Open AccessDevelopment of a new traction control system using ant colony optimization
Author(s) -
Liqiang Jin,
Mingze Ling,
LI Jian-hua
Publication year - 2018
Publication title -
advances in mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 40
eISSN - 1687-8140
pISSN - 1687-8132
DOI - 10.1177/1687814018792152
Subject(s) - control theory (sociology) , traction control system , ant colony optimization algorithms , traction (geology) , acceleration , brake , automotive engineering , controller (irrigation) , torque , vehicle dynamics , engineering , nonlinear system , computer science , control engineering , control (management) , mechanical engineering , artificial intelligence , classical mechanics , quantum mechanics , thermodynamics , biology , agronomy , physics , algorithm
An advanced traction control system can help limit wheel rotation and enhance vehicle stability. This article presents a new traction control system under complicated situations, including the low slippery road surface and split-µ road surface. First, a 15-degree-of-freedom nonlinear vehicle dynamics simulation model is established. Then, the driving wheel speed is regulated by adjusting the engine torque and the wheel brake pressure. The engine torque regulation is based on a proportional–integral–derivative plus ant colony optimization controller, and the wheel brake pressure regulation is based on a proportional–integral plus ant colony optimization controller. Finally, the proposed strategies are applied to simulation and road tests. Results indicate that the algorithm exhibits high control accuracy and robust performance. Compared with the traditional proportional–integral–derivative controller, the proposed strategies improve vehicle acceleration performance and stability.
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