# Research on Anti-Skid Control Strategy for Four-Wheel Independent Drive Electric Vehicle

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## Abstract

**:**

## 1. Introduction

## 2. Dynamic Model Establishment

#### 2.1. Vehicle Dynamics Model

_{s}is the spring mass; a

_{x}is the longitudinal acceleration of the car; a

_{y}is the lateral acceleration of the car; A is the windward area; C

_{D}is the wind resistance coefficient; δ is the steering angle of the front wheels of the vehicle; F

_{xi}is the longitudinal force of each wheel; F

_{yi}is the lateral force of each wheel; F

_{w}is wind resistance; ρ is the air density; V is the speed; μ is the longitudinal speed; v is the lateral speed; $\gamma $ is the yaw rate; I

_{z}is the moment of inertia of the vehicle around the axis; d

_{f}is the front axle track; d

_{r}is the track of the rear axle; and a, b are the distances from the center of mass of the vehicle to the front and rear axles, respectively.

#### 2.2. Tire Model

_{d}is the driving torque of the driving wheel, F

_{x}is the longitudinal force of the tire, R is the rolling radius of the tire, and T

_{d}= 0 for the non-driving wheel.

## 3. Design on Driving Anti-Skid Control Strategy

- (1)
- The current slip rate of the driving wheels and the road adhesion coefficient is calculated according to the vehicle dynamics model, tire model and motor model. The road slip rate and the wheel adhesion coefficient are used as the input of the road surface recognition controller, the current road surface condition is determined according to the road surface recognition controller, and the road surface parameters of the current road surface are calculated.
- (2)
- Then, the slip rate control module is input, and the optimal slip ratio suitable for the current road surface is determined through the control algorithm. By adjusting the pedal signal, the wheel speed and the vehicle speed can be adjusted in realtime to prevent the wheel from slipping.

#### 3.1. Wheel Slip Mechanism

#### 3.2. Road Identification Module

_{i}($i=1,2,3,4$).

_{opt-ij}and the peak adhesion coefficient μ

_{max-ij}of the current road surface are calculated by using the weighting method. To further match the current road surface parameters, the road surface is identified, as is the current road surface type.

#### 3.3. Slip Rate Control Module

## 4. The Simulation Analysis

^{2}, the moment of inertia about the y-axis is 2031.4288 kg∙m

^{2}, the moment of inertia about the z-axis is 2031.4288 kg∙m

^{2}and the radius of the rear axle is 330 mm.

#### 4.1. Road Recognition Module Verification

#### 4.2. Slip Rate Control Module Verification

## 5. Conclusions

- (1)
- The pavement recognition module establishes the standard pavement curve μ-s curve, and calculates the maximum adhesion coefficient of the pavement and the optimal slip rate when the vehicle is sliding.
- (2)
- The slip rate control module adopts a fuzzy PID control algorithm. The change rate of the difference between the real-time slip rate of the wheel and the target slip rate E and E is input, the torque adjustment signal is output, and the pedal signal is calculated and output to the wheel hub motor to further prevent the vehicle from slipping.
- (3)
- Carsim/Simulink software modeling is completed, and simulation verification of driving anti-skid controller is carried out. The results show that the road surface identification module in the driving anti-skid control strategy can quickly identify the current road surface conditions, and the slip rate control module can reasonably control the output motor driving torque, reasonably and effectively reduce the slip degree of the vehicle, and avoid the slip of the vehicle. Simulation results verify the feasibility of the control strategy. In the process of driving anti-skid, the standard road surface selected is not comprehensive enough and needs to be further optimized, so as to improve the efficiency and accuracy of road surface identification.

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

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Parameter Road Type | Dry Asphalt | Wet Asphalt | Snow Pavement | Ice Pavement |
---|---|---|---|---|

C1 | 1.2801 | 0.857 | 0.1946 | 0.05 |

C2 | 23.99 | 33.822 | 94.129 | 306.39 |

C3 | 0.52 | 0.3470 | 0.0646 | 0.001 |

Sopt | 0.170 | 0.131 | 0.065 | 0.03 |

μmax | 1.171 | 0.8 | 0.190 | 0.05 |

Adhesion Coefficient Slip Rate | Dry Asphalt S | Wet Asphalt M | Snow Pavement B | Ice Pavement VB |
---|---|---|---|---|

Dry asphalt H | ES | D | TD | TD |

Wet asphalt M | GS | ES | TD | TD |

Snow pavement L | TD | TD | ES | D |

Ice pavement VL | TD | TD | GS | ES |

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**MDPI and ACS Style**

Zhang, C.; Ma, J.; Chang, B.; Wang, J.
Research on Anti-Skid Control Strategy for Four-Wheel Independent Drive Electric Vehicle. *World Electr. Veh. J.* **2021**, *12*, 150.
https://doi.org/10.3390/wevj12030150

**AMA Style**

Zhang C, Ma J, Chang B, Wang J.
Research on Anti-Skid Control Strategy for Four-Wheel Independent Drive Electric Vehicle. *World Electric Vehicle Journal*. 2021; 12(3):150.
https://doi.org/10.3390/wevj12030150

**Chicago/Turabian Style**

Zhang, Chuanwei, Jian Ma, Bo Chang, and Jianlong Wang.
2021. "Research on Anti-Skid Control Strategy for Four-Wheel Independent Drive Electric Vehicle" *World Electric Vehicle Journal* 12, no. 3: 150.
https://doi.org/10.3390/wevj12030150