DLMPCS‐based improved yaw stability control strategy for DDEV

Shi, Ke; Yuan, Xiaofang; Huang, Guoming; Zhang, Xizheng; Shen, Yongpeng

doi:10.1049/iet-its.2018.5523

Cited by 10 publications

(4 citation statements)

References 27 publications

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“…To calculate the required motor torque, a torque balance equation is formed for each tyre without considering the vehicle vertical load transfer [21]. Therefore, F x of a single tyre is calculated as F x = 1 4 ṁv , and the relationship between and T is expressed as:…”

Section: Driving Systemmentioning

confidence: 99%

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Multiple model-based fault-tolerant control system for distributed drive electric vehicle

Liu¹,

Shi

Yuan

et al. 2019

J Braz. Soc. Mech. Sci. Eng.

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Generally, the distributed drive electric vehicle (DDEV) works under different fault status, and this may lead to unstable operating performance. However, the conventional fault-tolerant controller is only suitable for one special fault status, and thus, the stability of DDEV is hard to be guaranteed efficiently. To deal with this problem, a novel multiple model-based fault-tolerant control system (MMFTCS) is proposed in this paper. The MMFTCS integrates an operating status recognizer and a fault-tolerant controller set. The operating status recognizer is designed to distinguish current operating status, where the matching degree between current operating status and typical operating mode set is detected using fuzzy logic. The faulttolerant controller set is designed to achieve optimal fault-tolerant control, and each fault-tolerant controller is designed for the corresponding typical operating mode by the model predictive controller. The output of the MMFTCS is computed by the weighted signal of each fault-tolerant controller to realize smooth switching. The simulation is carried on the MATLAB environment, and the results show that the MMFTCS has excellent fault-tolerant performance under various operating status. Keywords Distributed drive electric vehicle (DDEV) • Multiple model method • Various actuator faults • Model predictive controller (MPC)

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Section: Driving Systemmentioning

confidence: 99%

“…Here, F yf and F yr are linear functions of f and r [21], respectively. After linear approximation, the expression for F y can be simplified as (6):…”

Section: Steering Systemmentioning

confidence: 99%

Multiple model-based fault-tolerant control system for distributed drive electric vehicle

Liu¹,

Shi

Yuan

et al. 2019

J Braz. Soc. Mech. Sci. Eng.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The adaptability of non-optimization allocation methods is weak, especially on a high curvature or low adhesion road, so optimization methods have attracted more attention. Shi et al [25] proposed a torque optimization allocation based on sequential quadratic programming, whose optimization goal was to minimize tire adhesion utilization. Song et al [26] and Hang et al [27] aimed to minimize the longitudinal force of tire and increase the stability margin and solved the torque optimization allocation problem based on the least squares method, which increased computational efficiency.…”

Section: Introductionmentioning

confidence: 99%

Direct Yaw Moment Control for Distributed Drive Electric Vehicles Based on Hierarchical Optimization Control Framework

Hu,

Zhang,

Zhang

et al. 2024

Mathematics

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Direct yaw moment control (DYC) can effectively improve the yaw stability of four-wheel distributed drive electric vehicles (4W-DDEVs) under extreme conditions, which has become an indispensable part of active safety control for 4W-DDEVs. This study proposes a novel hierarchical DYC architecture for 4W-DDEVs to enhance vehicle stability during ever-changing road conditions. Firstly, a vehicle dynamics model is established, including a two-degree-of-freedom (2DOF) vehicle model for calculating the desired yaw rate and sideslip angle as the control target of the upper layer controller, a DDEV model composed of a seven-degree-of-freedom (7DOF) vehicle model, a tire model, a motor model and a driver model. Secondly, a hierarchical DYC is designed combining the upper layer yaw moment calculation and low layer torque distribution. Specifically, based on Matlab/Simulink, improved linear quadratic regulator (LQR) with weight matrix optimization based on inertia weight cosine-adjustment particle swarm optimization (IWCPSO) is employed to compute the required additional yaw moment in the upper-layer controller, while quadratic programming (QP) is used to allocate four motors’ torque with the optimization objective of minimizing the tire utilization rate. Finally, a comparative test with double-lane-change and sinusoidal conditions under a low and high adhesion road surface is conducted on Carsim and Matlab/Simulink joint simulation platform. With IWCPSO-LQR under double-lane-change (DLC) condition on a low adhesion road surface, the yaw rate and sideslip angle of the DDEV exhibits improvements of 95.2%, 96.8% in the integral sum of errors, 94.9%, 95.1% in the root mean squared error, and 78.8%, 98.5% in the peak value compared to those without control. Simulation results indicate the proposed hierarchical control method has a remarkable control effect on the yaw rate and sideslip angle, which effectively strengthens the driving stability of 4W-DDEVs.

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“…With the development of vehicle technology, the automobile penetration rate rises quickly and the road safety becomes very important [1]. In recent years, many effort have been made to improve the vehicle performance, including suspension control [2–5], lateral and yaw stability control [6, 7], power system control [8, 9] and active steering control [10–12]. For the driving safety, spinning and skidding are two situations which should be avoided, and yaw moment control has been proved as an effective control strategy for that [13].…”

Section: Introductionmentioning

confidence: 99%

Non‐fragile multi‐objective linear parameter‐varying controller design for vehicle lateral stability

Zhao

et al. 2020

IET Control Theory & Appl

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DLMPCS‐based improved yaw stability control strategy for DDEV

Cited by 10 publications

References 27 publications

Multiple model-based fault-tolerant control system for distributed drive electric vehicle

Multiple model-based fault-tolerant control system for distributed drive electric vehicle

Direct Yaw Moment Control for Distributed Drive Electric Vehicles Based on Hierarchical Optimization Control Framework

Non‐fragile multi‐objective linear parameter‐varying controller design for vehicle lateral stability

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