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RBS and ABS Coordinated Control Strategy Based on Explicit Model Predictive Control.

Liang Chu1, Jinwei Li1, Zhiqi Guo1

  • 1State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China.

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|May 25, 2024
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Summary
This summary is machine-generated.

This study introduces an explicit model predictive control strategy for electric vehicle braking systems. The new method enhances coordination between regenerative and hydraulic braking for better energy recovery and real-time performance.

Keywords:
coordinated control strategy (CCS)electro-hydraulic composite braking systemerror compensatorexplicit model predictive control (eMPC)four-wheel hub drive electric vehicle

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Area of Science:

  • Automotive Engineering
  • Control Systems
  • Electric Vehicle Technology

Background:

  • Electric vehicles utilize both regenerative braking systems (RBS) and anti-lock braking systems (ABS).
  • Coordination between RBS and ABS can lead to control conflicts, impacting braking effectiveness and real-time control.
  • Existing methods struggle to optimize the combined electro-hydraulic braking system.

Purpose of the Study:

  • To propose and evaluate a novel coordinated control strategy (eMPC-CCS) for electro-hydraulic composite braking systems.
  • To enhance the effectiveness and real-time capability of coordinated control between RBS and ABS.
  • To improve braking energy recovery and overall vehicle braking performance.

Main Methods:

  • Development of a comprehensive braking control framework integrating offline adaptive control law generation and online optimized control law application.
  • Utilizing explicit model predictive control (eMPC) for generating real-time-oriented state feedback control laws based on real-world driving data.
  • Incorporation of a state error compensator to optimize vehicle braking status and ensure robustness.

Main Results:

  • The proposed eMPC-CCS effectively coordinates regenerative and hydraulic braking forces.
  • Offline generation of control laws improves adaptiveness to diverse driving conditions.
  • Online implementation of pre-computed control laws enhances real-time performance.
  • Simulation and HIL testing confirm superior braking energy recovery and real-time capability compared to other control strategies.

Conclusions:

  • The eMPC-CCS provides an effective solution for coordinated control of regenerative and hydraulic braking systems in electric vehicles.
  • The strategy significantly improves braking energy recovery and real-time control performance.
  • The proposed method offers enhanced robustness across various braking conditions.