It concerns the introduction of new software tools, the integration between those, and a refinement of simulation and testing processes to improve collaboration between analysis teams that handle different applications.
A modern development process should be able to predict the behavior of the complete system for all functional requirements and including physical aspects from the very beginning of the design cycle.
Based on this information, manufacturers can send software updates to continue optimizing behavior, or to adapt to a changing operational environment.
It challenges design teams, as they need to react quickly and make behavioral predictions based on an enormous amount of data.
That calls for a firm globally operating product lifecycle management system that starts with requirements definition.
Manufacturers gradually deploy the following methods and technologies, to an extent that their organization allows it and their products require it: In this multi-disciplinary simulation-based approach, the global design is considered as a collection of mutually interacting subsystems from the very beginning.
From the very early stages on, the chosen architecture is virtually tested for all critical functional performance aspects simultaneously.
Closing the loop happens on 2 levels: Closed-loop systems driven product development aims at reducing test-and-repair.
3D simulation or 3D CAE are still indispensable in the context of predictive engineering analytics, becoming a driving force in product development.
Software suppliers put great effort into enhancements, by adding new capabilities and increasing performance on modeling, process and solver side.
Software suppliers achieve this through offering co-simulation capabilities for de:Model in the Loop (MiL), Software-in-the-Loop (SiL) and Hardware-in-the-Loop (HiL) processes.
This provides the right combination of accuracy and calculation speed for investigation of concepts and strategies, as well as controllability assessment.
Using SiL validation on a global, full-system multi-domain model helps anticipate the conversion from floating point to fixed point after the code is integrated in the hardware, and refine gain scheduling when the code action needs to be adjusted to operating conditions.
[29][30] During the final stages of controls development, when the production code is integrated in the ECU hardware, engineers further verify and validate using extensive and automated HiL simulation.
This HiL approach allows engineers to complete upfront system and software troubleshooting to limit the total testing and calibration time and cost on the actual product prototype.
During HiL simulation, the engineers verify if regulation, security and failure tests on the final product can happen without risk.
When replacing the global system model running in real-time with a more detailed version, engineers can also include pre-calibration in the process.
Besides, also in other development stages, combining test and simulation in a well aligned process will be essential for successful predictive engineering analytics.
As part of predictive engineering analytics, modal testing has to evolve, delivering results that increase simulation realism and handle the multi-physical nature of the modern, complex products.
In general a whole new range of testing capabilities (some modal-based, some not) in support of simulation becomes important, and much earlier in the development cycle than before.
These hybrid modeling techniques will allow realistic real-time evaluation of system behavior very early in the development cycle.
They will include predictive functionalities based on system models, adapt to their environment, feed information back to design, and more.
Only this can enable traceability between requirements, functional analysis and performance verification, as well as analytics of use data in support of design.