Abstract
Active suspension systems help to deliver superior ride comfort and can be used to resolve the objective conflict between ride comfort and road-holding. Currently, there exists no method for analyzing the influence of actuator limitations, such as maximum force and maximum rate of change, on the achievable ride comfort. This research paper presents a method that is capable of doing this. It uses model predictive control to eliminate the influence of feedback controller performance and to integrate both actuator limitations and necessary constraints on dynamic wheel-load variation and suspension travel. Various scenarios are simulated, such as driving over a speed bump and inner city driving, as well as driving on a country road and motorway driving, using a state-of-the-art quarter-car model, parameterized for a luxury class vehicle. It is analyzed how comfort, or in one scenario road-holding, can be improved with consideration for the actuator limitations. The results indicate that actuator rate limitation has a strong influence on vertical vehicle dynamics control system performance, and that relatively small maximum forces of around 1000 to 2000 N are sufficient to successfully reject disturbances from road irregularities, provided the actuator is capable of supplying the forces at a sufficiently high rate of change.
Highlights
Together, automated and autonomous driving, and new propulsion technologies, make up one of the biggest research fields in the automotive industry
A constant feedback matrix is derived for the controller, in Model predictive control (MPC) the optimization problem is solved in each time step through the prediction horizon (PH)
In the time step, the system states and PH are updated and the optimization is solved again. This is referred to as receding horizon optimization. As it involves the repeated calculation of an updated feed-forward control problem, MPC is a form of feedback control, because it always starts from measured or estimated states that are independent of model inaccuracies and dependent on non-modelled disturbances
Summary
Together, automated and autonomous driving, and new propulsion technologies, make up one of the biggest research fields in the automotive industry. A typical development methodology is the so called V-Model [1,2], which is defined for mechatronic systems in VDI 2206 [3] It prescribes a framework for development according to requirements defined for the product, subsystem and component levels. Other requirements are more difficult to define, as they are dependent on many internal and external factors, such as customer demand, market strategy, self-set quality standards and price targets. Having set these vehicle-specific requirements on product level, they need to be broken down to subsystem and component level. In the case of vehicle dynamics and Actuators 2020, 9, 77; doi:10.3390/act9030077 www.mdpi.com/journal/actuators
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