Coordinated control of steer‐by‐wire and brake‐by‐wire for autonomous emergency braking on split‐μ roads

Xue, Zhongjin; Li, Chenfeng; Wang, Xiangyu; Zhang, Lipeng; Zhong, Zhihua

doi:10.1049/iet-its.2020.0184

Cited by 10 publications

(3 citation statements)

References 35 publications

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“…ABS adjusts brake torque by setting slip ratio and angular acceleration thresholds and achieves steering compensation and brake coordination through yaw rate thresholds. Its advantages lie in simplicity and independence from state observation, but it lacks robustness and overly relies on calibration, affecting driving comfort [19,20]. Some scholars have implemented ABS using slip mode control, taking actual and optimal slip ratios as inputs, designing a slip surface to output braking torque, and adjusting the actual slip ratio to the target.…”

Section: Introductionmentioning

confidence: 99%

An NMPC-Based Integrated Longitudinal and Lateral Vehicle Stability Control Based on the Double-Layer Torque Distribution

Bai,

Wang,

Jia

et al. 2024

Sensors

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With the ongoing promotion and adoption of electric vehicles, intelligent and connected technologies have been continuously advancing. Electrical control systems implemented in electric vehicles have emerged as a critical research direction. Various drive-by-wire chassis systems, including drive-by-wire driving and braking systems and steer-by-wire systems, are extensively employed in vehicles. Concurrently, unavoidable issues such as conflicting control system objectives and execution system interference emerge, positioning integrated chassis control as an effective solution to these challenges. This paper proposes a model predictive control-based longitudinal dynamics integrated chassis control system for pure electric commercial vehicles equipped with electro–mechanical brake (EMB) systems, centralized drive, and distributed braking. This system integrates acceleration slip regulation (ASR), a braking force distribution system, an anti-lock braking system (ABS), and a direct yaw moment control system (DYC). This paper first analyzes and models the key components of the vehicle. Then, based on model predictive control (MPC), it develops a controller model for integrated stability with double-layer torque distribution. The required driving and braking torque for each wheel are calculated according to the actual and desired motion states of the vehicle and applied to the corresponding actuators. Finally, the effectiveness of this strategy is verified through simulation results from Matlab/Simulink. The simulation shows that the braking deceleration of the braking condition is increased by 32% on average, and the braking distance is reduced by 15%. The driving condition can enter the smooth driving faster, and the time is reduced by 1.5 s~5 s. The lateral stability parameters are also very much improved compared with the uncontrolled vehicles.

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Section: Introductionmentioning

confidence: 99%

An NMPC-Based Integrated Longitudinal and Lateral Vehicle Stability Control Based on the Double-Layer Torque Distribution

Bai,

Wang,

Jia

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…Park used vehicle dynamics and sensor fusion information to calculate the warning distance, and predicted the vehicle speed before the accident happens to determine the precise warning and braking time [10]. Chelbi pointed out that when the AEB braking is an emergency to prevent a collision, the yaw moment generated by the asymmetric braking force will result in losing control of the vehicle [11], and Xue found that the coordinated control of steer-by-wire (SBW) can solve the problem of vehicle loss of control caused by asymmetric yaw moment when AEB starts on mu-split road conditions [12].…”

Section: Introductionmentioning

confidence: 99%

Automatic emergency braking/anti‐lock braking system coordinated control with road adhesion coefficient estimation for heavy vehicle

Guiyang

Hesen

et al. 2022

IET Intelligent Trans Sys

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The road adhesion coefficient is a key factor influencing automatic emergency braking (AEB) and anti-lock braking system (ABS) safety control of trucks. With the fading factor introduced, and the covariance gain adjusted in real time, the strong tracking unscented Kalman filter (STUKF) algorithm is modified to estimate the road adhesion coefficient more accurately. Composed of an ABS fuzzy sliding mode controller (SMC) and an AEB controller, an AEB/ABS coordinated control strategy with an adhesion coefficient estimation is designed for a three-axle heavy vehicle. The control effects are verified through experiments on various road conditions based on a hardware-in-loop test platform. The test results show that the proposed control strategy has a better braking efficiency than the traditional AEB/ABS and AEB control strategy without adhesion coefficient estimation and can decrease braking distance by 8.4% and braking time by 5.9%, which is beneficial to the vehicle longitudinal safety.

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“…WITH the improvement of people's living standards and the rapid development of automobile industry, people have higher requirements for the safety of road traffic, and autonomous emergency braking system (AEBS) has been widely used. It helps drivers to reduce the risk of collisions while driving on the road and raise the road safety level [1]. Generally, the architecture of AEBS includes three parts, namely sensing system, decision-making system, and execution system.…”

Section: Introductionmentioning

confidence: 99%

An autonomous emergency braking strategy based on non‐linear model predictive deceleration control

Sun

et al. 2022

IET Intelligent Trans Sys

Self Cite

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Surrogate safety measures (SSM) are used to assess the risk for autonomous emergency braking system (AEBS). Developing appropriate SSM and accurately executing the braking request are the key issues. Time‐to‐collision (TTC) is a typical time‐based SSM with limitations. By analyzing the braking process, this paper proposes a new SSM based on deceleration rate to avoid collision (DRAC). As the brake actuator, vehicle electronic stability control (ESC) system has many problems, such as large overshoot and pressure fluctuation. Considering the model of hydraulic control unit (HCU) and vehicle, a deceleration controller based on non‐linear model predictive control (NMPC) is proposed. Based on this, a layered AEBS architecture is proposed. The upper‐layer AEBS controller calculates the expected deceleration based on modified DRAC (MDRAC), and transmits it to the lower‐layer NMPC deceleration controller. Finally, the simulation and experimental tests are carried out. The results show that the system has a fast and stable response. In addition, the performance of the proposed AEBS strategy is tested according to the Euro‐NCAP test protocol. Comparing the results with the TTC method, the proposed method can improve the stability of the distance margin by more than 0.55 m, which ensures the safety and improves the stability of the vehicle.

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Coordinated control of steer‐by‐wire and brake‐by‐wire for autonomous emergency braking on split‐μ roads

Cited by 10 publications

References 35 publications

An NMPC-Based Integrated Longitudinal and Lateral Vehicle Stability Control Based on the Double-Layer Torque Distribution

An NMPC-Based Integrated Longitudinal and Lateral Vehicle Stability Control Based on the Double-Layer Torque Distribution

Automatic emergency braking/anti‐lock braking system coordinated control with road adhesion coefficient estimation for heavy vehicle

An autonomous emergency braking strategy based on non‐linear model predictive deceleration control

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