Torque control strategy of electric racing car based on acceleration intention recognition

Anlu Yuan; Tieyi Zhang; Lingcong Xiong; Zhipeng Zhang; Anlu Yuan; Tieyi Zhang; Lingcong Xiong; Zhipeng Zhang

doi:10.3934/mbe.2024128

Mathematical Biosciences and Engineering

2024, Volume 21, Issue 2: 2879-2900. doi: 10.3934/mbe.2024128

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Torque control strategy of electric racing car based on acceleration intention recognition

School of Mechanical Engineering, Guangxi University, Nanning 530004, China

Received: 14 November 2023 Revised: 14 January 2024 Accepted: 18 January 2024 Published: 25 January 2024

A torque control strategy based on acceleration intention recognition is proposed to address the issue of insufficient power performance in linear torque control strategies for electric racing cars, aiming to better reflect the acceleration intention of racing drivers. First, the support vector machine optimized by the sparrow search algorithm is used to recognize the acceleration intention, and the running mode of the racing car is divided into two types: Starting mode and driving mode. In driving mode, based on the recognition results of acceleration intention, fuzzy control is used for torque compensation. Based on the results of simulation and hardware in the loop testing, we can conclude that the support vector machine model optimized using the sparrow search algorithm can efficiently identify the acceleration intention of racing drivers. Furthermore, the torque control strategy can compensate for positive and negative torque based on the results of intention recognition, significantly improving the power performance of the racing car.
- accelerated intention recognition,
- compensation of torque,
- fuzzy control,
- support vector machine,
- SSA,
- torque control
Citation: Anlu Yuan, Tieyi Zhang, Lingcong Xiong, Zhipeng Zhang. Torque control strategy of electric racing car based on acceleration intention recognition[J]. Mathematical Biosciences and Engineering, 2024, 21(2): 2879-2900. doi: 10.3934/mbe.2024128

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Abstract

A torque control strategy based on acceleration intention recognition is proposed to address the issue of insufficient power performance in linear torque control strategies for electric racing cars, aiming to better reflect the acceleration intention of racing drivers. First, the support vector machine optimized by the sparrow search algorithm is used to recognize the acceleration intention, and the running mode of the racing car is divided into two types: Starting mode and driving mode. In driving mode, based on the recognition results of acceleration intention, fuzzy control is used for torque compensation. Based on the results of simulation and hardware in the loop testing, we can conclude that the support vector machine model optimized using the sparrow search algorithm can efficiently identify the acceleration intention of racing drivers. Furthermore, the torque control strategy can compensate for positive and negative torque based on the results of intention recognition, significantly improving the power performance of the racing car.

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