Acceleration Slip Regulation for Electric Vehicles Based on Fuzzy PID Controller

Nguyen, An-Toan; Nguyen, Binh Minh; Trovão, João P.; Ta, Minh C.

doi:10.1109/iccais56082.2022.9990274

Cited by 1 publication

(1 citation statement)

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“…Some researchers use fuzzy control logic, taking the accelerator pedal position and the slope of the tire/road adhesion coefficient as inputs to output the required motor torque to achieve ASR. This method is simple in principle and does not require an accurate model, but it has extensive theoretical research and is difficult to implement in actual controllers [27][28][29][30]. In the lateral stability of vehicles, two key aspects need to be considered.…”

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%