Reprint

Actuators for Intelligent Electric Vehicles

Edited by
March 2022
330 pages
  • ISBN978-3-0365-3512-8 (Hardback)
  • ISBN978-3-0365-3511-1 (PDF)

This book is a reprint of the Special Issue Actuators for Intelligent Electric Vehicles that was published in

Chemistry & Materials Science
Engineering
Summary

This book details the advanced actuators for IEVs and the control algorithm design. In the actuator design, the configuration four-wheel independent drive/steering electric vehicles is reviewed. An in-wheel two-speed AMT with selectable one-way clutch is designed for IEV. Considering uncertainties, the optimization design for the planetary gear train of IEV is conducted. An electric power steering system is designed for IEV. In addition, advanced control algorithms are proposed in favour of active safety improvement. A supervision mechanism is applied to the segment drift control of autonomous driving. Double super-resolution network is used to design the intelligent driving algorithm. Torque distribution control technology and four-wheel steering technology are utilized for path tracking and adaptive cruise control. To advance the control accuracy, advanced estimation algorithms are studied in this book. The tyre-road peak friction coefficient under full slip rate range is identified based on the normalized tyre model. The pressure of the electro-hydraulic brake system is estimated based on signal fusion. Besides, a multi-semantic driver behaviour recognition model of autonomous vehicles is designed using confidence fusion mechanism. Moreover, a mono-vision based lateral localization system of low-cost autonomous vehicles is proposed with deep learning curb detection. To sum up, the discussed advanced actuators, control and estimation algorithms are beneficial to the active safety improvement of IEVs.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
curb detection; intelligent vehicles; autonomous driving; electro-hydraulic brake system; master cylinder pressure estimation; vehicle longitudinal dynamics; brake linings’ coefficient of friction; ACC; safety evaluation; human-like evaluation; naturalistic driving study; driving behavior characteristic; electric vehicles; independent drive; direct yaw control; torque distribution; ultra-wideband; relative localization; enhanced precision; clock self-correction; homotopy; Levenberg–Marquardt; electric power steering; autonomous driving; steering actuator; driverless racing vehicles; control; autonomous vehicles; lane-changing; decision-making; path planning; autonomous driving; four-wheel independent drive; four-wheel independent steering; path tracking; handling stability; active safety control; electric vehicle; intelligent sanitation vehicle; trash can-handling robot; truss structure; multi-objective parameter optimization; topology optimization; discrete optimization; multiple load cases; intelligent electric vehicles; driver behavior recognition; multi-semantic description; confidence fusion; autonomous vehicles; drift parking; open-loop control; supervision mechanism; electric vehicles; two-speed AMT; in-wheel-drive; shifting process; selectable one-way clutch; electro-hydraulic brake system; master cylinder pressure estimation; five-degree-of-freedom vehicle model; pressure–position model; recursive least square; advanced driver assistant systems; adaptive cruise control; direct yaw moment control; extension control; model predictive control; optimization design; vehicle structure design; uncertainty; deceleration device; tyre-road peak friction coefficient estimation; tyre model; normalization; incentive sensitivity; four-wheel steering; model predictive control; path tracking; semantic segmentation; high-resolution atlas training; super-resolution