The SystemVision Cloud Team is happy to announce that we’re adding new models to support electro-hydraulic system development. We’ve recently added basic hydraulic elements, such as a pump, valve and cylinder (or linear actuator). We will be adding many more models in the near future, but the examples shown in this blog demonstrate the broad range of electro-hydraulic motion and fluid control systems that are already supported. These basic hydraulic elements, when combined with our existing mechanical, electro-mechanical, electronic and control-block models, support simulation of the multi-discipline interactions that occur in mechatronic systems.
This example is a car lift powered by a three-phase induction motor driven pump. Three valves are used to control the pump outlet flow, directing it either to the extend port of the hydraulic cylinder to lift the car, or to return the flow to the tank or reservoir. When pressurized to approximately 4 MPa, the cylinder lifts the 2000 kg vehicle.
The simulation results in the upper-left show the motor phase A current (dark blue) and shaft speed (green) waveforms. This view is zoomed-in on initial start-up time of the pump. In the upper right, the lift position of the car (red waveform) and the extend port pressure (light blue waveform) are shown over the entire up/down cycle of the lift. Note that fluid compressibility is modeled in the components that have significant volume, including both the variable volume of the actuator, and the constant volume element (vol1) at the pump outlet. The ringing observed on the pressure waveform is due to the dynamic interaction between the mass of the vehicle and the compressibility of the fluid.
This is a “Live” design, so you can move waveform probes around and look at any other signals on nets or within components. For example, move the red and the light-blue waveform probes onto the motor and the hydraulic cylinder respectively, and compare the motor electrical_power_input and cylinder mechanical power output. This can help designers assess the efficiency of the overall system. Models in the SystemVision Cloud Library include power and energy tracking, specifically for this purpose. You can also double-click on components to view their parameter values.
This second example system extends not only the range of interacting technologies, to include analog and digital electronics, but also shows the concept of creating “assembly models”. This fuel injection system includes a DC-motor/pump/pressure-regulator, an electro-hydraulic fuel injector, and a mixed-signal drive circuit that regulates the injector current.
The design shows the ability to reduce the drive current after injection-start, for the purpose of improved efficiency. This leverages a characteristic that is common to electro-magnets, in that a lower current is needed to "hold" the magnet closed than is needed for initial "pull-in". The simulation results shown in the upper left include the commanded injector current set-point (dark blue waveform) and the actual current (orange waveform) which is being regulated by PWM switching of the MOSFET. The results shown in the upper right include the regulated pressure at the injector inlet (green waveform) and injector plunger position (magenta waveform) during the pull-in and release cycle.
Both the pressure regulating pump and the fuel injector component models are created by “assembling” more primitive models of key physical effects. For the pump (top center section of the schematic), this includes the DC motor, an ideal fixed-displacement pump, and a bypass valve. That valve returns pump outlet flow to the tank when the pressure, acting on a control area, exceeds the force of the pre-load spring. The injector model (lower center section of the schematic) includes the electro-magnet, spring/mass/damper and travel-limiting hard-stop, as well as the injection valve and a fixed orifice representing the spray nozzle. The flow rate (light blue waveform) is converted to a quantity and is processed by an integrator math-block model. This provides the value of fuel volume delivered to the engine (red waveform), a key performance metric for an injection event.
The fueling volume depends not only on the duration of the commanded injection time, but also on the dynamic response of the drive circuit and the injector, the regulated pressure from the pump, and other factors. The ability to observe and analyze these multi-discipline interactions is what makes SystemVision Cloud such a useful platform for mechatronic system development.