Simulation-Based Testing of Subsystems for Autonomous Vehicles at the Example of an Active Suspension Control System

Abstract

Automated driving functions are expected to increase both the safety and ride comfort of future vehicles. Ensuring their functional safety and optimizing their performance requires thorough testing. Costs and duration of tests can be reduced if more tests can be performed numerically in a feasible simulation framework. This simulation setup must include all subsystems of the autonomous vehicle, which significantly interact with the system under test. In this paper, a modular model chain is presented, which is developed for testing systems with an impact on vehicle motion. It includes trajectory planning, motion control, and a model of the vehicle dynamics in a closed loop. Each subsystem can easily be exchanged to adapt the model chain with respect to the simulation objectives. As a use case, the testing of an active suspension control system is discussed. It is designed directly for use in autonomous cars and uses inputs from the vehicle motion planning subsystem for planning the suspension actuator motion. Using the presented closed-loop model chain, the effect of different actuator control strategies on ride comfort is compared, such as curve tilting. Furthermore, the impact of the active suspension system on lateral vehicle motion is shown.

Design of Virtual Reference Feedforward Controller for an Active Suspension System

“…This problem is non-linear and non-convex. Hence, there are no analytic methods to find an optimum [51]. For the reason, a heuristic optimization method is adopted.…”