Coordinated control of distributed drive electric vehicle by TVC and ESC based on function allocation

Liang, Xiutian; Wang, Qidong; Chen, Wuwei; Zhao, Lian

doi:10.1177/09544070211026185

Cited by 6 publications

(5 citation statements)

References 29 publications

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“…The 2-DOF bicycle model is used as the ideal reference model. According to Alleyne, 11 the state equation of the tracking error between the four-wheel steering system and the desired model can be obtained as (34).…”

Section: Steering Tracking Control Sub Modulementioning

confidence: 99%

“…The expressions of A, B, and E are as follows. The equation (34) above can be transformed into the standard linear quadratic optimal solution problem to minimize the following performance function J.…”

Section: Steering Tracking Control Sub Modulementioning

confidence: 99%

“…Xiang et al 31 presented an MPC method to obtain the front wheel steering angle and two virtual generalized forces. Yao et al 32 and Taghavifar 33 combined front wheel steering with DYC, while Liang et al 34 and Ruan et al 35 used DYC alone, to improve the stability of the vehicle.…”

Section: Introductionmentioning

confidence: 99%

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Path tracking and stability integrated control of intelligent vehicles under steering collision avoidance

Lai

Huang

2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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In order to improve the path tracking performance and stability of intelligent vehicles during steering and collision avoidance working condition, an integrated control method combining four-wheel steering, active suspension and direct yaw-moment is proposed. Firstly, a unified chassis dynamics model with 18 degrees-of-freedom (DOF) is established, which includes steering, braking and suspension subsystems. Phase plane analysis results for both traditional 2-DOF bicycle model and the 18-DOF model are compared. The results show that although the uneven road has a certain influence on the phase portraits of sideslip angle and sideslip angular velocity of the 18-DOF model, the overall trend is consistent with those of the 2-DOF model. Secondly, a general control framework for steering and collision avoidance of autonomous vehicle is put forward, consisting of the steering control for path tracking, and active suspension and direct yaw-moment control for stability. The collision avoidance reference path is planned by the fifth-degree polynomial, and three types of steering control methods including optimal control front wheel steering, optimal control four-wheel steering and front wheel steering combined with feedforward and feedback control, are adopted for comparison. The main contribution of this paper is that the role of active suspension is considered in the path tracking and stability integrated control of intelligent vehicles under steering collision avoidance. The active suspension subsystem uses optimal control method by two different kinds of weight coefficients, which can be switched between “comfort mode” and “sport mode” based on the vehicle lateral acceleration. According to the phase portraits of vehicle center of gravity sideslip angle and sideslip angular velocity, the direct-yaw moment control system adopts proportional differential control method based on the distance from the state point to the stability boundary. Finally, simulations and comparative analysis are compared among four different control systems on high and low adhesion roads. The research results indicate that the integrated control system can improve the vehicle path tracking performance and stability significantly.

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Section: Steering Tracking Control Sub Modulementioning

confidence: 99%

Section: Steering Tracking Control Sub Modulementioning

confidence: 99%

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Path tracking and stability integrated control of intelligent vehicles under steering collision avoidance

Lai

Huang

2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…There have been many research achievements in the lateral stability control of DDEVs, among which direct yaw moment control (DYC) can significantly improve the stability and handling performance of the vehicle (Liang et al, 2022). The main methods of DYC include PID control (Novellis et al, 2014), SMC (Mousavinejad et al, 2017), nonlinear three-step control (Zhao et al, 2015), and MPC (Ao et al, 2023; Jalali et al, 2018; Reza et al, 2022; Xie et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…For stability control, the boundary of the stability domain needs to be considered, and the phase plane is widely used in analyzing the system’s stability (Han et al, 2018; Li et al, 2021). Based on phase plane theory, Liang et al (2022) fitted the stability domain boundary of the side slip angle and side slip angle rate phase plane. They used extension control to coordinate the active front wheel steering controller (AFS) and DYC controller weights to improve vehicle handling stability Li et al (2021).…”

Section: Introductionmentioning

confidence: 99%

Coordinated control of longitudinal and lateral movements considering dynamics for distributed drive electric vehicle platoon on curved roads

Fang

Wang

Zhao

et al. 2023

Transactions of the Institute of Measurement and Control

Self Cite

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The control goal of the vehicle platoon is to maintain the same speed and desired distance. Most current studies are based on simplified vehicle models, and the leader’s state is also rarely considered. However, under complex working conditions, such as low adhesion or curves, the lateral stability of the platoon will be difficult to guarantee, and tracking errors of desired speed and spacing may further increase. To solve the above problems, a new hierarchical coordinated control strategy is proposed. Taking distributed drive electric vehicles (DDEVs) as research objects, the upper control level establishes a stability situation assessment model according to the vehicle’s dynamic characteristics. At the medium control level, variable weight model predictive control (MPC) coordinates conflicts between longitudinal tracking and lateral stability. A correction term is also introduced to revise the prediction model. At the same time, the weight of different control objectives of the leader and following vehicle was adjusted, respectively. Torque distribution is carried out at the lower level controller. Finally, the control strategy is tested on a hardware-in-the-loop (HIL) platform. The results show that the proposed control strategy can ensure lateral stability while improving the tracking performance of the vehicle platoon.

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A New Stopping Sight Distance Model and Fuzzy Reliability Analysis Comparison

Chen

et al. 2022

IEEE Access

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Aiming at the research on the stopping sight distance of the highway, on the basis of calculating the stopping sight distance in the current specification, the actual braking process of the car is divided into three stages: the driver's reaction stage, the braking force rising stage and the continuous braking stage. The calculation model of the complete braking stage is analyzed by MATLAB, and then the calculation model of the stopping sight distance of the ESC system is proposed. Considering the ambiguity of the operating speed, the fuzzy reliability theory is introduced to establish the function of the fuzzy reliability of the stopping sight distance. Using the Gaussian fuzzy number and the center point method, the reliability index and failure probability of the stopping sight distance are obtained, and the safety of the stopping sight distance is evaluated. According to the "Uniform Standard for Reliability Design of Highway Engineering Structures", the traditional reliability calculation method and the fuzzy reliability calculation method are used to calculate the stopping sight distance value that meets the corresponding reliability index of the highway safety level. The calculated value of the system stopping sight distance model is used as a reference, and the reliability index and failure probability of the two reliability calculation methods are calculated. The calculation results show that: compared with the traditional reliability calculation method, the fuzzy reliability calculation method calculates the stopping sight distance value with higher reliability index, lower failure probability and higher calculation accuracy. Implementing the road design based on the stopping sight distance value calculated by the fuzzy reliability theory can improve the road safety.

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Coordinated control of distributed drive electric vehicle by TVC and ESC based on function allocation

Cited by 6 publications

References 29 publications

Path tracking and stability integrated control of intelligent vehicles under steering collision avoidance

Path tracking and stability integrated control of intelligent vehicles under steering collision avoidance

Coordinated control of longitudinal and lateral movements considering dynamics for distributed drive electric vehicle platoon on curved roads

A New Stopping Sight Distance Model and Fuzzy Reliability Analysis Comparison

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