Hydrive’s engineers have created a detailed simulation model of a pressure control valve for a client in the automotive supply industry. This valve is one of the most important components in an active roll stabilisation system for high-class cars. The task was to develop a physics-based simulation model able to precisely forecast and investigate the behaviour of both the valve and entire system on a computer.
Among other tasks, our client is using the model to optimise their valve’s design, allowing them to improve the slide valve design and eliminating the need for a complex series of tests in their testing facility. Furthermore, continuing the modelling process is helping to fulfil the aim of integrating the valve model into a more comprehensive overall model of the roll stabilisation system. By considering the pump, electronic control system and the rolling factor itself, it will be possible to investigate behaviour during a typical driving manoeuvre more precisely. This will improve the understanding of cause and effect and enable the important system parameters not included in the valve’s design to be coordinated in a targeted way.
A stabiliser uses a torsion bar to connect the right and left sides of the suspension of the vehicles’ axles. When the vehicles turn a corner, they sway less towards the side, meaning that they hold the road better. Active roll stabilisation uses a hydraulically adjustable stabiliser and an electronic control system to improve vehicle handling further. This makes more extreme driving manoeuvres possible and drivers are also able to choose between two different comfort settings, both features that increase the demands on these hydraulically actuated systems.
The model is structured in such a way that allows the adjustment of design parameters, such as the clearance of leakage gaps, to be analysed directly. CFD calculations are used to work out complicated model parameters, such as hydraulic drag coefficients or flow force. If measurements are unable to be taken from prototypes, such methods increase the models’ performance considerably.