Paper FR-EA-T38.6
Xu, Yinggang (Tsinghua University)
Wheel Vibration Identification and Suppression of Distributed Drive Electric Vehicles Based on EMB
Scheduled for presentation during the Regular Session "S38b-Towards Scalable and Trustworthy AI in Connected Mobility" (FR-EA-T38), Friday, November 21, 2025,
14:50−15:30, Coolangata 2
2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia
This information is tentative and subject to change. Compiled on October 18, 2025
|
|
Keywords Real-time Incident Detection and Emergency Management Systems in ITS, Energy-efficient Motion Control for Autonomous Vehicles, Verification of Autonomous Vehicle Sensor Systems in Real-world Scenarios
Abstract
Distributed drive electric vehicles (DDEV) employ multiple in-wheel or wheel-side motors as power sources. Due to the direct connection between the motors and the wheels, and the elimination of traditional clutches, the introduction of motors alters the vehicle's inherent damping characteristics through their interaction with components such as the suspension and shock absorbers. Specifically, during Anti-lock Braking System (ABS) intervention, the wheels are susceptible to high-frequency oscillations, which may trigger frequent torque reductions by the ABS. This, in turn, degrades braking performance and may even lead to severe issues, such as the loss of braking force.This paper proposes an anti-oscillation control strategy based on Electro-Mechanical Braking (EMB). First, a tire model is developed that incorporates the damping effects of the motors and the suspension system, and the system's resonance peak frequency is analyzed. Second, a high-frequency oscillation detection method is designed based on wheel speed characteristics. Finally, a Model-Based Predictive and Logic Control (MP-LC) framework is introduced. This framework suppresses high-frequency oscillations by regulating the amplitude and frequency of ABS torque reductions, thereby ensuring sufficient braking force.Simulation results demonstrate that the proposed method significantly reduces braking distance and improves braking deceleration. Compared to conventional ABS algorithms, the proposed strategy achieves substantial improvements in braking performance.
|
|