Global Chassis Control System Using Suspension, Steering, and Braking Subsystems

Abstract

A novelGlobal 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.

Anti-Lock Braking System Components Modelling

“…(3) (4) The difference between the wheel acceleration and brake pressure can be calculated by the next equations 24:…”

The cross-coupling of lateral-longitudinal vehicle dynamics: Towards decentralized Fault-Tolerant Control Schemes

“…Therefore, it is proposed to achieve the required neutral-steer response directly by the closed loop dynamics, reducing the need for pre-filtering elements or reference model. The yaw rate reference signal is set to [26]:…”

Review of integrated vehicle dynamics control architectures

“…Controllers have to work simultaneously. They have their own information system and Electronic Control Unit (ECU), which require more costs and space [10]. The only way to add "integration" in the process is by allowing additional communications between the controllers as the Fig.…”

“…• Fault-tolerance: it ensures a minimum of operations safety even if the high-level controller fails, • Extensibility: it can be evolved to a multi-layer hierarchical structure to add more functionalities, • Modularity: it allows manufacturers and suppliers develop independently complementary control algorithms. Using this structure, [10] used three main layers with two levels of abstraction: 1) Decision Layer: Identifies the current driving situation first, then decide how to coordinate the subsystems actions, 2) Control Layer: Transforms the control objectives generated by the Decision Layer to references for each of the local controllers, 3) Physical Layer: Contains simply the different actuators and sensors. It should be noted that the decision layer plays a major role to ensure the overall system safety.…”

“…It is responsible of two main tasks: classifying the current driving situation and deciding how coordination should be made. For example, in [10], a k-means data-based algorithm and a decision logic module based on a set of heuristic rules have been used 1 .…”