Abstract

This paper presents a braking strategy analysis for a Formula SAE electric race car. The proposed braking strategy aims to increase the recovery energy by a relevant distribution of the braking forces between the rear and front wheels. A mathematical model of the car is presented, and a simulation is performed in Matlab-Simulink. The model is organized using the energetic macroscopic representation graphical formalism. A real racetrack driving cycle is considered. Three braking strategies are compared considering the energy recovery and the vehicle stability. The simulation results show that the proposed strategy enables higher energy recovery while avoiding locking on both rear and front wheels. As in such a race the driving range is fixed, the reduction in energy consumption can be used to reduce the battery size. The battery weight can thus be decreased to improve the vehicle performance during competition.

Highlights

  • Greenhouse gas (GHG) emissions and air pollution are major concerns related to the massive deployment of gasoline and diesel vehicles

  • The harmful effects of GHG and air pollution on human health should drastically change the trends in transportation evolution

  • The study was performed in AVL/CRUISE software, and the results showed that braking distribution biased to the rear wheels increases the energy recovered

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Summary

Introduction

Greenhouse gas (GHG) emissions and air pollution are major concerns related to the massive deployment of gasoline and diesel vehicles. The results obtained with the MPC were compared to a rule-based controller for dry, wet, and snow road conditions Other works such as [12,13,14,15] presented different braking strategies with similar objectives and applications in EVs. The works mentioned above used different strategies to define the distribution of braking forces and the participation of regenerative braking in passenger EVs. it is not common to find braking strategies for rear wheels traction EVs, such as formula race cars. The torque and angular speed in the transmission are converted to longitudinal force and car velocity through the wheels as follows (mono-physical conversion element in EMR).

Inversion-Based Control of the Studied Car
Section 4.2.
Braking Strategy
Distribution of strategy
RBS and FBS Contribution in the Rear Wheels
The braking k is calculated based on the flowchart presented in
Results
Studied
Aerodynamic parameters
Simulation Using the Proposed Braking Strategy
Comparison of Different Braking Strategies
Conclusion
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