Abstract

The optimal control strategy for the decoupling of drive torque is proposed for the problems of runaway and driving stability in straight-line driving of electric vehicles driven by four-wheel hub motors. The strategy uses a hierarchical control logic, with the upper control logic layer being responsible for additional transverse moment calculation and driving anti-slip control; the middle control logic layer is responsible for the spatial motion decoupling for the underlying coordinated distribution of the four-wheel drive torque, on the basis of which the drive anti-skid control of a wheel motor-driven electric vehicle that takes into account the transverse motion of the whole vehicle is realized; the lower control logic layer is responsible for the optimal distribution of the driving torque of the vehicle speed following control. Based on the vehicle dynamics software Carsim2019.0 and MATLAB/Simulink, a simulation model of a four-wheel hub motor-driven electric vehicle control system was built and simulated under typical operating conditions such as high coefficient of adhesion, low coefficient of adhesion and opposing road surfaces. The research shows that the wheel motor drive has the ability to control the stability of the whole vehicle with large intensity that the conventional half-axle drive does not have. Using the proposed joint decoupling control of the transverse pendulum motion and slip rate as well as the optimal distribution of the drive force with speed following, the transverse pendulum angular speed and slip rate can be effectively controlled with the premise of ensuring the vehicle speed, thus greatly improving the straight-line driving stability of the vehicle.

Highlights

  • Distributed drive is a new drive mode for electric vehicles in which the speed and torque of each drive wheel can be controlled quickly, accurately, and independently

  • Studied the influence of different wind angles, crosswinds, and vehicle speeds on the straight-line driving of electric vehicles driven by four-wheel hub motors, and established a direct yaw moment control model based on fuzzy logic to improve the straight-line driving stability of electric vehicles driven by four-wheel in-wheel motors under crosswinds

  • The results proves that velocity of vehicle make biggest difference to the influence on vehicle under the cross wind, and the direct yaw control (DYC) model can decline the amplitude of yaw rate and improve the straight-line stability of vehicle well [13]

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Summary

Introduction

Distributed drive is a new drive mode for electric vehicles in which the speed and torque of each drive wheel can be controlled quickly, accurately, and independently. To ensure the stability of distributed drive electric vehicles in a straight line, three conditions have to be fulfilled: Regardless of whether it is a traditional car or an in-wheel motor-driven electric car, most of the research studies on the control of motion stability use a single variable to optimize the control algorithm. The control process must consider the problem of kinematic coupling to achieve the optimal distribution of wheel drive torque to ensure that each variable can reach the optimal state For this reason, this paper selects the yaw rate, slip rate, and vehicle speed as the control variables, and designs the four-wheel hub motor-driven electric vehicle straightdriving stability decoupling optimal control system to ensure the stability of the vehicle in the straight-line driving process.

Vehicle Stability Analysis in a Straight Line
Vehicle
Vehicle Model
Wheel Hub Motor Matching Calculation
CarSim Vehicle Model Straight-Line Driving Capability Validation
Decoupled Optimal Control of Straight-Line Driving Stability
Expectation Model
Design of the Model Predictive Controller
Design of Acceleration Slip Controller
Yaw Movement Bottom Control
Slip Rate Bottom Control
Decoupling Control
Optimal Distribution of the Generalized Drive Torque
Simulation Analysis of Control Effects
High Adhesion Pavement Simulation Analysis
Figures and
Findings
10. Conclusions

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