Commercial vehicle designers are using a variety of simulation and validation tools as they attempt to find new ways to improve many aspects of vehicle design. Engineers are working with a growing number of tools and physical parameters as they attempt to add features and functions that often require close interaction between systems.
Design software tools allow developers to do more with models, letting them try a range of options before beginning to work with hardware and prototypes. This ability to simulate using virtual components and systems is critical for design teams trying to improve safety and functionality while cutting fuel consumption and emissions.
As vehicles and subsystems get more complex, improvements often come when engineers can analyze many factors using a range of tools. Multiphysics software is becoming increasingly important. Computational fluid dynamics, finite element analysis and model-based simulations are among the tools being used.
“Advanced simulation techniques continue to drive the design process in both the on- and off-highway industries,” said Kiran Govindswamy, Vice President, NVH and Vehicle Engineering at FEV. “This includes the use of hybrid-methodologies which may include the linking of multiple simulation toolchains, like CFD/FEA and MBS/FEA or a judicious combination of test and CAE-based data. As an example, test data for vehicle noise transfer functions can be combined with simulated powertrain/driveline vibration and noise to simulate the customer’s experience at the driver’s ear location, well before physical prototypes become available.”
In areas like engines, it’s difficult to further improve fuel economy while meeting emissions requirements. Minute changes in one area often have unexpected consequences, forcing engineers to process a number of design iterations to understand how tweaks of one parameter impact other facets of the design.
“There’s a lot of complexity, so we need to do a lot of validation,” said Jonathon White, Executive Director of Cummins Engine Business. “From a powertrain perspective, we need to understand how we go about making trade-offs.”
Tool providers have taken different paths to make it easier for engineers and programmers to use software that meets their needs yet still move files easily to other design team members who use data in their development programs. Large suppliers like Siemens and Dassault have acquired several companies. Smaller firms like ANSYS and COMSOL offer multiphysics software that handles many different parameters.
“Multiphysics-based approaches are becoming critical to linking various subsystems to achieve the goal of systems-level optimization,” said Dean Tomazic, CTO at FEV North America. “In the simulation world, this includes models from disciplines such as fluid dynamics, structural analysis, acoustics, and electromagnetics that will need to talk to each other. In many cases, this is achieved via co-simulation methodologies. A similar approach is also increasingly being utilized in the testing world where physical hardware can be replaced by relevant in-the-loop models.”
Analyzing internal combustion is among the growing number of fields that benefit when engineers can examine many different parameters in a single simulation. Subtleties in gas flow, temperature changes and other areas all combine in different ways as various factors change. Similar challenges face those who develop systems that clean up the emissions.
“A couple emissions problems are burning fuel in an efficient way to avoid creating unwanted chemicals and treating the emissions with some type of aftertreatment system,” said Valerio Marra, Marketing Director at COMSOL. “Soot reduction and chemical reduction are purely multiphysics, and that’s what we do. Users can make any change and see how it impacts performance at any temperature.”
The benefits of the shift to modeling and simulation extend beyond the design phase. Long-term aspects of product support can also be improved by using the large volumes of data that come when everything is stored digitally. So-called big data analysis makes it possible for companies to analyze performance parameters and determine the changes that precede failures. That lets suppliers predict when failures are likely.
“With increased validation work, we can better understand potential failure modes and do better diagnostics,” said Brent Keppy, Manager of Commercial Vehicle Powertrains at Robert Bosch. “We can also make predictions so people can replace parts before they fail.”