Actuated Vehicle Platoon based on Reference Vector Field

et al. 2019

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Featured Application: The proposed method is applied to the coordinated control for over-actuated vehicle platoon with an integrated hierarchical controller.Abstract: Collaborative vehicle platoon control with full drive-by-wire vehicles with four-wheel independent driving and steering (FWIDSV) has attracted broader research interests. However, the problem of cooperative vehicle platoon control in two-dimensional driving scenes remains to be solved. This paper proposes a coupling control method for path tracking and spacing-maintaining based on the reference vector field (RVF). An integrated hierarchical control structure, including the following control layer, tire force allocator layer, and an actuator controlling layer for FWIDSV is presented. Inside, the next control layer was designed according to the spacing control strategy and RVF within the limitation of the friction circle. For verifying the effectiveness of this control method, sufficient conditions for error convergence are analyzed when considering the influence of the critical parameters on the particle dynamics model. The tire force allocator layer is designed based on linear quadratic programming (LQP), which is used to distribute the total forces and yaw moment. The sliding mode control (SMC) is employed to track the desired tire forces in the actuator controlling layer. The proposed control methods are validated through simulation in intelligent cruise control (ICC) and platoon merging scenarios. The results demonstrate an effective FWIDSV platoon control approach that is based on the RVF in the 2-D driving scenes.

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Section: Tire Force Allocator Layermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Approach of Coordinated Control Method for Over-Actuated Vehicle Platoon based on Reference Vector Field

et al. 2019

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“…Considering the dynamic characteristics of the system, rolling optimization is used [22]. The first control input of the control sequence which is obtained is applied to the system.…”

Section: Speed Optimization and Lower Level Controlmentioning

confidence: 99%

Research on Speed Optimization Strategy of Hybrid Electric Vehicle Queue Based on Particle Swarm Optimization

Wang

Shi

et al. 2018

Mathematical Problems in Engineering

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Traffic lights intersections are common in cities and have an impact on the energy consumption of vehicles, so it is significant to optimize the velocities of vehicles in urban road conditions. The novel speed optimization strategy for hybrid electric vehicle (HEV) queue that helps reduce fuel consumption and improve traffic efficiency is presented in this paper, where real-world traffic signal information is used to construct the research scenario. The initial values of the target velocities are obtained based on the signal phase and timing (SPAT). Then the particle swarm optimization (PSO) algorithm is used to solve the nonlinear constrained problem and obtain the optimal target velocities based on vehicle to vehicle communication (V2V) and vehicle to infrastructure communication (V2I). The lower controller, which applies rule based control strategy, is designed to split the power of the engine and two electric motors in a power split HEV, which is quite promising because of its advantages in fuel economy. Simulation results demonstrate the superior performance of the proposed strategy in reducing fuel consumption of the HEV queue and improving traffic smoothness.

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“…However, as a result of the high-frequency switching of the sliding mode controller, a "chattering" phenomenon occurs to a certain degree, which has a certain impact on the control accuracy of vehicle dynamics. Huang et al studied model predictive control theory and designed a yaw moment decision controller [26]. Moreover, on the basis of the theory of tire friction ellipse, the wheel torque was distributed by minimizing the sum of the adhesion coefficients of the four tires.…”

Section: Introductionmentioning

confidence: 99%

Lateral Stability Control of Four-Wheel-Drive Electric Vehicle Based on Coordinated Control of Torque Distribution and ESP Differential Braking

Chen

Yang

et al. 2021

Actuators

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This research focuses on four-wheel-drive electric vehicles. On the basis of the hierarchical coordinated control strategy, the coordinated control system of driving force distribution regulation and differential braking regulation was designed to increase the electric vehicles steering stability under special road working conditions. A seven-degree-of-freedom model of an electric vehicle was established in MATLAB/Simulink, and then a hierarchical coordination control model of the Electronic stability program and dynamic torque distribution control system was established. Adaptive fuzzy control was applied to ESP and, based on the neural network PID control, a torque distribution control system was designed. On the basis of the proposed coordinated control model, a performance simulation and a hardware-in-the-loop test of the control system under the typical working condition of single line shift were carried out. From the final results, it can be seen that the proposed control strategy can greatly improve the safety of the vehicle after serious side slip, increase the stability of the whole vehicle, and effectively increase the vehicle lateral stability.

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Lateral Stability Control of Four-Wheel Independent Drive Electric Vehicles Based on Model Predictive Control

Cited by 17 publications

References 19 publications

Approach of Coordinated Control Method for Over-Actuated Vehicle Platoon based on Reference Vector Field

Approach of Coordinated Control Method for Over-Actuated Vehicle Platoon based on Reference Vector Field

Research on Speed Optimization Strategy of Hybrid Electric Vehicle Queue Based on Particle Swarm Optimization

Lateral Stability Control of Four-Wheel-Drive Electric Vehicle Based on Coordinated Control of Torque Distribution and ESP Differential Braking

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