Review on Traction Control System

Kumar, Arvind

doi:10.1007/978-3-030-92905-3_23

International Conference on Intelligent Emerging Methods of Artificial Intelligence &Amp; Cloud Computing

2022

DOI: 10.1007/978-3-030-92905-3_23

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Review on Traction Control System

Arvind Kumar

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2024

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Design and Analysis of Traction Control Strategies for Icy Road Conditions

Mihalkov,

Caponio,

Hankovszki

et al. 2024

Lecture Notes in Mechanical Engineering

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Traction control (TC) plays a key role in improving vehicle safety, especially for driving scenarios involving extremely low levels of tyre-road friction. In this paper a novel deep reinforcement learning (DRL) based TC strategy is formulated and its performance is compared against a nonlinear model predictive control (NMPC) solution for a simulated straight-line acceleration manoeuvre on icy road conditions. The paper explores the design and assessment of the proposed controllers using a vehicle model experimentally validated on ice. The simulation results show that the DRL solution outperforms the NMPC strategy by reducing the wheel slip ratio peaks and oscillations at the start of an acceleration manoeuvre. Additionally, it converges more quickly to the reference slip and is more computationally efficient.

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Design and Analysis of Traction Control Strategies for Icy Road Conditions

Mihalkov,

Caponio,

Hankovszki

et al. 2024

Lecture Notes in Mechanical Engineering

View full text Add to dashboard Cite

show abstract

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Review on Traction Control System

Cited by 1 publication

References 9 publications

Design and Analysis of Traction Control Strategies for Icy Road Conditions

Design and Analysis of Traction Control Strategies for Icy Road Conditions

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