News from AVL’s Virtual Vehicle Development - Hybrid Vehicle Powertrain System
AVL Vehicle Model Factory - Automatic Generation of Validated Virtual Prototypes
News from AVL’s Virtual Vehicle Development
Do you spend more than 50% of your working time gathering input data, while setting up your simulation models or working on the correlation? Would you prefer to automatically build up your simulation model based on existing road measurement data? Then you’re in the right place, as thanks to the AVL Vehicle Model Factory this is now possible.
The core of the solution uses measurement data from on-road testing to automatically identify and validate parameters of vehicle systems. These are based on a limited number of standard maneuvers like coast-down, full-load acceleration and constant radius cornering. The identification process generates parameters for the suspension, tires, driving resistance and many more. You can also identify more in-depth parameters from the component testbed data, such as battery or mounting parameters.
The AVL Vehicle Model Factory makes use of AVL’s Global Vehicle Benchmarking database, which supports you on demand with comprehensive vehicle measurement data from more than 500 vehicles. Alternatively, if no measurement data is available yet, this solution will offer the possibility to create completely new vehicle models based on only a few high-level key parameters. It matches them closely with the AVL VSM™ vehicle template database and automatically transforms them into a new vehicle model.
You can use the automatically generated models in any simulation environment supported by AVL VSM™, such as office, Hardware-in-the-loop(Hil), powertrain and other component testbeds. The offering provides numerous benefits for engineers of all different experience levels in simulation.
In a nutshell, the Vehicle Model Factory solution enables users to create validated vehicle models with little effort and time. It can be applied throughout the entire development process, creating new models from scratch and improving existing models with validated parameters that are identified from on-road measurements.