Global chassis control system using suspension, steering, and braking subsystems

Carlos A. Vivas-Lopez, Juan C. Tudon-Martinez, Diana Hernandez-Alcantara, Ruben Morales-Menendez

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

© 2015 Carlos A. Vivas-Lopez et al. A novel Global Chassis Control (GCC) system based on a multilayer architecture with three levels: top: decision layer, middle: control layer, and bottom: system layer is presented. The main contribution of this work is the development of a data-based classification and coordination algorithm, into a single control problem. Based on a clustering technique, the decision layer classifies the current driving condition. Afterwards, heuristic rules are used to coordinate the performance of the considered vehicle subsystems (suspension, steering, and braking) using local controllers hosted in the control layer. The control allocation system uses fuzzy logic controllers. The performance of the proposed GCC system was evaluated under different standard tests. Simulation results illustrate the effectiveness of the proposed system compared to an uncontrolled vehicle and a vehicle with a noncoordinated control. The proposed system decreases by 14% the braking distance in the hard braking test with respect to the uncontrolled vehicle, the roll and yaw movements are reduced by 10% and 12%, respectively, in the Double Line Change test, and the oscillations caused by load transfer are reduced by 7% in a cornering situation.
Original languageEnglish
JournalMathematical Problems in Engineering
DOIs
Publication statusPublished - 1 Jan 2015

Fingerprint

Chassis
Braking
Subsystem
Control System
Control systems
Vehicle suspensions
Controllers
Fuzzy Logic Controller
Fuzzy logic
Multilayer
Control Problem
Multilayers
Classify
Clustering
Heuristics
Oscillation
Controller
Decrease
Line
Simulation

All Science Journal Classification (ASJC) codes

  • Mathematics(all)
  • Engineering(all)

Cite this

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title = "Global chassis control system using suspension, steering, and braking subsystems",
abstract = "{\circledC} 2015 Carlos A. Vivas-Lopez et al. A novel Global Chassis Control (GCC) system based on a multilayer architecture with three levels: top: decision layer, middle: control layer, and bottom: system layer is presented. The main contribution of this work is the development of a data-based classification and coordination algorithm, into a single control problem. Based on a clustering technique, the decision layer classifies the current driving condition. Afterwards, heuristic rules are used to coordinate the performance of the considered vehicle subsystems (suspension, steering, and braking) using local controllers hosted in the control layer. The control allocation system uses fuzzy logic controllers. The performance of the proposed GCC system was evaluated under different standard tests. Simulation results illustrate the effectiveness of the proposed system compared to an uncontrolled vehicle and a vehicle with a noncoordinated control. The proposed system decreases by 14{\%} the braking distance in the hard braking test with respect to the uncontrolled vehicle, the roll and yaw movements are reduced by 10{\%} and 12{\%}, respectively, in the Double Line Change test, and the oscillations caused by load transfer are reduced by 7{\%} in a cornering situation.",
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Global chassis control system using suspension, steering, and braking subsystems. / Vivas-Lopez, Carlos A.; Tudon-Martinez, Juan C.; Hernandez-Alcantara, Diana; Morales-Menendez, Ruben.

In: Mathematical Problems in Engineering, 01.01.2015.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Global chassis control system using suspension, steering, and braking subsystems

AU - Vivas-Lopez, Carlos A.

AU - Tudon-Martinez, Juan C.

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AB - © 2015 Carlos A. Vivas-Lopez et al. A novel Global Chassis Control (GCC) system based on a multilayer architecture with three levels: top: decision layer, middle: control layer, and bottom: system layer is presented. The main contribution of this work is the development of a data-based classification and coordination algorithm, into a single control problem. Based on a clustering technique, the decision layer classifies the current driving condition. Afterwards, heuristic rules are used to coordinate the performance of the considered vehicle subsystems (suspension, steering, and braking) using local controllers hosted in the control layer. The control allocation system uses fuzzy logic controllers. The performance of the proposed GCC system was evaluated under different standard tests. Simulation results illustrate the effectiveness of the proposed system compared to an uncontrolled vehicle and a vehicle with a noncoordinated control. The proposed system decreases by 14% the braking distance in the hard braking test with respect to the uncontrolled vehicle, the roll and yaw movements are reduced by 10% and 12%, respectively, in the Double Line Change test, and the oscillations caused by load transfer are reduced by 7% in a cornering situation.

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