the CIL process, where delays and model uncertainties account for most of the uncertainties. As a result, it is important to quantify each process, as one might not necessarily lead to greater uncertainties than another one.
As shown in Figure H-16, each process should be standardized, from data gathering to model validation and reporting of results.
Hardware set-up process. For any process involving hardware, from HIL to RCP or vehicle testing, detailed test procedures should be developed to ensure consistency across organizations. While some work has been performed for vehicle testing, little to no work has been done for HIL and RCP, and more work is required to validate or improve vehicle test protocols.
Validation process. From a modeling point of view, a critical need is to define what validation means and how it should or could be quantified. While all engineers claim their models are validated, the assumptions behind each one can vary significantly.
A detailed process should be developed, describing what tests should be performed to validate specific subsystems, systems, or vehicles. A report should be provided to the regulatory agency demonstrating the process and the results of the validation. This report could be generic and automatically developed based on the list of required parameters or comparisons for the regulation.
Appropriate modeling level. Using wrong assumptions can lead to erroneous conclusions; errors can come from modeling assumptions or from data. To answer the right questions, users need to have the right modeling tools. For instance, one common mistake is to study engine emissions by using a steady state model or to study component transient behavior by using a backward model. A study providing general guidance would accelerate development of the required models.
Regulatory report. Since the results must be approved for regulatory purposes, a generic report should be defined so that every original equipment manufacturer provides the same information. This report or set of reports would include not only the results but also the assumptions and details of the simulations or tests for selected critical parameters to ensure validity and consistency of the results.